Response to Peer Review of: Ricardo
            Computer Simulation of Light-Duty
            Vehicle Technologies for Greenhouse
            Gas Emission Reduction in the
            2020-2025 Timeframe
&EPA
United States
Environmental Protection
Agency

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                 Response to Peer Review of: Ricardo
                  Computer Simulation of Light-Duty
                 Vehicle Technologies for Greenhouse
                     Gas Emission Reduction in the
                           2020-2025 Timeframe
                               Assessment and Standards Division
                              Office of Transportation and Air Quality
                              U.S. Environmental Protection Agency
                                    Prepared for EPA by
                                      Ricardo, Inc.
                                         and
                         Systems Research and Applications Corporation (SRA)
                                 EPA Contract No. EP-C-11-007
                                 Work Assignment No. 0-12
                 NOTICE

                 This technical report does not necessarily represent final EPA decisions or
                 positions. It is intended to present technical analysis of issues using data
                 that are currently available. The purpose in the release of such reports is to
                 facilitate the exchange of technical information and to inform the public of
                 technical developments.
&EPA
United States
Environmental Protection
Agency
EPA-420-R-11-021
December 2011

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Peer Review Response Document                                                  November 29, 2011
Introduction
As the U.S. Environmental Protection Agency (EPA) develops programs to reduce greenhouse gas
(GHG) emissions and increase fuel economy of light-duty highway vehicles, there is a need to evaluate
the costs of technologies necessary to bring about such improvements.  Some potential technology paths
that manufacturers might pursue to meet future standards may include advanced engines, hybrid electric
systems, and mass reduction, along with additional road load reductions and accessory improvements.
One method of assessing the effectiveness of future light duty vehicle (LDV) technologies on future
vehicle performance and GHG emissions in the near-term timeframe is through modeling assessments.

Ricardo, Inc. developed such simulation models and documented the relevant technologies, inputs,
modeling techniques, and results of the study in its April 6, 2011, Draft Report, "Computer Simulation of
Light-Duty Vehicle Technologies for Greenhouse  Gas Emission Reduction in the 2020-2025 Timeframe"
contained in the supplement of this document.  Ricardo performed this work under a subcontract to
Systems Research and Applications Corporation (SRA) under EPA contract EP-W-07-064. The report
documented both LDV technologies likely to be available within the specified timeframe and the
development of a visualization tool that allows users to evaluate  the effectiveness of such technology
packages in both reducing GHG emissions and their resulting effect on vehicle performance. The
technologies addressed including conventional and hybrid powertrains, transmissions, engine
technologies and displacement, final drive ratio, vehicle weight,  and rolling resistance were examined for
seven light-duty vehicle classes.

EPA then contracted with ICE International (ICE) to coordinate an external peer review of the inputs,
methodologies,  and results described in this report. The review was broad and encouraged reviewers to
address  the adequacy of the model's inputs and parameters, the simulation methodology, and its
predictions as well as the report's completeness and adequacy for the stated goals. Through this process,
EPA was able to conduct a thorough peer review with reviewers  representing subject matter expertise in
advanced engine technology, hybrid vehicle technology, and vehicle modeling.

The following five individuals agreed to participate in the peer review:

    1.   Dr. Dennis Assanis, University of Michigan
   2.   Mr. Scott McBroom, Fallbrook Technologies, Inc.
   3.   Dr. Shawn Midlam-Mohler, The Ohio State University
   4.   Dr. Robert Sawyer, University of California at Berkeley
   5.   Mr. Wallace Wade, Ford Motor Company (Retired)

ICE provided reviewers with the following materials:

   •    Draft proj ect report by Ricardo (2011);
   •    The Ricardo Computer Simulation tool;
   •    The Peer Reviewer Charge to guide their evaluation; and
   •    A template for the comments organized around the Peer  Reviewer charge.

The consensus of the first review based on these materials was that reviewers needed more information
than was provided in the Ricardo report to complete their review. EPA then requested a second round of
peer review in which the peer reviewers were provided more detailed information. Ricardo provided 45

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additional PowerPoint presentations and documents, which included more clarity on assumptions,
pictures of engine maps, and other pertinent information.  Only three of the original reviewers were
available to participate in the second round of peer review:

    1.  Mr. Scott McBroom, Fallbrook Technologies, Inc.
    2.  Dr. Shawn Midlam-Mohler, Ohio State University
    3.  Dr. Robert Sawyer, University of California, Berkeley

More detail about the review is available in the ICF report entitled: Peer Review ofRicardo, Inc. Draft
Report,  "Computer Simulation of Light-Duty Vehicle Technologies for Greenhouse Gas Emission
Reduction in the 2020-2025  Timeframe" (September 30, 2011) contained in the supplement of this
document. In response to this peer review, EPA issued a follow-on work assignment to SRA (and Ricardo
as SRA's subcontractor) to address the peer review comments. The response to the peer review involved:

    •  Significant revisions to the draft report
    •  A user's guide to the Data Visualization Tool referenced in the report
    •  Specific responses to each of the peer review comments

The final version of the report  includes numerous changes, especially in Sections 4 and 6 of the report,
and new appendix and attachment materials. The revised report serves as the primary response to the
overall peer review input.  The final report with all revisions is dated November 14, 2011. In addition,
Ricardo, Inc., as a subcontractor to SRA, is preparing a separate user's guide to the tool.  The final guide
will be made available to the public by EPA upon final approval of that document.

Finally, this companion report presents item-by-item responses to each individual comment raised in the
peer review. The responses reflect discussions about each of the comments between EPA, SRA, and
Ricardo.  Many of the responses refer to the specific revisions within the report that represent the decision
on how best to address the comment. Others provide a brief response in the event that the comment was
handled through the  general  process of revising the report, where the comment can be answered with a
clarifying response but without any corresponding report revision, or where EPA and the project team
determined that no revision was warranted given the nature of the comment within the context of the
study.

The comments in the following Table 1 are the same as those presented in Table 2 to ICF's report of the
peer review findings. In developing the responses, we added a column with a report section reference, if
applicable.  Where no specific report section applies to the specific comment, we used "General" in that
column. We then sorted the comments based on this column.

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                                    Table 1:  Response to Individual Peer Review Comments
Charge Question
Topic
Other Comments
Completeness
Inputs and
Parameters
Completeness
Completeness


Section 3.3
Technology
Selection
Process
Section 3.2
Ground Rules for
Study
Section 3.3
Ground Rules


14
124
63
123
128
Con,™,
Including the membership of the advisory committee would be
appropriate.
Who is on the Advisory Committee? Is it independent? How did
the program team come up with the comprehensive list of
potential technologies? (From the phone call it sounded like it was
based on what models Ricardo had in their library. This is
concerning.)
The vehicle and technology selection process needs further
discussion. My experience in these large simulation studies is
that the vast majority of the time needs to be spent on the
selection and once selected agreeing upon the model/data.
How did the group arrive at the seven vehicles? While it show
comprehensiveness, it's possible to see that there could be some
overlap. If one looks at the engine and transmissions packages
available in these vehicles already you can see the overlap.
Reducing the number of vehicles might save on the number of
runs you'll need to make.
Regarding "Current (2010) maturity of the technology", how was
maturity ranked?

The Advisory Committee is described in Chapter
1.
The Advisory Committee is described in Chapter
1.
EPA and Ricardo appreciate the comment; see
section 3 of the final report. No further response
is required.
Some overlap is expected as the utility of these
vehicles varies based on vehicle class. The 5
center vehicle classes are carryover from the
previous work and were used for consistency
moving forward into the future technologies. The
smallest class was added to reflect this growing
segment and the class 3 truck was added to help
EPA bridge the gap between light and heavy
duty analysis.
Ricardo subject matter experts provided the
rankings for the various technologies.
Section
Ref e re nee
1
1
3.2
3.3
3.3

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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                 Specific
e Question     Assump
Comment
Simulation
methodology
             Section 3.4 CSM
             Approach
77
Is the CSM approach used in other applications? If so it would be
helpful to give citations.  If it was developed by Ricardo, that
should be stated. The discussion refers to physics based models,
but other than that very little about the type of modeling is
discussed. I  recall on the phone call that lumped parameter
models were mentioned. There is no discussion of that.
In the final report, Ricardo has added significant
details of the modeling and provided graphics to
illustrate a number of the issues. As for CSM, it
is a standard approach to analyzing complex
systems with many variables, and Easy5 as a
tool for CSM has been used in many
applications, including rocket and aircraft design,
as well  as automotive design and modeling
applications. The report focuses on the findings
of the study, and not the validation of CSM as an
approach.
3.4
Other Comments
                                19
            The characterization of the modeling methodology as objective
            and "scientific" suggests that the simulation is composed of
            rigorous, first-principle expressions for the various phenomena
            without using "correlations", "empirical formulas", and
            "phenomenological models". Are these conditions truly met? For
            instance, in many cases, steady-state dyno test data are the basis
            of an engine map featuring a certain technology. In other cases,
            available data were scaled based on
            empirical/proprietary factors and modifiers. The report should not
            characterize the study as "scientific" unless data uncertainty is
            discussed and shown in appropriate situations. For example,
            Table 7.1 presents comparisons between simulated and actual
            vehicle fuel economy performance. Given the various subjective
            assumptions involved in the analysis, the authors should
            comment whether the noticeable differences in certain cases are
            significant.
                                                             Complex systems modeling is a recognized
                                                             scientific-based approach to analysis of complex
                                                             systems, so the language used in the draft report
                                                             remains in the final report. However, the point is
                                                             taken that the study takes this science-based
                                                             modeling approach, and applies certain
                                                             assumptions and other factors based on
                                                             empirical considerations, some of which are
                                                             qualitative and potentially subjective.
                                              3.4,7.1,8
                                                                                  4

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                                                   Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
                               70
            No mention or consideration of cylinder deactivation technologies.
            This seems like pretty low hanging fruit, even on downsized
            boosted engines, especially if you deploy DVA.
                                                                                                                                                            Section
                                                                                                                                                           Reference
                                                            Ricardo subject matter experts along with the
                                                            study group and engine manufacturers could not
                                                            justify cylinder deactivation on four cylinder
                                                            engines at this  time due to significant NVH and
                                                            durability issues.  Cylinder deactivation was
                                                            included in the  previous study.
Completeness
                               126
            Why wasn't HCCI technology considered? From the publications
            this seems to be a candidate for production in the next 10 yrs.
                                                            Ricardo subject matter experts along with the
                                                            study group could not justify this technology for
                                                            full range vehicle applications. HCCI was
                                                            included in the previous study.
Completeness
             Section 4.
             Technology
             Review and
             Selection
127
Regarding qualitative evaluation of technology "Potential of the
technology to improve GHG emissions on a tank to wheels basis",
since this was a qualitative assessment I think it would be better
to include well to wheels.
A well to wheels analysis was beyond the scope
of this study.
Completeness
                               129
            Citations required for statement" SI engine efficiency to approach
            Cl efficiency in the time frame considered"  This represents
            relatively large gains in SI technology compared to Cl, however
            EU and Japanese engine companies are making big
            improvements on Cl as well.
                                                            The technology details in Section 4 are a basis
                                                            for this general expectation, which clarifies why
                                                            the study focused significant energy on the SI
                                                            category. Ricardo's professional judgment is
                                                            that, given the emission standards, this
                                                            statement is a reasonable expectation for the
                                                            study time frame.

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                                                 Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Comment
                                                                                                                                                         Section
                                                                                                                                                        Reference
Other Comments
             Engine Models
256
The description of the derivation of the engine models in the
report was, at best, vague, as illustrated by the two examples
below:

Example 1:  Stoichiometric Dl Turbo
The current research engines of this configuration were reported
to be the Sabre engine developed by Lotus and the downsized
concept engine developed by Mahle.  Since the engine modeled
in the Ricardo report had a peak BMEP of 25-30 bar and used
series-sequential turbochargers, the Sabre engine is not
applicable since it only had a peak BMEP of 20 bar and used a
single stage turbocharger (Coltman et a., 2008; Turner et al.,
2009).

On the other hand, the Mahle engine appeared to be directly
applicable, since it had a peak BMEP of 30 bar and used series-
sequential turbocharging (Lumsden et al., 2009).  Since Lumsden
et al. provided the BSFC map for this engine, shown below, it is
not clear why the Ricardo report could not have shown this map,
or a map derived from this one, and then described how it was
derived and/or combined with other maps to provide the model
used in the report. (See Exhibit 3)
See revised section 4 for additional details and
engine technology examples.
Other Comments
             Engine Models
258
The report should explain whether the engine model is only a map
of BSFC vs. speed and load, or if the engine model includes
details of the turbocharger, valve timing, and control algorithms for
parameters such as air/fuel ratio, spark/injection timing, EGR rate,
boost pressure, and valve timing.
All of these parameters are inherent to the
engine map.  See revised section 4.

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                                                  Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Comment
                                                                                                                                                            Section
                                                                                                                                                           Reference
Other Comments
             Engine Models
259
Advanced valvetrains were included in many of the advanced
engines (page 12). However, the method for applying these
advanced valvetrains to the engine maps was not provided. Also,
no description of the control strategy for these valvetrains was
provided. The report did not provide a description of how the
reduction of pumping losses with an advanced valvetrain was
applied to a downsized engine that already had reduced pumping
losses. Therefore, no assessment of how the model handled
synergies could be made.
Section 4 has been revised with this additional
information.
Recommendations
             Engine Models
311
Describe what the "other inputs" are to the engine maps.
See Chapter 4.
Inputs and
Parameters
             Section 4
64
There was no model data provided. Engine maps, transmission
efficiency maps, battery efficiency maps etc need to be in the
Appendices. The black box nature of the inputs is disconcerting.
The final report adds detail on these types of
issues; see especially changes to sections 4 and
6.8.
4,6.8
Inputs and
Parameters
             Engine Models
306
The engine model is the most important element in successfully
modeling the capability of future vehicles, since it is the
responsible for the largest loss of energy. It is also one of the
most difficult aspect to predict since it involves many complicated
processes (i.e. combustion, compressible flow) which must be
considered in parallel with emissions compliance (i.e. in-cylinder
formation, catalytic reduction.) Because of this, this sub-model
must be viewed with extreme scrutiny in order to ensure quality
outputs from the model.
See revised section 4.1.
4.1
Inputs and
Parameters
             SI Engine Maps
             and Diesel
             Engine Maps
395
For the 2020 engine maps, there is insufficient detail in this
presentation on how the maps were generated. Getting accurate
simulation requires careful validation of the model as well as the
data in the model - these engine maps are not sufficiently well
documented for me  to make a judgment on their suitability for the
overall goal of the simulator.  I am well aware that these future
engines do not exist, but there had to be some process of
generating these  engine maps. Without more information on this
process it is simply not possible to comment on their accuracy.
See revised section 4.1.
4.1

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                                                   Table 1:  Response to Individual Peer Review Comments
                T
                       Specific       Comment
Charge Question    Assump
Completeness
                   Sections 4.1 and
                   4.2
130
There's no descriptions of the models. There are only descriptions
of the technologies and their perceived benefits. The reader has
to assume that the same modeling approach was used to model
each technology, but I know from personal experience this is very
difficult and most likely not the case.
The final report adds details on the study's
modeling approach.  See sections 4.1 & 4.2,
which also reference chapter 6. Engine modeling
is described in Section 6.3.  The revised Figure
6.1 provides an overall vehicle diagram.
4.1,4.2,
6.3
Recommendations
                   Specific
                   recommendations
                   for improvements
238
Provide descriptions of the algorithms used for engine control,
transmission control, hybrid system control, and accessory
control.
See revised sections 4.1 and 6.
4.1,6
Simulation
methodology
                   Engines and
                   Engine Models
                   (Sections 4.1  and
                   6.3)
31
Specific suggestions regarding models that need more detailed
coverage: The report lacks detail on the specifics on the different
engine design and operating choices. For instance, what was the
compression ratio (and limit) that was used? What is the
equivalence ratio, or range considered, for the lean burn engine?
How much EGR has been used across the speed and load
range? What constraints, if any, were applied to the simulations to
account for combustions limitations such as knock and
flammability limits? The NOx aftertreatment/constraints  section
could also be expanded.
The final report adds detail on the compression
ratio, and the use of 0 for LBDI.  The report also
details the range of EGR used, and expands on
the NOx treatment/constraints. The final report
also adds a chart for the switching zone, and
includes text concerning the exhaust
temperatures. These factors were all built in to
the fueling maps. See revised sections 4.2.1
through 4.2.3 and 4.2.6.
4.1,6.3
Simulation
methodology
                   Engines and
                   Engine Models
                   (Sections 4.1  and
                   6.3)
32
Specific suggestions regarding models that need more detailed
coverage:
In cases where engine models have been used to generated
maps, how was combustion modeled? For instance, discussion is
made as to the heat transfer effect resulting from surface to
volume changes connected to downsizing. More detail on the heat
transfer assumptions that go into the applied heat transfer factor
would be helpful. Was heat transfer modeled based on Woschni's
correlation? What about friction scaling with piston speed? This
would change with stroke at a constant RPM. Also friction would
change with the number of bearings and cylinders.
The fueling maps were adjusted to account for
the number of cylinders and the per-cylinder
displacement. Detailed combustion models were
not within the scope of the study; the fueling
maps were based on experimental data and
experience with the incorporated technologies.
4.1,6.3

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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                 Specific
e Question     Assump
Other Comments
             Advanced
             Valvetrains
             (Section 4.1.1)
Comment
56
The report states that advanced valvetrain systems improve fuel
consumption and GHG emissions mainly by improving engine
breathing. Other benefits cited are in supporting engine
downsizing and faster aftertreatment warm-up.  Beyond improving
volumetric efficiency and reducing pumping losses, advanced
valvetrains can enable compression ratio variation to increase fuel
economy and avoid knock, alter the combustion process by
modulating trapped residual, and enable cylinder deactivation to
reduce pumping losses. From the report, it is not clear which of
the possible benefits of the advanced valvetrain packages have
been harnessed in each case. A more systematic analysis of
technology package combinations is warranted as several are
synergistic but not additive.
The discussion in section 4.2.6.1 indicates the
improvements expected in the fueling map from
use of a CPS system in the 2020-2025
timeframe versus the current valvetrain.  The
other possible benefits of advanced valvetrains
noted by this reviewer were not included in the
final report, as Ricardo, based on its experience,
believes these are less important characteristics
than the elements included in the report.
4.1.1
Simulation
methodology
             Section 4.1.1
             Advanced
             Valvetrains
82
There is no explanation of how CPS and DVA systems were
modeled. There was only a description of what CPS and DVA is.
See revised section 4.1.1.
4.1.1
Inputs and
Parameters
             Advanced
             Valvetrains
             (Section 4.1.1)
318
Two types of advanced valvetrains were included in the study,
cam-profile switching and digital valve actuation.  Both of these
technologies are aimed at reducing pumping losses at part-load.
The impact of these technologies is difficult to predict using
simplified modeling techniques and typically require consideration
of compressible flow and a 1-D analysis at a minimum.  Even with
an appropriate fidelity model, these systems require significant
amounts of optimization in order to determine the best possible
performance across the torque-speed plane of the engine. It is
unclear how these systems were used to generate accurate
engine maps given the level of detail  provided in the report.
The final report shows how and where cam-
profile switching and digital valve actuation
improve the fueling map. See the additional
material in Section 4.1.1, including new figures to
help show the physical approach and provide a
range of improvement.
4.1.1
Recommendations
             Advanced
             Valvetrains
             (Section 4.1.1)
319
Describe how variable valve timing technologies were applied to
the base engine maps.
See response to Comment Excerpt 318.
4.1.1

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                                                  Table 1:  Response to Individual Peer Review Comments
                T
                       Specific       Comment
Charge Question     Assump
Recommendations
                   Advanced
                   Valvetrains
                   (Section 4.1.1)
                  320
            Describe the process of determining the extent of the efficiency
            improvement.
See response to Comment Excerpt 318.
4.1.1
                                                 Describe how optimal valve timing was determined across the
                                                 variety of engines simulated.
Recommendations
Advanced
Valvetrains
(Section 4.1.1)
321
See response to Comment Excerpt 318.
4.1.1
Completeness
                   Section 4.1.2 Dl
                   Fuel Systems
                  131
            No discussion of Dl control strategy. How was it selected? Was
            there a separate optimization of Dl control or was it one size fits
            all?
Dl controls were not modeled. See revised
sections 4.1.1 and 4.1.2.
4.1.1,4.1.2
Inputs and
Parameters
                                     21
                              Some examples of the types of inputs and parameters that would
                              be helpful to include the following in the report: Any published fuel
                              economy maps, or other related data, with actual numbers. For
                              proprietary maps and data, a normalized representation would be
                              useful, as well, without the actual bsfc values shown on the map.
                                                                        To address this concern, the final report uses
                                                                        public fueling maps concepts, and then illustrates
                                                                        the technical transformation of baseline
                                                                        technologies to the future. See especially revised
                                                                        Sections 4.1 and revised Section 4.2. New
                                                                        Section 4.2.6 provides case studies for EGR Dl
                                                                        Turbo and Atkinson engines.  The hybrid
                                                                        sections (especially section 6.8) are significantly
                                                                        expanded as well.
                                             4.1.1,4.2,
                                             4.2.6
Inputs and
Parameters
                                     24
                              Some examples of the types of inputs and parameters that would
                              be helpful to include the following in the report: Details of EGR
                              modeling parameters, such as maps showing percentage of EGR
                              being used at various loads.
                                                                        To address this concern, the final report uses
                                                                        public fueling maps concepts, and then illustrates
                                                                        the technical transformation of baseline
                                                                        technologies to the future. See especially revised
                                                                        Sections 4.1 and revised Section 4.2. New
                                                                        Section 4.2.6 provides case studies for EGR Dl
                                                                        Turbo and Atkinson engines.
                                             4.1.1,4.2,
                                             4.2.6
                                                                                 10

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                                                  Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Comment
Other Comments
             Engine Models
255
The report states that engines used in the model were developed
using two main methods (page 14).
1.  The first method assumed that "reported performance of
   current research engines" would closely resemble production
   engines of the 2020-2025 timeframe.
2.  The second method began with current production engines
   and then a "pathway of technology improvements over the
   new 10-15 years that would lead to an appropriate engine
   configuration for the 2020-2025 timeframe" was applied.
Both of these approaches are reasonable if:
1.  Appropriate references are provided,
2.  The reported performances for the research engines used are
   documented in the report,
3.  The technology improvements are documented in the report,
   and
4.  The methodology of incorporating the improvements is fully
   documented.
To address this concern, the final report uses
public fueling maps concepts, and then illustrates
the technical walk to the future. See revised
Section 4.1.1 and revised Section 4.2. New
Section 4.2.6 provides case studies for EGR Dl
Turbo and Atkinson engines. Additional
references have also been provided.
4.1.1,4.2,
and 4.2.6
Inputs and
Parameters
             Engine Models
308
The report outlines two methods were used to produce engine
models. The first method was used for boosted engines and
relied upon published data on advanced concept engines which
would represent production engines in the 2020-2025 timeframe.
The second method was used with Atkinson and diesel engines
and somehow extrapolated from current production engines to the
2020-2025 time frame.  The description of both of these methods
in the report is unsatisfactory. It also  fails to address how the
various technologies are used to build up to a single engine map
for a specific powertrain. Validation, to the extent possible with
future technologies, is also lacking in  this area.
To address this concern, the final report uses
public fueling maps concepts, and then illustrates
the technical walk to the future. See revised
Section 4.1.1 and revised Section 4.2. New
Section 4.2.6 provides case studies for EGR Dl
Turbo and Atkinson engines.
4.1.1,4.2,
and 4.2.6
                                                                                 11

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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                       Specific       Comment
Charge Question    Assump
Inputs and
Parameters
                   Section 4.1.1.1
                   CPS
65
How were the profiles selected? Was there an optimization
process for each engine size of a given engine type?
See the revisions to sections 4.1.1.1 and 4.1.1.2
generally.  Section 4.2.6 provides detail on the
fuel map development, and section 6.3
addresses the engine models specifically.  The
questions raised in this comment are not
appropriate to answer by adding text to section
4.1.1.1.
4.1.1.1
Inputs and
Parameters
                   Section 4.1.1.2
                   DVA
66
Was the actuation power requirement accounted for?  What were
the timing/lift profiles and what control strategy was used to select
the timing/lift profile? Was this an active model or was the
timing/lift profile preset and then unchangeable. I would expect
that as the engine size changes and the boost changes the
timing/lift profile will have to change with it.
See the revisions to sections 4.1.1.1 and 4.1.1.2
generally.  Section 4.2.6 provides detail on the
fuel map development, and section 6.3
addresses the engine models specifically.
Ricardo to add to report that losses are
accounted for in Figure 4.4.
4.1.1.2
Inputs and
Parameters
                   Direct Injection
                   Fuel Systems
322
Because of the availability of research and production data in this
area, it is expected that performance from this technology was
used to predict performance rather than any type of modeling
approach.  That being said, the report does not describe where or
how this data might have been used to develop the fuel
consumption map of the engines simulated nor what data sources
were used.
The approach to this is similar to the approach
taken to the similar comment made in Row 16.
See revisions to section 4.1.2 for this comment.
4.1.2
Inputs and
Parameters
                   Section 4.1.3
                   Boosting
                   Systems
67
What about superchargers?  Eaton's AMS supercharger systems
offer high efficiency supercharges that are comparable to turbo's
and don't have the lag problem.
The selection was based on Ricardo subject
matter expert judgment for this study.  The
series-sequential turbocharger was used for the
modeling of all boosted engines. Section 4.1.3
details the boosting system assumptions.
4.1.3
Completeness
                   Section 4.1.3
                   Boosting
                   Systems
132
It says that other boosting systems were included in the study, but
only turbocharging is discussed.
Other boosting systems were included in the
study but turbocharging was the only boosting
system chosen for modeling.
4.1.3
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                T
                       Specific       Comment
Charge Question     Assump
Inputs and
Parameters
                   Engine
                   technology
                   selection
172
The feasibility of the following assumptions for the engines
modeled should be re-examined as indicated below:
Turbocharger delays of the magnitude assumed in the model will
result in significant driveability issues for engines that are
downsized approximately 50%. Although  Ricardo assumed a
turbocharger delay of approximately 1.5 seconds, the comparable
delay published for a research engine was significantly longer at
2.5 seconds (Lumsden et al., 2009).
See revised section 4.1.3.
4.1.3
Other Comments
                   Boosting
                   Systems
272
The report states that "various boosting approaches are possible,
such as superchargers, turbochargers, and electric motor-driven
compressors and turbines." (page 13).  However, elsewhere the
report states "series-sequential turbochargers" will be used on the
Stoichiometric Dl Turbo engine (page 15).
The series-sequential turbocharger was used for
the modeling of all boosted engines. Section
4.1.3 details the boosting system assumptions.
4.1.3
Other Comments
                   Boosting
                   Systems
273
It is not clear in the report how the series-sequential turbocharger
was selected from the variety of boosting devices that were
introduced.  Models for the turbochargers with compressor and
turbine efficiency maps were not provided, so the appropriateness
of these model cannot be assessed.
The selection was based on Ricardo subject
matter expert judgment for this study. The
series-sequential turbocharger was used for the
modeling of all boosted engines. Section 4.1.3
details the boosting system assumptions.
4.1.3
Other Comments
                   Boosting
                   Systems
274
Comment: The model should include a single turbocharger
system with less extreme downsizing as advocated by the Sabre
Engine (Coltman et al., 2008; Turner et al., 2009) as a lower cost
alternative to series-sequential turbochargers.
The selection was based on Ricardo subject
matter expert judgment for this study. The
series-sequential turbocharger was used for the
modeling of all boosted engines. Section 4.1.3
details the boosting system assumptions. EPA
affirmed the recommendation of series-
sequential turbos.
4.1.3
Other Comments
                   Stoichiometric Dl
                   Turbo Engine
280
The foregoing table indicates several significant issues: 2. The
turbocharger response time for the Mahle engine is 2.5 seconds,
whereas Ricardo assumed a time constant of 1.5 seconds. Such
turbocharger delays are expected to result in significant
driveability issues for engines that are downsized approximately
50%. (see Exhibit 7)
See revised section 4.1.3.
4.1.3
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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                       Specific       Comment
Charge Question     Assump
Inputs and
Parameters
                   Boosting System
                   (4.1.3 and 6.3)
326
Boosting was applied to many of the different powertrain
packages simulated. Beyond stating what maximum BMEP that
was achievable, very little is mentioned in how the efficiency of
the boosted engines were determined.  Among other factors,
boosting often creates a need for spark retard which costs
efficiency if compression ratio is fixed. These complex issues are
tied to combustion which is inherently difficulty to model. This
aspect of the engine model is not well documented in the report.
The final report includes additional detail related
to boosting. See revisions in 4.1.3, 4.2, 4.2.1,
4.2.6, and 6.3.
4.1.3,4.2,
4.2.1,
4.2.6, 6.3
Other Comments
                   Stoichiometric Dl
                   Turbo Engine
283
Turner et al. (2009) indicates that the Sabre engine with a single
stage turbocharger provides an attractive alternative to extreme
downsizing with series-sequential turbochargers.
The selection was based on Ricardo subject
matter expert judgment for this study.  The
series-sequential turbocharger was used for the
modeling of all boosted engines. Section 4.1.3
details the boosting system assumptions.
4.1.3,4.2.1
Simulation
methodology
                   Turbocharger
                   systems (Section
                   4.1.3)
33
Specific suggestions regarding models that need more detailed
coverage: There is no discussion of turbocharger efficiencies and
their range. Did the simulations assume current boosting
technologies? Were maps used for this simulation or some other
representation? Was scaling used? What were the allowed boost
levels?
Turbocompressor system effects are built into
the torque curve fueling map, so that the
specifics of efficiency, boost P, etc. are not
relevant to model. The final report includes a
figure based on a relevant, published GM study,
and more detailed discussion on this issue.
4.1.3,
4.2.1,6.3
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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                       Specific       Comment
Charge Question     Assump
Other Comments
                   Boosting System
                   (4.1.3 and 6.3)
57
A two-stage system is indeed promising for advanced
turbocharging concepts. A distinction should be made between
series and sequential configurations. Airflow manipulation can
make it a series system (two-stage expansion and compression)
or a sequential system (turbos activated at different rpm). Variable
geometry or twin-scroll turbines can be good options for the low or
high pressure stages, respectively. A two-stage turbocharging
system like this would take advantage of the lean SI exhaust
enthalpy, reduce pumping work (or even aid pumping), avoid
mechanical work penalties, improve engine transient response,
enable high dilution levels (if desired) and probably help keep in-
cylinder compression ratio below 12:1, since significant
compression would be done  before the cylinder. EGR flow could
be driven through a low pressure loop (after the turbines) or an
intermediate pressure loop (between the turbines). The resulting
turbo lag will depend on the details of the configuration and the
control logic used. Note that  the assumption of a time constant of
1.5 seconds (as stated in the report) to represent the expected
delay may not hold true in all cases.
Sections 4.1.3, 4.2.6, 6.2, and 6.3 provide
additional discussion and graphics related to
turbo lag and the two-stage system concept and
how it was applied in this study.
4.1.3,
4.2.6, 6.2,
6.3
Inputs and
Parameters
                                     22
            Some examples of the types of inputs and parameters that would
            be helpful to include the following in the report: Baseline maps
            used to represent turbomachinery, in actual or normalized form.
                                                             See figures and text added to the final report,
                                                             including section 4.1.3 and 4.2.6.1.
                                              4.1.3,
                                              4.2.6.1
Recommendations
                   Boosting System
                   (4.1.3 and 6.3)
327
Describe the process of arriving at the boosted engine maps.
The final report includes additional detail related
to boosting. See revisions in 4.1.3, 4.2, 4.2.1,
4.2.6, and 6.3.
4.1.3,6.3
Recommendations
                   Boosting System
                   (4.1.3 and 6.3)
328
Describe how factors like knock are addressed in the creation of
these maps.
The engine knock strategy itself was assumed to
be similar to today's methods. The fueling maps
reflect the effect of knock mitigation strategies.
4.1.3,6.3
Inputs and
Parameters
                   Turbo Lag
391
The data and methods used in modeling turbo lag are appropriate
and there is sufficient explanation and data to support the model.
EPA and Ricardo appreciate the comment; no
further response is required.
4.1.3,6.3
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                                                  Table 1: Response to Individual Peer Review Comments
                T
                       Specific       Comment
Charge Question     Assump
Inputs and
Parameters
                                     403
            Engine Model: The trend in engine technology is forced induction
            (engine downsizing). I think the selection of turbo only is too
            limiting. I anticipate variable speed supercharging and other
            combination of forced induction. I think the study would do well to
            include this.
                                                            The selection was based on Ricardo subject
                                                            matter expert judgment for this study. The
                                                            series-sequential turbocharger was used for the
                                                            modeling of all boosted engines. Section 4.1.3
                                                            details the boosting system assumptions.
                                             4.1.3,6.3
Inputs and
Parameters
                                     406
            Diesel Technology: Curious about the author's comment
            regarding supercharging, "advances to avoid variable speed".
            Why not variable speed?
                                                            See response to Comment Excerpt 403.
                                             4.1.3,6.3
Inputs and
Parameters
                   Section 4.1.4
                   Other Engine
                   Technologies
68
regarding global engine friction reduction, whatvalue(s) was
assigned to that? Was it the same across all engines? If so, why?
Friction reduction improvements were assumed
to be 3.5% across all engine maps, and were
extrapolated from the benefits assumed in the
2008 EPA study for 2012-2016. (see section
4.2.6.1)
4.1.4
Inputs and
Parameters
                                     69
            How was the FEAD electrification energy balance accomplished?
            Was additional load placed on the alternator?
                                                            The load of the electrical cooling fan is included
                                                            in the base electrical loads.  Mechanical fans are
                                                            included in the engine map.
                                             4.1.4,6.3.2
Inputs and
Parameters
                   Section 4.2
                   Engine
                   Configurations
71
Quantification needed ..."The combinations of technologies
encompassed in each advanced engine concept provide benefits
to the fueling map...."
Use of proprietary data was a ground rule of the
study. However, in the final report, we have
added a great deal of detail using publically
available references and sources to provide
further understanding of these issues and how
the study addressed them.
4.2
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                                                   Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Comment
Simulation
methodology
             Engines and
             Engine Models
             (Sections 4.1 and
             6.3)
30
Specific suggestions regarding models that need more detailed
coverage:
It is not clear whether the engine maps in the simulation tool were
generated based on simulations or existing experimental data,
somehow fitted and scaled to the various configurations. In
general, the explanation on how maps were obtained is vague for
such an important component. In one section, the report states
that the fueling maps and other engine model parameters used in
the study were based on published data. If so, it would be nice to
have a list of the published materials that have been used as the
resource. In Section 4.2, the report states that the performance of
the engines in 2020-25 were developed by taking the current
research engines and assuming the performance of the 2020
production engines will  match that of the research engine under
consideration. Does this assumption take into account the
emission standards in 2020, and do the current research engines
match those emission standards? What is the systematic
methodology that has been adopted to scale the performance and
fuel economy of current baseline engines to engine models for
2020-25? Also, the report lacks detail concerning the
methodology of extrapolating from available maps to maps
reflecting the effects on overall engine performance of the
combination of the future technologies considered.
The final report adds text on criteria pollutant
standards to confirm that the study assumed
LEVIII=SULEV II. The diesel engines fueling
maps account for these standards. The final
report includes more description on the
methodology, and explains how the referenced
publications inform the model. See revised
sections 4.2, 4.2.5 and 4.2.6.
4.2, 4.2.5,
4.2.6
Other Comments
             Engine Models
254
Engine models provided the torque curve, fueling map and other
input parameters (which were not specified in the report) (page
25).  Since the report stated that "The fueling maps and other
engine model parameters used in the study were based on
published data and Ricardo proprietary data" (page 26), their
adequacy and suitability could not be assessed.
Use of proprietary data was a ground rule of the
study. However, in the final report, we have
added a great deal of detail using publically
available references and sources to provide
further understanding of these issues and how
the study addressed them.
4.2, 6.3
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                                                   Table 1:  Response to Individual Peer Review Comments
                T
                       Specific
      e Question     Assump
                  Comment
Other Comments
                   Engine Models
                  260
            In summary, the Ricardo report provided insufficient descriptions
            of the derivation of the maps used for all of the engines in this
            study, which included:
            -   Baseline
            -   Stoichiometric Dl Turbo
            -   Lean-Stoichiometric Switching
            -   EGR Dl Turbo
            -   Atkinson Cycle
            -   Advanced Diesel
                                                            Use of proprietary data was a ground rule of the
                                                            study. However, in the final report, we have
                                                            added a great deal of detail using publically
                                                            available references and sources to provide
                                                            further understanding of these issues and how
                                                            the study addressed them.
4.2, 6.3
Recommendations
                   Engine Models
                  310
            Provide fuel and efficiency map data for all engines used in
            simulation.
                                                            Use of proprietary data was a ground rule of the
                                                            study. However, in the final report, we have
                                                            added a great deal of detail using publically
                                                            available references and sources to provide
                                                            further understanding of the modeling and
                                                            related issues, and  how the study addressed
                                                            them.
4.2, 6.3
Recommendations
                   Engine Models
                  312
            Provide specific references of which published data was used to
            predict performance of the future engines. Some references are
            given, however, it is not clear how exactly these references are
            used.
                                                            Multiple public references were provided. These
                                                            were used by the study group to balance and
                                                            verify the final engine maps based on Ricardo
                                                            research engine data.
4.2, 6.3
Recommendations
                   Engine Models
                  313
            Wherever possible, provide validation against data on similar
            technologies.
                                                            Please refer to the revised report concerning
                                                            technology/model validation.
4.2, 6.3
Recommendations
                   Engine Models
                  314
            Describe in detail the approach used to "stack up" technologies
            for a given powertrain recipe.
                                                            This is inherent to Ricardo's proprietary vehicle
                                                            models.
4.2, 6.3
Recommendations
                   Engine
                   technology
                   selection
                  343
            Describe in greater detail the approach used to model technology
            stack-up on the advanced vehicles.
                                                            This is inherent to Ricardo's proprietary vehicle
                                                            models.
                                                                                                             Engineering judgment was used by Ricardo,
                                                                                                             EPA, and the advisory committee to select
                                                                                                             engines suitable for the various vehicle classes.
4.2, 6.3
Recommendations
Engine
technology
selection
344
Provide some form of validation that this approach is justified.
4.2, 6.3
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                                                  Table 1:  Response to Individual Peer Review Comments
                T
                       Specific       Comment
Charge Question     Assump
Simulation
methodology
                   Section 4.2.1
                   Stoich Dl Turbo
83
Quantify how did the cooled exhaust manifold/lower turbine inlet
temp improved the BSFC map. This is a good example of
technology interaction...how did the radiator size grow to
accommodate the additional heat rejection; how did the frontal
area of the vehicle change to accommodate the larger radiator?
See Figure 4.6 for zone of engine operation
where enrichment for in-cylinder cooling was
removed. The effect on fuel economy results is
modest, since the Stoichiometric Dl Turbo
engine only has a few operating points in this
range over the US06 cycle. It was assumed that
specific heat rejection issues from the application
of advanced technologies would be addressed
without affecting fuel economy within the design
space considered, for example, within the range
of vehicle mass and frontal area and
aerodynamic drag.
4.2.1
Inputs and
Parameters
                   Engine
                   technology
                   selection
171
The feasibility of the following assumptions for the engines
modeled should be re-examined as indicated below: None of the
Stoichiometric Dl Turbo engines listed as references by Ricardo
limited the turbine inlet temperature to a value as low as the 950C
limit in the Ricardo model (Coltman et al., 2008; Turner et al.,
2009; Lumsden et al., 2009). Reducing the turbine inlet
temperature to reach this limit is expected to result in BMEP
levels below the assumed 25-30 bar level in the model (which
were obtained in the referenced engine with a turbine inlet
temperature of 1025C).
See revisions in section 4.2.1 of the final report,
including addition of Schmuck-Soldan et al.
(2011) reference. Water-cooled exhaust
manifolds were a technology considered in the
establishing of the 950C limit.  Ricardo's SME's
made adjustments to the map in GT/Power to
account for the 950C constraint that EPA asked
them to incorporate.
4.2.1
Other Comments
                   Stoichiometric Dl
                   Turbo Engine
275
The table below compares several attributes of the Ricardo
Stoichiometric Dl Turbo Engine with the Mahle Turbocharged, Dl
Concept Engine. (See Exhibit 7)
EPA and Ricardo acknowledge and appreciate
the reviewer's comments.
4.2.1
Other Comments
                   Stoichiometric Dl
                   Turbo Engine
276
Key content of the Mahle Turbocharged, Dl Concept Engine:
-   Two turbochargers in series
-   Charge air cooler
-   Dual variable valve timing
-   High energy ignition coils
-   Fabricated, sodium cooled valves
-   EGR cooler
EPA and Ricardo acknowledge and appreciate
the reviewer's comments.
4.2.1
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                T
                      Specific      Comment
Charge Question     Assump
Other Comments
                  Stoichiometric Dl
                  Turbo Engine
277
Lumsden et al. (2009) describing the Mahle concept engine stated
that lowest fuel consumption that usually occurs around 2000 rpm
had moved out to 4000 rpm for the series-sequential
turbocharged engine.
EPA and Ricardo acknowledge and appreciate
the reviewer's comments.
4.2.1
Other Comments
                  Stoichiometric Dl
                  Turbo Engine
279
The foregoing table indicates several significant issues: 1.  The
turbine inlet temperature of the Mahle engine is significantly
higher than the limit assumed for the Ricardo engine (1025C vs.
950C).  Reducing the turbine inlet temperature is expected to
result in lower BMEP levels where the temperature is limited, (see
Exhibit 7)
It is not possible for an apples-to-apples
comparison of today's Mahle engine vs. the 2020
advanced engines. Too many factors, such as
turbocharger efficiency can change BMEP levels
for a given turbine inlet temperature.
4.2.1
Other Comments
                  Stoichiometric Dl
                  Turbo Engine
281
The table below compares several attributes of the Ricardo
Stoichiometric Dl Turbo Engine with the Lotus Sabre Engine, (see
Exhibit 8)
EPA and Ricardo acknowledge and appreciate
the reviewer's comments.
4.2.1
Other Comments
                  Stoichiometric Dl
                  Turbo Engine
282
The paper on the Sabre engine (Turner et al., 2009) indicates that
operation at lower turbine inlet temperatures results in a reduction
in BMEP. However, the turbine inlet temperature for the Sabre
engine is still 40C above Ricardo's assumption.
See excerpt 279
4.2.1
Other Comments
                  Cooled Exhaust
                  Manifold
284
The Ricardo report states, "The future engine configuration was
assumed to use a cooled exhaust manifold to keep the turbine
inlet temperature below 950C..."  No explanation was provided of
how the limit on turbine inlet temperature would affect boost
pressure and power.
The limit on turbo inlet temperature was chosen
to avoid prohibitively expensive turbochargers
and is accounted for in the model.
4.2.1
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                                    Table 1:  Response to Individual Peer Review Comments
Charge Question

References Used
Recommendations
Recommendations
Recommendations
Recommendations
Other Comments
Specific
Assumption/

References
(Used for this
Review that are
also listed in the
Report)
BSFC Map
Comparisons
Direct Injection
Fuel Systems
Direct Injection
Fuel Systems
Direct Injection
Fuel Systems
Stoichiometric Dl
Turbo Engine
Comment

292
396
323
324
325
278


References used to establish the basis for the Stoichiometric Dl
Turbo engine assumptions (page 15 of the report):
1 . Coltman, et al. (2008), "Project Sabre: A Close-Spaced Direct
Injection 3-Cylinder Engine with Synergistic Technologies to
Achieve Low C02 Output", SAE Paper 2008-01-0138
2. Turner, et al. (2009), 'Sabre: A Cost-Effective Engine
Technology Combination for High Efficiency, High
Performance and Low C02 Emissions", IMechE conference
proceedings
3 Lumsden, et al. (2009), "Development of a Turbocharged
Direct Injection Downsizing Demonstrator Engine", SAE Paper
2009-01-1503
I reviewed this but do not have any substantive comments. All of
the figures compare pseudo-virtual engines with other pseudo-
virtual engines. A comparison back to a known, experimentally
validated engine current engine would have been more useful for
me as it would allow one to see the magnitude of improvements
that were assumed for the 2020 engines and where on the map
these improvements were made.
Cite sources of data used to predict Dl performance.
Describe how this data was used to develop the future engine
performance maps.
Provide validation of modeling techniques used.
Issue: The Ricardo report did not discuss the concern that the
lowest fuel consumption in a series-sequential turbocharged
engine had moved out to 4000 rpm, rather than the usual 2000
rpm and did not discuss how this concern was handled.


EPA and Ricardo acknowledge and appreciate
the reviewer's comments.
Please refer to Coltman et al. (2008) and Turner
et al. (2009) for publically disclosed engine
examples for comparison.
Predictions were based on Ricardo experience
with research and production engines much of
which is proprietary.
See response to Comment Excerpt 323.
See response to Comment Excerpt 323.
This is true of the referenced material but not in
the study. See significant revisions to section
4.2. land addition of 4.2.6.1.
^t^SiHjj

4.2.1
4.2.1
4.2.1,4.2.6
4.2.1,4.2.6
4.2.1,4.2.6
4.2.1,
4.2.6.1
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                T
                      Specific      Comment
Charge Question     Assump
Other Comments
                  Lean-
                  Stoichiometric
                  Switching
                  (Section 4.2.2)
58
The mixed-mode operation considered in the report seems to
switch between stoichiometric and lean SI direct injection
operation. There are several multi-mode combustion efforts under
development that encompass several more combustion modes,
including HCCI and Spark assisted compression ignition with
amounts of EGR dilution.
EPA and Ricardo appreciate the comment.
Future analyses could expand the scope to
include these technologies.
4.2.2
Simulation
methodology
                  Section 4.2.2
                  Lean Stoich
                  Switching
84
This type of tech points to one of the dangers of optimizing
configuration/technology/control strategy to the drive cycles; that
is that it has the potential to over constrain the design and effect
the "real world" performance/fuel economy.
EPA and Ricardo appreciate the comment; no
further response is required.
4.2.2
Other Comments
                  Lean-
                  Stoichiometric
                  Switching Engine
288
The report states that this engine will use a lean NOx trap or a
urea-based SCR system (page 15). The use of fuel as a reducing
agent was also suggested in the report (page 16).  However, the
fuel economy penalty associated with regenerating the NOx trap
or the reducing agent for the SCR system was not provided.
The fuel penalty varies with vehicle class and
other factors and is accounted for in the Ricardo
proprietary model.
4.2.2
                                                                               22

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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
             Aftertreatment/
             Emissions
             Solutions
315
Based on the report, it seems that emissions solutions are
assumed to be available for all powertrain technology packages
selected. The report discusses this in some qualitative detail in
section 4.2.2 with respect to lean-stoichiometric switching. This
discussion is somewhat incomplete, in that the way it is written it
assumes operating at stoichiometry lowers exhaust gas
temperature. In reality, switching from lean to stoichiometric
operation at constant load results in higher exhaust gas
temperatures.  Despite this factual inconsistency, it is indeed
generally better to operate a temperature sensitive catalyst hot
and stoichiometric or rich rather than hot and lean - so the
concept of lean-stoich switching is valid even if the explanation
provided is not.  Even without this factual inconsistency, some
additional discussion of aftertreatment systems would be of
benefit given that lean-burn gasoline engines are at present a
well-known technology for many years that is still problematic with
respect to emissions control. A separate issue is the topic of fuel
enrichment for exhaust temperature management which will have
an important impact on emissions and, if emissions are excessive,
reduce the peak torque available  from an engine.
The lean-stoich switching points were
determined to maintain exhaust temperatures
and catalyst operating limits. See revised
section 4.2.2.
4.2.2
Simulation
methodology
             Section 4.2.5
             Advanced Diesel
            Why were only the benefits of improved pumping losses or friction
            considered? What improvements were assigned to these
            benefits? Was it across the board or regional? What about
            advanced boosting technology for these engines?
                                                             Friction and pumping losses are the primary
                                                             targets to increase the efficiency of the engine.
                                                             Advanced boosting technology includes two-
                                                             stage turbocharging for the advanced turbo
                                                             engines.  In addition, combustion advancements
                                                             (such as  the lean boost engine) further lower fuel
                                                             consumption.
                                              4.2.5
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                                                  Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Comment
Simulation
methodology
                               87
            Ricardo's expectation for pace and direction: I thought there was
            an advisory committee making these decisions.  I'm surprised that
            they think boost will be limited to 17-23bar.
                                                            The Advisory Committee and EPA provided input
                                                            on many elements of the study, working with
                                                            Ricardo's expertise and experience. The final
                                                            study retains this language as a reasonable
                                                            expectation for advanced diesel technologies in
                                                            the study timeframe.  The final boost limit was
                                                            raised to 27 bar.
                                             4.2.5
Other Comments
             Engine Models
257
The description of the derivation of the engine models in the
report was, at best, vague, as illustrated by the two examples
below: Example 2: Advanced Diesel
For the advanced diesel, the report provided the following
description: "...the LHDT engine torque curve and fueling maps
were generated by starting with a 6.6L diesel engine typical for
this class and applying the benefits of improvements in pumping
losses or friction to the fueling map".  No description of the
improvements in pumping losses or friction reduction was
provided and the variation of these improvements over the speed
and load map were not provided.  In addition, the baseline 6.6L
engine map was not provided, the 6.6L friction map was not
provided and the methodology for applying the improvements to
the 6.6L engine map was not provided.
As described in Section 4.2, the Diesel engines
and Atkinson engines used the same
methodology to translate current production
fueling maps to the 2020-2025 timeframe. This
methodology is described in detail in Section
4.2.6.2, with the example of an Atkinson engine
since a published map can be presented as a
starting point. The Diesel engine maps were
based on Ricardo Confidential Business
Information.
4.2.5
Inputs and
Parameters
             Input Data
             Review
397
The documentation on the Diesel engine maps was helpful;
however, it did not discuss how the 2020 engine maps were
developed.  This is critical for having confidence in the predictions
made for the Diesel powertrains in 2020.
See Section 4.2.5.
4.2.5
Inputs and
Parameters
                               405
            Diesel Engine Fuel Maps: The presentation shows the
            technologies to be deployed, but doesn't discuss how the 2020
            bsfc maps were arrived at. It might be helpful to also use the
            same method for comparison that the authors used to show LBDI
            vs EGR.
                                                            See Section 4.2.5.
                                             4.2.5
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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                       Specific       Comment
Charge Question     Assump
Simulation
methodology
                   Section 4.2.4
                   Atkinson Cycle
85
How do the 2020-2025 maps differ from the 2010 maps?
                                                                                                                              Response
See new section 4.2.6.
4.2.6
Inputs and
Parameters
                                     408
            EBDI Engine: Couldn't find fuel economy benefit discussion in
            presentation. Should be done as gasoline or energy equivalent. I
            know C02 is proportional, but....
                                                             EBDI results shown are for "EO" fuel.
                                              4.2.6.1
Simulation
methodology
                   6.3 Engine
                   Models
92
Two methods to develop engine models were discussed. It is not
disclosed which approach was used for which engine. |
recommend that one approach be developed for all engines or
both approaches be applied to each engine to converge to a
solution.
EPA and the program team did not opt for this
approach in designing this study.  The final
report provides further detail on the different
approaches (see 6.3 plus a number of revisions
in section 4.2, especially 4.2.6.a and 4.2.6.2).
The option used was recommended by Ricardo
and intended to be an appropriate approach
given the current data available (in some cases a
research engine was used because it provided
an appropriate starting point, while in other cases
a current production engine was determined to
be the most appropriate starting point).
4.2.6.1,
4.2.6.2, 6.3
References Used
                   References
                   (Used for this
                   Review that are
                   also listed in the
                   Report)
294
References containing supporting information for the hybrid
powertrains:
5.  Hellenbroich, et al. (2009), "FEV's New Parallel Hybrid
   Transmission with Single Dry Clutch and Electric Torque
   Support"
6.  Staunton, et al. (2006), "Evaluation of 2004 Toyota Prius
   Hybrid Electric Drive System", ORNL technical report TM-
   2006/423
EPA and Ricardo acknowledge and appreciate
the reviewer's comments.
4.3
Completeness
                   Section 4.3.1
                   Micro Hybrids
134
It is implied that electrified accessories aren't used in this
configuration. I don't see that as the case.
This case includes electrified accessories, but
assumes no electrified cooling. See Weissier
article cited in revised report on recent
expectations for addressing cooling needs.
4.3.1
                                                                                 25

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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                       Specific       Comment
Charge Question     Assump
Inputs and
Parameters
                   Accessory load
                   assumptions
185
The accessory selections listed in Table 5-2 (page 22) appear to
be adequate except for the following issue: Belt driven air
conditioning for the stop-start powertrain configuration is not
acceptable for driver comfort. Electrically driven air conditioning is
required for the stop-start powertrain configuration to provide
driver comfort for extended idle periods.
The study runs assumed belt-driven for this
situation. Also see Weissier article cited in
revised report on recent expectations for
addressing cooling needs. EPA and Ricardo will
consider this issue for future analysis.
4.3.1
Inputs and
Parameters
                   Accessory load
                   assumptions
189
Recommendation: Both mechanically driven and electrically
driven accessory power requirements should be clearly provided
in the report.
See accessory power requirements table.
4.3.1,6.3.2
Other Comments
                   P2 Parallel
                   Hybrid (Section
                   4.3.2)
59
P2 refers to pre-transmission parallel hybrid, where an electric
machine is placed in between the engine and the transmission.
While the report does not discuss details, there are two possible
configurations: (i) a single clutch, located in between the engine
and the electric machine, such as in the Hyundai Sonata, and (ii)
two clutches, one in between the engine and the motor, and the
other one in between the motor and the transmission, such as in
the Infiniti M35 HEV. The P2 system looks promising to achieve
good efficiency, but remaining barriers include cost, drive quality,
durability and to a lesser extend packaging. Careful consideration
of details is needed to properly assess benefits compared to a
single mode power split. Early reports have indicated that Nissan
got 38% mpg increase out of their P2 and Hyundai got 42%, both
with higher horsepower, as well. However, the P2 Touareg
doesn't seem to meet EPA 2012 CAFE standards.
EPA and Ricardo appreciate the comment; no
further response is required.
4.3.2
Completeness
                   Section 4.3.2 P2
                   Hybrid
135
No discussion of why DCT was only transmission used for P2
hybrids instead of CVT and AMT.
DCTs were chosen as current industry direction
and to simplify the study scope while modeling a
representative technology.
4.3.2
Other Comments
                   Transmission
                   Technologies
                   (Section 4.4)
60
What about automatic transmissions with automated clutch
replacing the torque convertor and lock-up clutch? This is also a
possibility.
This technology was not part of the study.  EPA
and Ricardo appreciate the comment; no further
response is required.
4.4
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                                                  Table 1:  Response to Individual Peer Review Comments
                T
                       Specific       Comment
Charge Question     Assump
Completeness
                   4.4 Transmission
                   Technologies
136
What types of CVT's were in the original mix? Toroidals, push-
belts, Miller?
CVTs were not part of this study.  See edits to
section 4.4.
4.4
Inputs and
Parameters
                   Transmission
                   technology
                   selection
173
The transmission technologies selected for this study, listed in
Table 5.3 (page 23) are appropriate.
EPA and Ricardo appreciate the comment; no
further response is required.
4.4, 5.2
Inputs and
Parameters
                   6.4 Transmission
                   Models
76
no efficiency maps, no description of the efficiency maps. What
was efficiency a function of?  Typically it's gear ratio, torque and
speed.
Efficiency assumptions added to report. See
revised section 4.4 and 6.4.
4.4, 6.4
Simulation
methodology
                   4.4 Transmission
                   Technologies
            How were the gear ratios selected? What about shift logic?
                                                            Gear ratios added to report and shift logic
                                                            detailed in section 6.4 of the final report.
                                             4.4, 6.4
Inputs and
Parameters
                   Transmission
                   technology
                   selection
175
The report mentions that the transmissions include dry sump,
improved component efficiency, improved kinematic design, super
finish, and advanced driveline lubricants (page 22).
See revisions to section 4.4 and 6.4 in the final
report.
4.4, 6.4
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                                                 Table 1: Response to Individual Peer Review Comments
                T
                 Specific
e Question    Assump
Comment
Other Comments
             Transmission
             Models
261
Similar to engine models, the description of the derivation of
transmission models was also vague. Using the automatic
transmission model as an example, "For the 2020-2025
timeframe, losses in automatic transmissions are expected to be
about 20-33% lower than in current automatic transmissions from
the specific technologies described below." The specific
technologies that could provide these reductions appeared to
include:
-   Shift clutch technology - to improve thermal capacity of the
   shifting clutch to reduce plate count and lower clutch losses
   during shifting.
-   Improved kinematic design - no description of these
   improvements was provided.
-   Dry sump - to reduce windage and churning losses.
-   Efficient components - improvements in seals, bearings and
   clutches to reduce drag.
-   Super finishing - improvements expected were not specified.
-   Lubrication- new developments in base oils and additive
   packages, but improvements were not specified.
In-house efficiency calculations provided the
overall average transmission efficiencies based
on benchmarking data, with small adjustments
based on the expected improvements of
advanced technologies.
4.4, 6.4
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                                                  Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Comment
Other Comments
             Transmission
             Models
262
In addition to not specifying the improvements expected from
these technologies, no indication was provided of how these
technologies were applied to the transmission models. For
example,
-   The report stated that losses in automatic transmissions are
   expected to be about 20-33% lower than in current automatic
   transmissions (page 19).  However, the baseline losses were
   not provided for reference and the means to achieve these
   reductions were not described.
-   The report stated that energy losses in DCTs are expected to
   be 40-50% lower than in current automatic transmissions
   (page 19). The details of this reduction were not provided and
   references describing these reductions were not provided.
-   Bearing and seal  losses have a greater effect on efficiency at
   light loads than at heavy loads. The report did not describe
   how these losses were incorporated in the model. In contrast
   to the lack of descriptions of details in the report, PQA and
   Ricardo (2008), as an example, provided the following map of
   bearing losses in  a transmission as a function of shaft
   diameter and speed.  Similar details for the relevant aspects of
   the transmission models in this report would have been
   expected. (See Exhibit 4)
Efficiency assumptions added to report. See
revised section 4.4 and 6.4.
4.4, 6.4
Other Comments
             Transmission
             Models
263
In summary, the Ricardo report provided insufficient descriptions
of the derivation of the maps for the following transmissions:
-   Advanced automatic
-   Dry clutch DCT
-   Wet clutch DCT
-   P2 Parallel hybrid transmission
-   PS  Power Split hybrid transmission
The transmission model only captures efficiency
and torque/speed for each gear. Transmission
efficiency for each gear was derived from actual
component test data and normalized to represent
a "typical" transmission.
4.4, 6.4
Other Comments
             Transmission
             Models
264
In addition, the models for the automatic transmissions of the
baseline vehicles were not provided, so that their adequacy could
not be assessed.
The transmission model only captures efficiency
and torque/speed for each gear.
4.4, 6.4
                                                                                 29

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November 29, 2011
                                    Table 1:  Response to Individual Peer Review Comments
Charge Question

Inputs and
Parameters
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Specific
Assumption/

Transmissions
Transmissions
Transmissions
Transmissions
Transmissions
Transmissions
Transmissions
Transmissions
Transmissions
Comment

360
361
362
363
364
365
366
367
368


This peer reviewer is not as well-practiced in transmissions as in
other areas in this review. Because of this, a more limited review
was conducted of this aspect of the report. As with the other
areas of the report, the general concern in this area is the
inadequacy of documentation of the modeling approach and
validation.
Cite data sources used in modeling.
Validate models wherever possible.
Fully describe transmission models/maps and processes used to
generate them.
Fully describe clutch/torque converter models/maps and
processes used to generate them.
Fully describe the process used to generate shift maps and the
operation of the shift controller.
Fully describe the lockup controller (i.e. how soon can it enter
lockup after shifting?).
Fully describe the process for modeling torque holes during
shifting.
Fully describe the model used for the final drive (i.e.
inputs/structure/outputs).


See revisions to section 4.4 and 6.4 in the final
report.
See revised Sections 4.4, 6.4 (gearbox), and 6.5
(lock-up). Includes Figure 4.9.
See revised Sections 4.4, 6.4 (gearbox), and 6.5
(lock-up). Includes Figure 4.9.
See revised Sections 4.4, 6.4 (gearbox), and 6.5
(lock-up). Includes Figure 4.9.
See revised Sections 4.4, 6.4 (gearbox), and 6.5
(lock-up). Includes Figure 4.9.
See revised Sections 4.4, 6.4 (gearbox), and 6.5
(lock-up). Includes Figure 4.9.
See revised Sections 4.4, 6.4 (gearbox), and 6.5
(lock-up). Includes Figure 4.9.
See revised Sections 4.4, 6.4 (gearbox), and 6.5
(lock-up). Includes Figure 4.9.
See revised Sections 4.4, 6.4 (gearbox), and 6.5
(lock-up). Includes Figure 4.9.
^KSfcMTMil

4.4, 6.4
4.4, 6.4,
6.5
4.4, 6.4,
6.5
4.4, 6.4,
6.5
4.4, 6.4,
6.5
4.4, 6.4,
6.5
4.4, 6.4,
6.5
4.4, 6.4,
6.5
4.4, 6.4,
6.5
                                                           30

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                                                  Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Comment
Completeness
             4.4.1 Automatic
             Transmission
138
No logical explanation for the 20-33% improvement...how was
this number arrived at?
Reference is made to loss reductions (88%
efficient trans has 12% loss). Efficiency goes
from approximately 88% to 90.5-92% (varies by
gear). Improvements considered by committee
and trans experts included reducing number
clutch plates, reducing rotating speed differences
between components, dry sump, improved
lockup clutch dampers, superfinishing, lubricants,
seals and bearings.  The processes to achieve
these  improvements were discussed by the
technology committee and are proprietary. Also,
an improved efficiency torque converter was
assumed by EPA based on their discussions with
suppliers.  The ZF 8HP trans that is scheduled
for the 2012 Chrysler already has some of these
design features.
4.4.1-4.4.2
Completeness
             4.4.3 Wet clutch
139
It said these were expected to be heavier, cost more and be less
efficient than DCT's so why where they included?
Technology selected during selection phase of
the study by EPA with input from others.  See full
text in 4.4.3 which discusses evolution toward
damp clutch systems.
4.4.3
Results
             Section 4.4.6
             Shifting Clutch
             Technology
101
"The technology will be best suited to smaller vehicle segments
because of reduced drivability expectations" - not in the US
market.
Disagree.  Reduced drivability expectations
versus shift efficiency (and improved fuel
economy) will tend to exist mainly in the small
vehicle segment, for the US bias toward
drivability that the reviewer suggests.  Luxury
small cars  are not considered to be
representative of the class average.
4.4.6
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                                                  Table 1:  Response to Individual Peer Review Comments
                T
                       Specific
Charge Question     Assump
     Topic
Results
Comment
                   Section 4.4.7
                   Improved
                   Kinematic Design
102
Assumes a sweeping improvement without identifying a clear
rationale...doesn't appear to describe a scientific or objective
approach.
Section 4.4.7 could repeat the statement about
reducing the number clutch plates and reducing
rotating speed differences between rotating
components is part of improved kinematic
design. This is similar to the improvement ZF
has attained in the 8HP trans for the 2012
Chrysler 300.
4.4.7
Other Comments
                   Efficient
                   Components
                   (Section 4.4.9)
61
Efficient components should also include gears since rotating
gears are also a major source of drag. Designing a better profile
for gear teeth can reduce drag losses.
Gears are included in 4.4.10 Super Finishing but
could also be added to the component list in
4.4.9.
4.4.10
Completeness
                   4.4.10 Super
                   Finishing
140
How much improvement is attributed to super finishing?
This is not attributed to separately, but as part of
the suite of improvements in 4.4.6-4.4.11. See
revised discussion in section 6.4.
4.4.10,6.4
Results
                   Section 4.4.11
                   Lubrication
103
Assumes a sweeping improvement without identifying a clear
rationale...doesn't appear to describe a scientific or objective
approach.
Technology options were presented to EPA and
Advisory Committee, and then selections made
based on EPA input.  This technology can apply
across vehicles classes as stated in report.
Improvements in transmission lubrication are
based on Ricardo Confidential Business
Information.
4.4.11
Simulation
methodology
                                     90
            There are several types of rolling resistance models, what type
            was used?
                                                            Standard rolling resistance models incorporated
                                                            into the MSC.EasyS libraries were used.
                                             4.5
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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                 Specific
e Question     Assump
Comment
Completeness
                                144
            There are several types of rolling resistance models, what type
            was used?
                                                            As stated in Section 4.5: "Several vehicle
                                                            technologies were also considered for the study
                                                            to the extent that they help support future ranges
                                                            of vehicle mass, aerodynamic drag, and rolling
                                                            resistance for each of the vehicle classes in the
                                                            study. The potential levels of improvement for
                                                            these "road load reduction" technologies were
                                                            not explicitly quantified; rather, they were
                                                            included as independent input variables within
                                                            the complex systems modeling approach."
                                              4.5
Recommendations
                                158
            Where lumped improvements are made, I recommend using
            historical results to publish technology improvement curves. For
            example, the parasitic losses (Cd, Crr) should be quantifiable.
            Vehicle mass reductions as well.
                                                            As stated in Section 4.5: "Several vehicle
                                                            technologies were also considered for the study
                                                            to the extent that they help support future ranges
                                                            of vehicle mass, aerodynamic drag, and rolling
                                                            resistance for each of the vehicle classes in the
                                                            study. The potential levels of improvement for
                                                            these "road load reduction" technologies were
                                                            not explicitly quantified; rather, they were
                                                            included as independent input variables within
                                                            the complex systems modeling approach."
                                              4.5
Simulation
methodology
                               415
            Accessories: I don't see any discussion on the treatment of
            accessories. I believe from my review of the previous material,
            that the authors assume that all accessories will be electric. I think
            that engine driven accessories will play a key role in 2020.
                                                             See revised section 4.5.
                                              4.5
Completeness
             4.5 Vehicle
             Technologies
141
No values for mass, rolling resistance or drag given.  No
discussion of the improvement possibilities. This would be a good
place to use historical trends for vehicle mass reduction, aero
improvements and parasitic loss improvement.
These were not a focal part of this study.  The
complex systems tool allows the user to evaluate
a range of changes (on a percentage basis) for
these various parameters. See new text in 4.5,
and information in Section 5.2.
4.5, 5.2
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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                       Specific       Comment
Charge Question     Assump
Simulation
methodology
                   Intelligent Cooling
                   Systems (Section
                   4.3.1)
34
Specific suggestions regarding models that need more detailed
coverage: The report describes intelligent cooling systems, but
does not provide any estimates of the anticipated reductions in
fuel consumption over the FTP cycle, though related papers have
been published in the open literature.
See revised section 4.5.1.
4.5.1
Simulation
methodology
                   Intelligent Cooling
                   Systems (Section
                   4.3.1)
35
Specific suggestions regarding models that need more detailed
coverage: Sizing of various cooling components plays a very
crucial role in fuel economy predictions. The report does not
provide any detail on how the optimum cooling flow required for a
given engine- transmission combination was determined. This
would significantly affect the oil, coolant and transmission oil
pump RPMs, which would in turn significantly change the
accessory loads.
See revised section 4.5.1.
4.5.1
Simulation
methodology
                   Intelligent Cooling
                   Systems (Section
                   4.3.1)
36
Specific suggestions regarding models that need more detailed
coverage: In addition, the report does not have any discussion on
how modified cooling components (radiator, condenser, etc.)
would be sized for more efficient powertrains. For instance, a
more efficient engine that would reject less heat would likely need
a smaller radiator and lesser airflow through the radiator;  hence,
the grill opening could be reduced to cut down on aero drag. A
high efficiency transmission will not reject a lot of heat to the
transmission oil; thus, a smaller transmission oil cooler could be
used.
See revised section 4.5.1.
4.5.1
Inputs and
Parameters
                                     23
            Some examples of the types of inputs and parameters that would
            be helpful to include the following in the report: The baseline
            vehicle cooling system and accessory schematic vs. cooling
            system and accessory load schematics of the future engines
            considered in the simulation.
                                                             After reviewing the overall comments, Ricardo
                                                             and EPA did not believe that adding significant
                                                             detail to the cooling and other accessory load
                                                             discussions in the final report would assist in the
                                                             overall presentation of the study findings.
                                              4.5.1,6.3.2
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                T
                 Specific
e Question     Assump
Comment
Simulation
methodology
             Constraints
41
Specific suggestions regarding models that need more detailed
coverage:  There is no discussion in the report that discusses the
constraints on the combinations that can be implemented in real
life. For example, would a multi-air system that is currently
designed for small size engines work for a full size car?
See revised section 5.
Results
             Issue with CSM
218
Issue: The technology "package definitions" (page 22 and 23)
precluded an examination of the individual effects of a variety of
technologies.
EPA and Ricardo acknowledge this limitation.
As with any study, there is a need to balance the
ability to evaluate each variable, with the ability
to contain the study to a manageable scope.
Results
             Other issues
220
 The Advanced Diesel does not appear to be modeled for the
Standard Car and Small MPV (page 46 and 47), yet no reason
was provided.
Many technology combinations decided to be
less popular were not modeled to constrain the
scope of the study to a reasonable size while
maintaining sufficient fidelity. EPA and the
advisory committee precluded diesels from
certain vehicle classes based on vehicle cost,
and in a desire to contain the project scope.
Results
             Other issues
221
 The P2 and PS hybrid system was not modeled for the LHDT
(page 47), yet no reason was provided.
Hybrids requiring towing were not considered.
Many technology combinations decided to be
less popular were not modeled to constrain the
scope of the study to a reasonable size while
maintaining sufficient fidelity. LHDT (class 3)
vehicles are also not in the light duty category.
Recommendations
                               246
            Recommendation:  A default weight increase/decrease should be
            added for each technology.  If weight reductions are to be studied,
            then the user should have to input a specific design change, with
            the appropriate weight reduction built into the model, rather that
            having an arbitrary slider for weight.
                                                            The mass of technologies was not included in
                                                            this study due to the evolving nature and
                                                            complex opinions regarding this topic. The user
                                                            of the RSM tool is responsible to add or remove
                                                            mass from the baseline vehicle to account for the
                                                            mass of technologies.
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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
                                           The vehicle classes and baseline exemplars are reasonably
                                           chosen, within the constraint that vehicle size, footprint, and
                                           interior volume for each class be locked to the 2010 base year. It
                                           is likely that new vehicle classes will emerge by 2025 and/or that
                                           these "locking" restraints will be relaxed.
                                                                        EPA and Ricardo appreciate the comment.
                                                                        Future analyses could consider modifications to
                                                                        the locking constraints noted by the reviewer.
                                                                                                           5.2
Inputs and
Parameters
                                26
            The engine technology selection appears somewhat limited in
            terms of the selected combinations. For example, why is the
            Atkinson engine not boosted as well? Moreover, a variable valve
            actuation technology, as common and important as variable cam
            phasing, is not included. As already stated in the introductory
            comments, advanced combustion technologies, such as HCCI,
            are worth considering. More flexibility in the engine and vehicle
            parameters would also allow better understanding of the
            improvements obtained for individual technologies and possibly
            even show some potential synergies not currently identified.
                                                             The technology selections and combinations
                                                             were selected to provide a representative group
                                                             of combinations that reflect the thinking of the
                                                             program team of some of the most common
                                                             expected combinations across the range of light
                                                             duty classifications.  The full slate of options
                                                             considered is set forth in Attachment A to the
                                                             final report. While EPA agrees that additional
                                                             combinations are of interest, the project scope
                                                             was a significant undertaking, both in terms of
                                                             budget and time, with the options selected. The
                                                             report is one of the technical studies relevant to
                                                             EPA's ongoing rulemaking efforts, and the scope
                                                             was designed to support that effort.  EPA
                                                             anticipates that others and perhaps EPA will
                                                             continue to explore these issues with further
                                                             studies that add scope.
                                              5.2
Results
             5.2 Vehicle
             Configuration and
             technology
             combinations
105
Also there is no scientific or objective reason given for the DoE
ranges.  It appears that I can make any vehicle 60% less mass,
70% less rolling resistance etc....This will skew the results
towards that end of the DoE, when they may not be practically
achievable.
See edits in section 5.2: "Tables 5.4 and 5.5 also
show the ranges of the continuous parameters-
expressed as a percentage of the nominal
value—used in the DoE study for the
conventional and hybrid powertrains,
respectively. The ranges were kept purposely
broad, to cover the entire span of practical
powertrain design options, with some added
margin to allow a full analysis of parametric
trends."
5.2
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                T
                       Specific       Comment
Charge Question     Assump
Completeness
                   5.2 Vehicle
                   Configuration and
                   technology
                   combinations
142
While the tables show the vehicle configurations, more discussion
regarding the selection criteria for each vehicle is warranted. In
some cases this discussion was attempted in the technology
sections, but I  don't think it should go there.
EPA believes the significant additional text and
figures added to the final report sufficiently
describe the vehicle configurations that were
modeled as part of this study. This includes text
in section 5.2, as well as expanded discussions
throughout sections 4 and 6.
5.2
Inputs and
Parameters
                   Hybrid
                   technology
                   selection
177
The hybrid technologies selected for this study, listed in Table 5.2
(page 22) are appropriate.
EPA and Ricardo appreciate the comment; no
further response is required.
5.2
Inputs and
Parameters
                   DOE ranges
192
The following DOE ranges for Baseline and Conventional Stop-
Start (page 23) appear to be appropriate, with the exception of
Engine Displacement. Since the default for the Stoichiometric Dl
Turbo engine appears to be greater than 50% reduction in
displacement (Standard Car baseline of 2.4L is reduced to 1.04L
for the Stoichiometric Dl Turbo (page 46)), the opportunity should
be provided to start with a displacment near the baseline engine
(2.4L) and progressively decrease it to approximatly 50% (1.04L).
This would require an Engine Displacement upper range of over
200%. The model should also have the capabilty of increasing
the boost pressure as the displacement is reduced. (See Exhibit
1).
The reason for the 1.04L nominal displacement
for the Standard Car was to keep performance
metrics equal to today's model. The methodology
of the study kept boost levels (and BMEP)
constant with displacement change to allow for
apples to apples comparison of displacement
change. Furthermore,  the advanced turbo
engines are already running high BMEP levels.
5.2
Inputs and
Parameters
                   DOE ranges
193
The following DOE ranges for P2 and PS hybrid vehicles (page
24) appear to be appropriate (See Exhibit 2)
EPA and Ricardo appreciate the comment; no
further response is required.
5.2
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                T
                       Specific
Charge Question    Assump
     •'--•--              Topic
Comment
Inputs and
Parameters
                                                 The design of experiment (DoE) ranges, Tables 5.4, 5.5, 8.1, and
                                                 8.2, are reasonable and do not exclude likely sizings. The
                                                 assumed alternator baseline and advanced alternator efficiencies
                                                 are reasonable. The assumed reduction in automatic transmission
                                                 losses is reasonable, but not aggressive for 15 development
                                                 years from the baseline year. Similarly the state-of-charge swing
                                                 for hybrid modeling of 30-70% is reasonable, but does not reflect
                                                 improved battery technology for the 2020-25 period, which should
                                                 allow a greater swing for reduced battery size, weight, and cost.
                                                                        EPA and Ricardo appreciate the comment.
                                                                        Future analyses could consider modifications to
                                                                        assess more aggressive reductions in
                                                                        transmission losses and improvements in battery
                                                                        technology.
                                                                                                          5.2, 8.1
Simulation
methodology
                   Major
                   deficiencies in the
                   report
202
Descriptions of the algorithms used for engine control,
transmission control, hybrid system control, and accessory control
were not provided.
See revised section 6.
Simulation
methodology
                   Vehicle model
                   issues
209
Although the report described the major powertrain subsystems
included in the vehicle models (page 24), a description of the
vehicle model was not provided.
See revisions to section 6, including addition of
Figure6.1.
Recommendations
                   Specific
                   recommendations
                   for improvements
234
Provide an overall schematic and description of the powertrain
and vehicle models.
a.  Show all of the subsystem models/maps used in the overall
   model.
b.  Show the format of the information in each of the subsystem
   models (including input, subsystem model, output).
See revised section 6.
Inputs and
Parameters
                                     302
            The simulation methodology is generally not described in the
            report in sufficient detail to assess the validity and accuracy of the
            approach.  The models and approach are described qualitatively;
            however, this is insufficient to truly evaluate the ability of the
            modeling approach to perform the desired function.  The following
            subsections address specific issues with the models, inputs, and
            parameters and suggest possible corrective actions to address
            these issues.
                                                            See revised section 6.
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                                                  Table 1:  Response to Individual Peer Review Comments
                T
                      Specific       Comment
Charge Question     Assump
Recommendations
                  Vehicle model
                  issues
304
List the dynamic equation describing the longitudinal motion of the
vehicle.
Dynamic equations for longitudinal motion are
those incorporated within the MSC.Easy
libraries.
Inputs and
Parameters
                  Engine
                  technology
                  selection
342
There are a host of different technologies superimposed to create
the future powertrain technologies.  There is not a clear process
described on how this technology "stack-up" is achieved.  For
instance, an advanced engine technology may allow for greatly
improved BMEP.  Greatly improved BMEP often comes at the
expense of knock limits which are difficult to model even with
sophisticated modeling techniques. In this simulation, many
layers of powertrain technology are being compounded upon each
other which will not simply sum up to the best benefits of all of the
technologies - there are simply too many interactions. At the
level of modeling described, which are maps which are altered in
various unspecified ways; it is not clear how the technology stack-
up is captured.
This is the purpose of the empirically derived
model and BSFC maps - to avoid technology
"stackup".  These have been accounted for as
Ricardo has based maps on real engines with
much of this content already.  Knock issue is
redundant with other comments (see other
responses).
Recommendations
                  Vehicle model
                  issues
381
List the dynamic equation describing the longitudinal motion of the
vehicle
a.  NOT ADDRESSED IN SUPPLEMNTAL MATERIAL
   REVIEWED
See Excerpt 1.
Recommendations
                  Vehicle model
                  issues
382
List all parameters used for each vehicle class for simulation
a.  NOT ADDRESSED IN SUPPLEMNTAL MATERIAL
   REVIEWED
Please see expanded baseline attributes table in
appendix
Simulation
methodology
                                    91
           Was coast-down data from the baseline vehicles obtained or
           where the coefficients of rolling resistance and Cd modified to get
           the data to match?
                                                           See revised Sections 6.1 and 7.1.
                                             6.1
Results
                  6.1 Baseline
                  Conventional
                  Vehicle Model
106
Results were compared to the EPA Vehicle Certification
Database. These results often include correction factors and
allowances that aren't documented on the sticker.  Recommend
that actual testing be run to perform the benchmark.
The report accurately describes what was done
for this study. The Certification Database
information comes from actual tests performed
on the baseline vehicles using actual unadjusted
results.
6.1
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                T
                 Specific
e Question     Assump
Comment
Recommendations
                               154
            Should use coast down data for baseline vehicles to model
            parasitic losses.
                                                            See revised Sections 6.1 and 7.1.
                                              6.1
Simulation
methodology
              Major
             deficiencies in the
             report
199
An overall schematic and description of the powertrain and
vehicle models and the associated subsystem models/maps were
not provided.  Only vague descriptions were included in the text of
the report.
See revised report Section 6.1, including new
Figure 6.1.
6.1
Simulation
methodology
             Vehicle model
             issues
210
Issue: A description of how aerodynamic losses, tire rolling
losses and weight are handled in the model was not provided.
The starting point for the vehicle models was to
use the existing road-load coefficients from the
EPA Test Car List, which are represented as the
target terms for the chassis dynamometer.
Known as target A-B-C terms, the coefficients
were used to derive the physical properties of
rolling resistance, linear losses, and
aerodynamic drag. These properties were then
used in the simulation to provide the appropriate
load on the vehicle at any given speed. See
revised Sections 6.1 and 7.1.
6.1
Simulation
methodology
                               297
            The vehicle model is reported as "a complete, physics-based
            vehicle and powertrain system model" - which it is not.  The
            modeling approach used relies heavily on maps and empirically
            determined data which is decidedly not physics-based. This
            nomenclature issue aside, the model is not described in sufficient
            detail in the report to make an assessment in this area. An
            excellent example of this is the electric traction drives and HEV
            energy storage system for which the report mentions no details,
            even qualitative ones, on the structure  of the models.
                                                            See revised section 6.1.
                                              6.1
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                T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
             Vehicle model
             issues
303
The vehicle model is described as "a complete, physics-based
vehicle and powertrain system model" developed in the
MSC.EasySTM simulation environment.  This description is not
particularly helpful in defining the type of model as portions of the
model are clearly not physics based, such as the various
empirical maps used or sub-models like the warm-up model which
is by necessity an empirical model due to the complexity of the
warm-up process compared to the expected level of fidelity of the
model. It is assumed that a standard longitudinal model accounts
for rolling losses,  aero losses, and grade is used to model the
forces acting on the vehicle.  Input parameters for the vehicle
model are not described.  The baseline vehicle platforms are
listed, however, the relevant loss coefficients are not provided
(rolling resistance, drag coefficient, inertia.)
See revised Section 6.1. Baseline vehicle
parameters are tabulated in Appendix 3.
6.1
Inputs and
Parameters
             Baseline vehicle
             subsystem
             models/maps
163
Recommendation: Since the baseline vehicles modeled were
2010 production vehicles, the models/maps for the subsystems
used in these vehicle models should be included in the report
before it is released.
It is important to note that, following the model
validation phase, baseline vehicles were not
established just using the given EPA Test List
data or the raw validated vehicle fuel economy
results. Rather than using the raw validation
vehicles and corresponding fuel economy
results, a new set of baseline values were
determined to facilitate a uniform comparison
between the advanced (future) concepts and
today's current technologies.
6.1,6.2
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                T
                 Specific
e Question     Assump
                  Topic
Comment
Recommendations
                               240
            Recommendation:  Since the baseline vehicles modeled were
            2010 production vehicles, the models/maps for the subsystems
            used in these vehicle models should be included in the report
            before it is released.
                                                             It is important to note that, following the model
                                                             validation phase, baseline vehicles were not
                                                             established just using the given EPA Test List
                                                             data or the raw validated vehicle fuel economy
                                                             results. Rather than using  the raw validation
                                                             vehicles and corresponding fuel economy
                                                             results, a new set of baseline values were
                                                             determined to facilitate a uniform comparison
                                                             between the advanced (future) concepts and
                                                             today's current technologies.
                                              6.1,7.1
Results
                               44
            There is also no baseline hybrid configuration and no validation of
            the hybrid model. Due to the increased complexity of these
            vehicle systems, it is important to ensure the parameters and
            assumptions are valid.
                                                             No validation was performed for the hybrid
                                                             architectures as no P2 hybrid vehicles were in
                                                             production during the study. The Small Car with
                                                             P2 architecture was simulated at comparable
                                                             road loads to the Toyota Prius, and the fuel
                                                             economy figures were higher than the current
                                                             Prius. Section 6.2 presents the baseline hybrid
                                                             configurations. The revised Section 6.8 more
                                                             fully describes the hybrid approach used for this
                                                             study.
                                              6.2, 6.1
                                              7.1
Inputs and
Parameters
             Baseline vehicle
             subsystem
             models/maps
164
A major omission was that a baseline model of a hybrid vehicle,
which is significantly more complex than the baseline vehicle, was
not developed and compared to available EPA fuel economy test
data for production hybrid vehicles.
No P2 hybrids in production now, so nothing to
validate against. Any production vehicle would
be optimized for specific engine/electric
machine/battery.  Study assumption assumed
leave a generic, accurate controller that would
cover the design space. Also, a Hybrid baseline
was not part of the scope; therefore it can't be
compared to the 2011 Hyundai Sonata Hybrid.
See revised Section 7.1 for further discussion.
6.2,7.1
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                T
                       Specific       Comment
Charge Question     Assump
Inputs and
Parameters
                   Baseline vehicle
                   subsystem
                   models/maps
165
Recommendation: A baseline model of a hybrid vehicle should be
developed and compared to 2010 EPA fuel economy test data for
production hybrid vehicles.
No P2 hybrids in production now, so nothing to
validate against. Any production vehicle would
be optimized for specific engine/electric
machine/battery.  Study assumption assumed
leave a generic, accurate controller that would
cover the design space. Also, a Hybrid baseline
was not part of the scope; therefore it can't be
compared to the 2011 Hyundai Sonata Hybrid.
See revised Section 7.1 for further discussion.
6.2,7.1
Inputs and
Parameters
                   6.3 Accessories
73
I think the assumption that LOT cooling fans will be engine driven
is incorrect. The new F150's have electric fans.
This issue was not considered significant enough
to warrant considering re-running the model
runs.  If the commenter is correct in gauging the
likely normal configuration in the future, the result
would be some modest gain in fuel efficiency and
reduced C02 emissions.
6.3
Simulation
methodology
                                     93
            Regarding engine downsizing, I'm not sure that the scaling
            approach applies to boosted engines, especially engine with
            multiple compressors as well as DVT and CPS technology.
                                                            Scaling method, including heat loss effects are a
                                                            standard energy approach. All SI engines use SI
                                                            scaling curve. Methodology is applicable to Dl
                                                            Turbo engines based on Ricardo experience.
                                                            See revised Section 6.3.
                                             6.3
Simulation
methodology
                                     94
            Turbo lag applied as a first order transfer function with a time
            constant. How was the time constant selected? Was it validated?
            How was the improvement attributed to turbo compounding
            modeled?
                                                            Time constant selected based on professional
                                                            experience, and validated against data shown in
                                                            Figure 4.5. See revised Section 6.3 for further
                                                            discussion on how the various improvements
                                                            were modeled.
                                             6.3
Inputs and
Parameters
                   Engine
                   technology
                   selection
167
Setting the minimum per-cylinder volume at 0.225L and the
minimum number of cylinders at 3 is appropriate.  However,
achieving customer acceptable NVH with 3 cylinder engines
continues to be problematic.
3-cylinder engines have been in production for
many years, and Ford has plans for a boosted 3
cylin2013.
6.3
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                 T
                 Specific
e Question     Assump
Comment
Other Comments
             Engine Scaling
289
The report states, "The BSFC of the scaled engine map is
.. .adjusted by a factor that accounts for the change in heat loss
that comes with decreasing the cylinder volume, and thereby
increasing the surface to volume ratio for the cylinder" (page 26).
This is a directionally correct correction.  However, specific values
for the correction should be provided, together with references to
the data and methodology used to derive the values used.
The correction factors are derived from Ricardo
data from benchmarking and development
programs.
6.3
Other Comments
             Engine Scaling
290
Issue: The report states, "...downsizing the engine directly scales
the delivered torque,..." (page 26).  However, since there will be
increased heat loss from the smaller displacement cylinder, the
torque would be expected to be less than the directly scaled
values for the same fueling rate.
The fueling rate itself is modified with scaled
torque. It is never stated that the torque is the
same for a given fueling rate.
6.3
Inputs and
Parameters
             Engine Models
307
The engine models are "defined by their torque curve, fueling
map, and other input parameters." This implies that the maps are
static representations of fuel consumption versus torque, engine
speed, and other unknown input parameters. Generally speaking,
representing engine performance in this fashion is consistent with
typical practice for this class of modeling.  This comment deals
only with the representation of the engine performance in
simulation, the generation of the data contained within the map  is
much more challenging.
EPA and Ricardo acknowledge and appreciate
the reviewer's comments.
6.3
Inputs and
Parameters
             Engine
             Downsizing
329
Engine scaling is used extensively in the report.  Basic scaling
based on brake mean effective pressure is common in modeling
at this level of fidelity, thus, this does not need any special
description. However, the report mentions some means of
modeling the increased relative heat loss with small displacement
engines which is not a standard technique. The model or process
used to account for this effect should be explicitly described given
that engine size is one of the key parameters in the design space.
See revisions to section 6.3 and new Figure 6.2.
6.3
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                T
                       Specific       Comment
Charge Question     Assump
Recommendations
                   Engine
                   Downsizing
330
Properly document the process of scaling engines.
See revised section 6.3.
6.3
Recommendations
                   Engine
                   Downsizing
331
Validate the process used to scale engines.
Engines were scaled linearly, with regard to
displacement and torque. The brake specific fuel
consumption maps were modified based on a
heat loss effect curve. The curve represents data
and simulation results that indicate a benefit in
BSFC with increased individual cylinder size.
6.3
Simulation
methodology
                   Scaling
                   Methodology
                   Review
393
With one exception, the scaling methodology appears to be sound
given the information provided in the presentation. The curve
used to adjust BSFC with displacement ratio is not supported with
data or any citation of where it originated.  The motivation for this
correction seems valid, however, it needs to be supported with
data.
EPA and Ricardo acknowledge and appreciate
the reviewer's comments. See revisions in
section 6.3.
6.3
Inputs and
Parameters
                                     402
            Engine Model: I see data on the HEDGE engine technology but
            no mention of it in the list of engine technologies unless it's the
            high EGR Dl gasoline engine.
                                                            The HEDGE is an example of the EGR Dl
                                                            engine.
                                             6.3
Inputs and
Parameters
                   Engine
                   technology
                   selection
168
Issue: The description of the derivation of all of the engine
models/maps was insufficient.
Use of proprietary data was a ground rule of the
study. However, in the final report, we have
added a great deal of detail using publically
available references and sources to provide
further understanding of these issues and how
the study addressed them. Also, on specific
maps relevant to the engine model, we note that
the effects of the valve actuation system, fueling
system,  and boost system were integrated into
the final  torque curves and fueling maps,
therefore subsystem performance maps, such as
turbine and compressor efficiency maps, are not
relevant to this study.
6.3, 6.8
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                T
                 Specific
e Question     Assump
                  Topic
Comment
Inputs and
Parameters
                               25
            Some examples of the types of inputs and parameters that would
            be helpful to include the following in the report: Details of warm-up
            model parameters, such as ambient temperature; warm up friction
            correction; cold start fuel consumption correction factor;
            generation of heat rejection maps for various combinations in the
            simulation matrix.
                                                            After reviewing the overall comments, Ricardo
                                                            and EPA did not believe that adding significant
                                                            detail to the warm-up model discussions in the
                                                            final report would assist in the overall
                                                            presentation of the study findings.
                                              6.3.1
Simulation
methodology
             Warm-up
             methodology
             (Section 6.3.1)
37
Specific suggestions regarding models that need more detailed
coverage: This section talks about using engine warm-up profile
during the cold start portion to ascertain additional fueling
requirements. It talks about a correction factor to account for this
additional fuel. How was this factor determined? Has a different
correction factor been used for various engines? For instance, for
a lean-burn engine that reject less heat, the oil warm-up is slower
compared to a baseline engine. Was a new heat rejection map
generated to account for start-up enrichment while modeling the
warm-up? What is the ambient temperature that has been
considered while performing the FTP 75 fuel economy test? Have
the viscous effects of engine oil considered in the warm up
simulation? How have the friction  losses for various valvetrain
engine combinations been modeled?
See revised section 6.3.1 for warmup
assumptions.
6.3.1
Results
             Section 4.5.1
             Intelligent Cooling
             System
104
The system as described seems more appropriate for regulated
emissions reduction opportunity rather than fuel economy or
GHG. I think these systems enable engine control strategies that
aren't part of this study that would have a greater impact on fuel
economy than warming up the engine faster.
See revised section 6.3.1.
6.3.1
Other Comments
             Warm-Up
             Methodology
285
"Ricardo used company proprietary data to develop an engine
warm-up profile" which was used to increase the fueling
requirements during the cold start portion of the FTP75 drive cycle
(page 26). Since this data was proprietary, no assessment of its
appropriateness can be made.
See revised section 6.3.1
6.3.1
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                T
                 Specific
e Question     Assump
Other Comments
             Warm-Up
             Methodology
Comment
287
Issue: No explanation was provided to clarify when the "engine
warm-up profile" is used and when the "correction factor" is used.
Therefore, the appropriateness of the warm-up methodology
cannot be assessed.
See revised section 6.3.1.
6.3.1
Inputs and
Parameters
             Warm-Up
             Methodology
332
The report describes a 20% factor applied to bag 1 of the FTP-75
for baseline vehicles and a 10% factor applied to the advanced
vehicles.  The motivation for these factors is described
qualitatively and is valid, as many organizations are currently
investigating strategies to selectively heat powertrain components
to combat friction effects.  However, the values for these factors
that were selected are not backed up with any data or citation.  It
is suspicious that the two values cited are such round numbers -
the data from which these numbers are derived should be cited.
Because of the complexity of this phenomenon,  some type of
empirical  model is justified. The model described in the report is
not sufficiently validated to judge its suitability.
See revised section 6.3.1.
6.3.1
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                 T
                 Specific
e Question     Assump
Comment
Simulation
methodology
             Cold Start
             Correction
             Methodology
384
The correction used to adjust fuel economy for cold start is
described in this presentation. The method is based on two
pieces of information:
1.  A set of three tests from a single vehicle's instantaneous fuel
   multiplication correction factor
2.  A piece of EPA data which shows a fleet-wide average for
   2007 of the instantaneous fuel multiplication correction factor
The instantaneous fuel multiplication correction factor is not
described in the presentation, however, it is assumed to be the
sum  of the "short term fuel trim" and "long term fuel trim."  If this is
the case, then this value doesn't correlate to  increased fuel
consumption, but rather, to errors in the injector characterizations,
fuel property assumptions, and air estimation algorithm in the
engine controller. The engine controller is going to maintain
stoichiometry based on oxygen sensor measurements, these trim
values are the simply the feedback correction values required to
do this based on the feedforward algorithm in the ECU. By way of
example, I could alter the fuel tables of an ECU by 15% which
would cause the feedback  control system to correct by an
opposite 15%.  This would not change the fuel consumption of the
vehicle once the control system has corrected it, which would
happen  in seconds.
I don't disagree necessarily with the magnitude of the outcomes,
since they are based mostly on EPA bag fuel economy data. If I
am correct in my understanding of the correction factor then the
method  is not valid.
Section 6.3.1 details the warmup methodology
for the study.
6.3.1
Inputs and
Parameters
                               401
            Battery Model: Overall the battery model is sound; however, I
            don't understand why cold modeling is included.  The FTP testing
            doesn't include cold testing therefore only 25C and up should be
            included and the battery is consistent at those temps.
                                                             Cold testing was considered but not modeled in
                                                             this study.  See revised section 6.3.1.
                                              6.3.1
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                T
                 Specific
e Question     Assump
Comment
Simulation
methodology
             6.3.1 Warm-up
             Methodology
95
How was the engine warmup modeled? Is it a first order transfer
function with a time constant? It said proprietary data was used,
but how? Does the method allow for different warmup depending
on size and engine technology?
Engine warmup assumptions are detailed in
revised sections 6.3.1 and 6.7.
6.3.1,6.7
Results
             6.3.1 Engine
             Warmup
             Methodology
107
Were there hot and cold engine maps? No mention.
Engine warmup assumptions are detailed in
revised sections 6.3.1 and 6.7.
6.3.1,6.7
Results
             6.7 Driver Model
115
How was the soak modeled? Were there hot engine maps and
cold engine maps?
Engine warmup assumptions are detailed in
revised sections 6.3.1 and 6.7.
6.3.1,6.7
Simulation
methodology
             Accessories
             Models (Section
             6.3.2)
38
Specific suggestions regarding models that need more detailed
coverage: Alternator efficiency has been assumed to be constant
around 55% for baseline. In the current baseline vehicles the
alternator efficiencies do vary with the temperature and load.
The report accurately portrays how this issue
was handled in the study. EPA and Ricardo will
consider this issue for future analysis.
6.3.2
Simulation
methodology
             Accessories
             Models (Section
             6.3.2)
39
Specific suggestions regarding models that need more detailed
coverage: Has AC compressor load been considered in any of the
simulations? In some of the new cycles being proposed by EPA, it
is required that AC remains ON throughout the cycle. Hence,
management of the AC load is very critical.
The study is based on 2-cycle FTP vehicle
testing that does not include air conditioning to
match current rulemakings.
6.3.2
Inputs and
Parameters
                               74
            Limiting the alternator to 200A is very conservative, particularly if
            the system voltage stays at 14V.
                                                            The use of a 200A alternator follows current
                                                            production trends while streamlining the
                                                            modeling process.
                                              6.3.2
Simulation
methodology
             6.3.2 Accessories
96
Constant alternator efficiency and load is not a very good
assumption.  New alternator technologies and higher alternator
loads due to electrification and increased electrical demands. V\
the future still continue to use 14V or will higher voltages be
used?
See small edits to this section to describe the
assumptions used in the modeling, and the basis
for those assumptions.
6.3.2
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                T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
             Accessory load
             assumptions
186
Input values
Alternator efficiency was increased from the current level of 55%
to 70% to reflect "an improved efficiency design" (page 26 and
27).
The 55% to 70% alternator efficiency assumption
is a legacy of the 2007-2008 EPA study.  The
value for the baseline and advanced design was
discussed with Ricardo and was based on EPA's
confidential discussions with suppliers.
6.3.2
Inputs and
Parameters
             Accessory load
             assumptions
187
Comment: Justification for the increase in alternator efficiency
from 55% to 70% should be added to the report with references
provided. Alternator efficiency as a function of speed and load
may be more appropriate than a constant value.
Electrical accessory loads were assumed as
constant value throughout drive cycle. Alternator
efficiency map adds little value. Electrical loads
over drive cycle are relatively small and with
stop/start and "smart" management are relatively
constant. Assumptions were considered
reasonable by committee and are consistent with
best practice in industry.
6.3.2
Inputs and
Parameters
             Accessory load
             assumptions
188
Accessory power requirements were not provided, such as shown
in Figure 3-3 of PQA and Ricardo (2008), for example.
See accessory power requirements table.
6.3.2
Recommendations
                               245
            Recommendation:  Both mechanically driven and electrically
            driven accessory power requirements should be clearly provided
            in the report.
                                                            See Tables 6.3 and 6.4 in Section 6.3.2.
                                             6.3.2
Other Comments
             Accessory
             Models
269
None of the accessory models were not provided for review, so
their adequacy and suitability cannot be assessed.
See accessory power requirements table.
6.3.2
Other Comments
             Accessory
             Models
270
The accessory loads vs. engine speed for the conventional belt
driven accessories were apparently removed from the engine
when electric accessories were applied.  However, the
conventional accessory loads as well as the alternator
loads/battery loads for the electric accessories were not provided.
See accessory power requirements table.
6.3.2
Other Comments
             Accessory
             Models
271
In contrast, as an example, PQA and Ricardo (2008) provided the
following map of an electric water pump and AC compressor drive
efficiency.  Similar maps for all accessory models would be
expected in this report. (See Exhibit 6)
See accessory power requirements table.
6.3.2
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                 T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
             Accessory load
             assumptions
335
The accessory model is divided into electrical and mechanical
loads. The electrical sub-model assumes alternator efficiency's of
55% and 70% for the baseline and advanced vehicles
respectively. Given the required simplicity of the model, a simple
model like this is likely acceptable, however, there is no source
described for the alternator efficiencies. The base electrical load
of the vehicle is mentioned briefly, however, no numerical values
are given for each vehicle class or any type of model described.
The 55% to 70% alternator efficiency assumption
is a legacy of the 2007-2008 EPA study.  The
value for the baseline and advanced design was
discussed with Ricardo and was based on EPA's
confidential discussions with suppliers.
6.3.2
Inputs and
Parameters
             Accessory load
             assumptions
336
The electrical system also includes an advanced alternator control
which allows for increased alternator usage during decelerations
for kinetic energy recovery. The control description given is valid
but simplistic, but seems to fit the expected level of accuracy
required for the purpose. There is an issue regarding with the
approach for modeling the battery during this process. When
charging the battery at the stated level of 200 amps, the charging
efficiency of the battery will be relatively poor. During removal of
the energy later, there will once again be an efficiency penalty.
There is no description of a low-voltage battery model in the
report nor any explicit reference to such charge/discharge
efficiencies.  Additionally, an arbitrary limit of a 200 amp alternator
is defined for all vehicle classes - it is unlikely that a future small
car and a future light heavy duty truck will have an alternator with
the same rating.
The low voltage battery was based on a
conventional 12 volt automotive battery. The
efficiency of the battery itself was not specifically
modeled. Several OE's have adopted the smart
alternator energy recovery strategy. 200 Amp
alternators already exist today. If there is the
potential to recover all of the base electrical load
during normal operation, then a 200 Amp
alternator would be a small investment.
6.3.2
Inputs and
Parameters
             Accessory load
             assumptions
337
On the mechanical side, it is assumed that "required accessories"
(e.g. engine water pump, engine oil pump) are included in the
engine maps. The mechanical loading of a mechanical fan is
mentioned but no description of the model which, at a minimum,
should be adjusted based on engine speed and engine power.
The mechanical fan (only used on the trucks)
was indeed modeled based on engine speed.
See accessory power requirements table in
report.
6.3.2
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                 T
                 Specific
e Question     Assump
Comment
Recommendations
             Accessory load
             assumptions
338
Cite and/or validate the alternator efficiency values of 55% and
70%.
The 55% to 70% alternator efficiency assumption
is a legacy of the 2007-2008 EPA study. The
value for the baseline and advanced design was
discussed with Ricardo and was based on EPA's
confidential discussions with suppliers.
6.3.2
Recommendations
             Accessory load
             assumptions
339
Account for charge/discharge losses in the advanced alternator
control and/or describe the 12V battery model used for the
simulation.
See excerpt number 336.
6.3.2
Recommendations
             Accessory load
             assumptions
340
Describe, cite, and validate the accessory fan model used in the
simulation.
The load of the electrical cooling fan is included
in the base electrical loads. Mechanical fans are
included in the engine map.
6.3.2
Recommendations
             Accessory load
             assumptions
341
Justify the use of a 200 Amp advanced alternator across all of the
vehicle platforms.
The use of a 200A alternator follows current
production trends while streamlining the
modeling process.
6.3.2
Inputs and
Parameters
             Alternator Regen
             Shift Optimizer
385
The alternator regeneration strategy is not well documented. The
key system specifications, such as max alternator output and
efficiency, are listed as assumptions without a data source for
validation. The efficiency of the battery is not mentioned in this
nor other presentations that this reviewer has read - battery
efficiency for a lead acid battery at high currents is poor, this
would have an impact on the recovery of energy. Strategies like
this are disruptive to drivability and this issue is not discussed in
the presentation.
See excerpt number 336. In addition, drivability
impact is minimal, as BMW already employs this
technology on current production models.
6.3.2
Inputs and
Parameters
                                404
            Rgen Alternator: Ricardo states - 70% efficient alternator;
            however, alternator efficiency is a function of temp, speed and
            load. 70% is probably the best, but it's highly unlikely that it will
            operate there for the duration of the conditions.
                                                             As reader notes, 70% is today's best case
                                                             scenario. It is a safe assumption that by 2020,
                                                             70% efficient alternators will be the norm. CBI
                                                             from alternator manufacturers supports this.
                                              6.3.2
Simulation
methodology
                                413
            Regen Alternator: Alternator model is too simplistic. On average
            the efficiency is too high as identified and it's unrealistic to
            assume that the battery will be able to accept 100% of the charge.
                                                             See response to Comment Excerpt 336.
                                              6.3.2
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                 T
                 Specific
e Question     Assump
Comment
Simulation
methodology
             Transmission
             Models (Section
             6.4)
40
Specific suggestions regarding models that need more detailed
coverage: The transmission efficiencies vary by almost 10-15%
based on the transmission oil temperature. How have these
effects been modeled?
The warmup factor accounts for all engine,
transmission and final drive gearing losses
during bagl and was derived from actual EPA
test results.
6.4
Other Comments
             Transmission
             Models (Section
             6.4)
62
It is claimed that gear selection will be optimized for fuel economy
for a given driver input and road load. Can this also be adaptive?
Engine performance degrades with age. This strategy could also
lead to more gear shifts; the latter would increase hydraulic loads
and frictional power losses in the clutch, thus eroding some of the
possible fuel economy gains.
See revised text in section 6.4 detailing
comparison of optimized shifting to baseline
production vehicles. Adaptive shift optimization
to account for engine or powertrain degradation
were not part of the scope of the study.
6.4
Simulation
methodology
             Section 6 Vehicle
             Models
89
No discussion of how driveline inertia is handled. This is
important in forward-looking models.
Addressed in revisions to section 6.4.
6.4
Results
             6.4 Transmission
             Models
108
Fig 6.1 appears to be a comparison of desired cvt ratio vs desired
6spd gear ratio. Should be stated as such.  The shift logic
controller should take into account the time to shift and whether or
not the desired shift is achievable.
Plots desired CVT ratio vs. desired DCT gear
ratios.  Shift optimizer does account for time to
shift and whether or not shift is desirable. The
study also included a constraint on shift
frequency. See revised section 6.4 detailing
comparison of optimized shifting to baseline
production vehicles.
6.4
Results
                                109
            What are the shift optimizer inputs? What are it's basic decision
            criteria?
                                                             Shift optimizer inputs are discussed. Strategy
                                                             tries to keep engine & trans at optimal efficiency.
                                                             See revised section 6.4.
                                              6.4
Results
                                110
            There is no discussion of engine downspeeding.
                                                             Engine downspeed not a first-order strategy, in
                                                             some cases it was the result of the optimized
                                                             shift strategy.
                                              6.4
Results
                                111
            There is no discussion of gear ratio selection.
                                                             Gear ratios are now included in section 6.4.
                                              6.4
Completeness
                                137
            No transmission data was shown. No mass, no inertia to
            efficiency maps, no gear ratios.
                                                             The transmission models use inertia values
                                                             comparable to contemporary production. See
                                                             revised Section 6.4.
                                              6.4
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                                                   Table 1:  Response to Individual Peer Review Comments
                T
                       Specific       Comment
Charge Question    Assump
Completeness
                   Section 6 Vehicle
                   Models
143
No discussion of how driveline inertia is handled.  This is
important in forward-looking models.
Addressed in revisions to section 6.4.
                                                                                                          6.4
Inputs and
Parameters
                   Transmission
                   technology
                   selection
174
The forecast that current 4-6 speed automatic transmissions will
have 7-8 speeds by 2020-2025 is appropriate for all except the
smallest and/or low cost vehicles (page 19).
                                                            EPA and Ricardo appreciate the comment; no
                                                            further response is required.
                                              6.4
Inputs and
Parameters
                   Transmission
                   technology
                   selection
176
Recommendation: The detailed assumptions showing how the
benefits of dry sump, improved component efficiency, improved
kinematic design, super finish, and advanced driveline lubricants
were added to the transmission maps should be added to the
report before it is released.
See revisions to section 4.4 and 6.4 in the final
report.
                                                                                                          6.4
Simulation
methodology
                   Transmission
                   optimization
207
A transmission shift optimization strategy is presented in the
report and the results are shown in Figure 6.1 (page 28). This
figure shows very frequent shifting, especially for 4th, 5th and 6th
gears.
See revised text in section 6.4 detailing
comparison of optimized shifting to baseline
production vehicles.
                                                                                                          6.4
Simulation
methodology
                   Transmission
                   optimization
208
Issue: Optimized shift strategies of the type used by Ricardo
have been previously evaluated and found to provide customer
complaints of "shift busyness".  Customers are likely to reject such
a shift strategy.
See revised text in section 6.4 detailing
comparison of optimized shifting to baseline
production vehicles.
                                                                                                          6.4
Recommendations
                                     242
            Recommendation:  The detailed assumptions showing how the
            benefits of dry sump, improved component efficiency, improved
            kinematic design, super finish, and advanced driveline lubricants
            were added to the transmission maps should be added to the
            report before it is released.
                                                            See revisions to section 6.4 in the final report.
                                              6.4
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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
             Shift Optimizer
386
Shifting strategy impacts efficiency, performance, and drivability.
Manufacturers are aware of this and balance all three when
calibrating shift maps. Changing baseline shift maps to improve
efficiency will have an impact on the other metrics which are also
important to the vehicle. Additionally, it is not clear how the
optimized shift strategy was developed, what the shift strategy is,
or how it will be applied to the range of transmissions in the study.
It is stated that is optimizes BSFC, however, there are other
constraints that must be applied in addition to this.
Your points are valid. The shift optimizer model
had many constraints at the expense of fuel
economy. The result was a similar number of
shifts over the cycle as compared to the baseline
vehicle and improved fuel economy. See revised
section 6.4 for more detail.
Inputs and
Parameters
             Input Data
             Review
398
The shift strategy is discussed qualitatively; however, it is not
described in enough detail to understand exactly how it is
accomplished.  Shift schedules are shown, however, no validation
is shown that would indicate that these shift schedules are optimal
as claimed.
See revised section 6.4.
6.4
Simulation
methodology
                                410
            Transmission Model: Ricardo describes an approach that asserts
            that using an average efficiency value vs a 3D efficiency map
            yields insignificant differences over the CAFE drive cycles, but
            offers no results to validate the claim.
                                                             See revised section 6.4.
                                              6.4
Simulation
methodology
                                411
            Transmission Model: Ricardo offers no discussion of how inertial
            changes are managed during shifts. This may have greatest
            impact on the shift strategies where the transmission shifts to put
            the engine at the best bsfc for the given load.
                                                             The transmission model only captures efficiency
                                                             and torque/speed for each gear.  Shift duration is
                                                             fixed and is already explained in report (6.4).
                                                             How "this may have  greatest impact on the shift
                                                             strategies" needs further explanation from
                                                             reviewer. Completely ignoring all of the rotating
                                                             inertias in these light duty vehicles would
                                                             probably affect the result by only 3%.
                                              6.4
Results
             6.5 torque
             Converter models
112
The lockup strategy seems very conservative.  Large gains are
achievable with more sophisticated control and are in use today.
See revised text in section 6.5.
6.5
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                                                  Table 1: Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Topic
Comment
Results
                                113
            What was the basis for the minimum rpm's for lockup sited?
            Should be based on lugging the engine. The controller should
            recognize when it needs to unlock the TC based on the engines
            ability to keep up.
                                                            The transmission controller prevented the engine
                                                            from extreme lugging. The torque converter
                                                            never locks at operating points where the engine
                                                            cannot keep up or drivability diminishes.
                                             6.5
Inputs and
Parameters
             Input Data
             Review
399
The torque converter models are standard models, thus, the
provided documentation is adequate.
EPA and Ricardo appreciate the comment; no
further response is required.
6.5
Results
             6.6 Final Drive
             Model
114
Only discussed the baseline, what improvements for 2020 and
what final drive selection criteria for the future vehicles was used?
Final drive ratio was one of the swept
parameters in the Design of Experiments matrix.
This allows the user to select from a range of
final drive ratios.
6.6
Results
                                           Performance calculations tied to the FTP, HWFET, and US06 test
                                           cycles do not adequately capture vehicle behavior under real-
                                           world operation. Therefore, technologies that address improving
                                           fuel economy under real-world operation are either excluded or
                                           their contribution not included. The application of a 20% reduction
                                           in fuel economy to the FTP75 bag 1 portion of the drive cycle for
                                           2010 baseline vehicles and 10% for 2020-2025 is crude, arbitrary,
                                           and treats only one of many problems with the driving simulation
                                           in the test cycles.  Test cycle difficulties carry over into the
                                           simulation of hybrid control strategies.
                                                                       The 20% value was based on actual results of
                                                                       EPA certification testing in the 2007 timeframe
                                                                       when it was applied. Current BMWs with electric
                                                                       water pumps exhibit an 11 % to 12% warmup
                                                                       penalty on bagl mpg (2011 EPA Test Car List
                                                                       Cert data) and EPA felt that an assumption of
                                                                       1 % to 2% further improvement was attainable.
                                                                       The EPA test cycles were not chosen  arbitrarily
                                                                       as they are the basis for past as well as future
                                                                       fuel economy standards.  Their relationship to
                                                                       "real world" fuel economy is well known and
                                                                       documented by EPA but does not serve to alter
                                                                       the legacy EPA Cert tests that will be used for
                                                                       2020-2025 fuel economy regulations. See
                                                                       excerpt 333.
                                                                                                         6.7
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                T
                 Specific
e Question     Assump
Comment
Other Comments
             Warm-Up
             Methodology
286
Elsewhere the report states, "A bag 1 correction factor is applied
to the simulated "hot" fuel economy result of the vehicles to
approximate warm-up conditions..." The correction factor
reduces the fuel economy results of the FTP75 bag 1 portion of
the drive cycle by 20% on the current baseline vehicles and  10%
on 2020-2025 vehicles that take advantage of fast warm-up
technologies" (page 29). No references or data are cited to
support this significant reduction in correction factor.
                                                                                                                            Response
See excerpt 333.
6.7
Recommendations
             Warm-Up
             Methodology
333
Cite sources of data for 10% and 20% factors applied to the cold
bag fuel economy data.
The 20% value was based on EPA test data and
a legacy of the 2007-2008 study and was
retained for current technology vehicles without
electric water pumps or other advanced
technologies that improve vehicle/powertrain
warmup. Current BMWs with electric water
pumps exhibit an 11 % to 12% warmup penalty
on bagl mpg (2011 EPA Test Car List Cert data)
and EPA felt that an assumption of 1 % to 2%
further improvement was attainable. This was
based on the Ford Escape warmup data
measured by Argonne Natl Lab, which was
better than Ricardo's model data at the time. If
today's Ford and BMW engines could achieve a
0.88 factor on bag 1, it seems reasonable to
expect future engines to achieve that.
6.7
Inputs and
Parameters
                               75
            Is there any accounting for the energy conversion on hybrids from
            the high voltage bus to the low voltage?
                                                           The DC-DC converter has specified efficiency
                                                           characteristics. See section 6.8.
                                             6.8
Simulation
methodology
             6.8 Hybrids
97
Were separate optimization runs to determine the best control
strategy done? How are we assured the best control strategy is
implemented?
See revised Section 6.8, which includes
significant additional text and figures to address
these concerns.
6.8
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                T
                      Specific      Comment
Charge Question     Assump
Completeness
                  Section 4.3
                  Hybrids
133
Don't see any data on the battery technology, battery
management, SOC control strategies. No discussion of regen
braking strategies.
Ricardo and EPA decided on generic Li-ion
battery technology that was equivalent to best
today.  See further discussion in section 6.8.
6.8
Completeness
                  6.8 Hybrid
                  Models
145
Too much data is missing. What were the pack voltages? What
were the battery technologies? Was there only one or more?
Other than improved resistance, what other future improvements
were included, like improved power density, improved usable
SOC range? What was the control strategy for each type?
See revised Section 6.8, which includes
significant additional text and figures to address
these concerns.
6.8
Completeness
                                     146
           Load leveling the engine by charging the batteries has been
           shown to not be a very good idea because the round trip
           efficiency hit is a killer. Should only be used when SOC falls
           below a certain level.
                                                           Load averaging was the approach chosen by the
                                                           full study team. If the engine is on, the study
                                                           assumes that operate at most efficient point.
                                                           Ricardo made a side comparison to evaluate this
                                                           issue; definitely better W/P2. See the revised
                                                           section 6.8.
                                             6.8
Completeness
                                     147
           We're left to assume that SOC leveling is accomplished, but there
           is no description of how? Was an EPA/SAE method used.
                                                           See revised section 6.8
                                             6.8
Inputs and
Parameters
                   Hybrid
                   technology
                   selection
178
Issue: The adequacy of the P2 Parallel and PS Power Split
Hybrid systems cannot be determined without having, at a
minimum, schematics and operational characteristics of the each
system together with comparisons with today's hybrid systems.
See revisions to Section 6.8.
6.8
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                T
                       Specific       Comment
Charge Question    Assump
Inputs and
Parameters
                   Hybrid
                   technology
                   selection
179
Although not contained in the report, the teleconference call EPA
on May 5, 2011 revealed that 90% of the deceleration kinetic
energy would be recovered.
Kinetic energy recovery is limited by the following:
-   Maintaining high generator efficiency over the range of speeds
   and resistive torques encountered during deceleration
-   Limitations on the rate at which energy can be stored in the
   battery
-   Losses in the power electronics
-   Some energy is lost when energy is withdrawn from the
   battery for delivery to the motor.
-   Inefficiencies in the motor at the speeds and torques required.
The inefficiencies of each of these four subsystems are in series
and are compounded.  If each subsystem had 90% efficiency, the
kinetic energy recovery efficiency would be only 66%.
Your points are valid.  To clarify: The model
assumes that 90% of the mechanical braking
energy will be performed by the hybrid electrical
system (not recovered) and less than 90% would
be stored and even less available for mechanical
reuse due to system efficiencies.  All of this has
been accounted for in the hybrid model. See
revisions to Section 6.8 to clarify these points.
6.8
Inputs and
Parameters
                   Hybrid
                   technology
                   selection
180
Issue: Capturing 90% of the deceleration kinetic energy is a
significantly goal. The technology to be used to achieve this goal
needs to be explained and appropriate references added to the
report.
Your point is valid. To clarify: The model
assumes that 90% of the mechanical braking
energy will be performed by the hybrid electrical
system (not recovered) and less than 90% would
be stored and even less available for mechanical
reuse due to system efficiencies. All of this has
been accounted for in the hybrid model. See
revisions to Section 6.8 to clarify these points.
6.8
Inputs and
Parameters
                   Battery SOC
                   swing and SOC
190
Although not contained in the report, an email from Jeff Cherry
(EPA) on May 5, 2011 revealed that the SOC swing was 30%
SOC to 70% SOC or 40% total, which appears to be appropriate.
Section 6.8 of the report has been revised to
include the 40% SOC value.
6.8
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                T
                 Specific
,e Question     Assump
Topic
Comment
Results
             Sample runs of
             CSM
215
In the review process, several sample runs of the Complex
Systems Model (CSM) for the Standard Car (Toyota Camry) were
made and the results are shown in the attached chart (at the end
of this peer review) and summarized below: Stoichiometric Dl
Turbo with Stop-Start to PS Hybrid
-   11.1% improvement in M-H mpg
-   A detailed explanation of the differences in the improvements
   between the P2 and PS hybrids should be provided in the
   report, especially considering that the P2 hybrid has better fuel
   economy and uses a 70% smaller electric motor (24 vs. 80
   kW).
The P2 hybrid architecture has better driveline
efficiency than the Powersplit type. Also, despite
having a smaller electric machine than the
Powersplit traction motor, both EM's are able to
regenerate at least 90% of the braking energy on
the drive cycles.
6.8
Results
             Sample runs of
             CSM
216
In the review process, several sample runs of the Complex
Systems Model (CSM) for the Standard Car (Toyota Camry) were
made and the results are shown in the attached chart (at the end
of this peer review) and summarized below: Stoichiometric Dl
Turbo PS Hybrid to Naturally Aspirated Atkinson CPS Hybrid
-   Loss of 2.3% M-H mpg (From Stoichiometric Dl Turbo PS
   Hybrid)
-   The details of the Naturally Aspirated Atkinson CPS Hybrid
   should be provided to explain the nearly equal fuel economy
   to the Stoichiometric Dl Turbo PS Hybrid.
One of the advantages of hybridization is the
ability to operate the engine near its most
efficient point. In this case, the Atkinson engine
had a better best BSFC region compared to the
Stoichiometric Dl Turbo engine.
6.8
Results
             Sample runs of
             CSM
217
In the review process, several sample runs of the Complex
Systems Model (CSM) for the Standard Car (Toyota Camry) were
made and the results are shown in the attached chart (at the end
of this peer review) and summarized below: Stoichiometric Dl
Turbo PS Hybrid to Naturally Aspirated Atkinson DVA Hybrid
-   2.1 % M-H mpg improvement in M-H mpg (From Stoichiometric
   Dl Turbo PS Hybrid)
-   The details of the Naturally Aspirated Atkinson DVA Hybrid
   should be provided to explain the nearly equal fuel economy
   to the Stoichiometric Dl Turbo PS Hybrid
See response to Comment Excerpt 216.
6.8
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                 Specific
e Question     Assump
                  Topi
Comment
Other Comments
             Hybrid
             Technologies
             Models
265
Key elements of a hybrid system include: electric machines
(motor-generator), power electronics, and a high-voltage battery.
Only the following vague description of the models for these
subsystems was provided:  "For each of these systems, current
state of the art technologies were adapted to an advanced 2020-
2025 version of the systems, such as by lowering internal
resistance in the battery pack to represent 2010 chemistries under
development and decreasing  losses in  the electric machine and
power electronics to represent continued improvements in
technology and implementation" (page  29).  This vague
description did not provide adequate details to assess the
adequacy of these models. For example, specific values for
internal resistance with references should be provided together
with an illustration of how this was incorporated in the model of
the battery.
See revisions to section 6.8.
6.8
Other Comments
             Hybrid
             Technologies
             Models
268
No mention was provided of how the cooling system for the hybrid
system was modeled.
The hybrid power electronics and motors were
assumed to be water cooled with the waste heat
added to the cooling load of the vehicle based on
the efficiencies described in the report.
6.8
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                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
             Hybrid
             technology
             selection
345
Hybrid vehicles are particularly challenging to model because of
the extra components which allow multiple torque sources, and
thus, require some form of torque management strategy (i.e. a
supervisory control.) The report briefly describes a proprietary
supervisory control strategy that is used to optimize the control
strategy for the FTP, HWFET, and US06 drive cycle.  The
strategy claims to provide the "lowest possible fuel  consumption"
which seems to be somewhat of an exaggeration - this implies
optimality which is quite a burden to achieve and verify for such a
complicated problem. The strategy also is reported to be "SOC
neutral over a drive cycle" which is also difficult to achieve in
practice in a forward looking model.  Once can get  SOC with a
certain window, however, short of knowing the future or simply not
using the battery - it is impossible to develop a totally SOC neutral
control strategy.
The powertrain operates at near best fit, and
thus is expected to provide very good fuel
consumption. But, it is not optimized over the
whole design space. Ricardo has adjusted the
"lowest possible..." language and added a state
flow diagram. See revised section 6.8.
6.8
Inputs and
Parameters
             Hybrid
             technology
             selection
347
Without even basic details on the hybrid control strategy, it is
simply not possible to evaluate this aspect of the work.  Because
of the batch simulations with varying component sizes and
characteristics, this problem is not trivial. Supervisory control
strategies used in practice and in the literature require intimate
knowledge of the efficiency characteristics and performance
characteristics of all of the components (engine, electric
motors/inverters, hydraulic braking system, and energy storage
system) to develop control algorithms.  This concern is amplified
by the lack of validation of the hybrid vehicle model against a
known production vehicle. It is unclear how a "one-size fits all"
control strategy can be truly be perform near optimal over such
widely varying vehicle platforms.
See revised section 6.8.
6.8
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                T
                 Specific
e Question     Assump
Comment
Recommendations
             Hybrid
             technology
             selection
350
Validate that the HEV control algorithm performs equally well on
all vehicle classes.
The class of vehicles does not change the hybrid
control strategy. The different roadload effects of
the various classes change the level of benefit
from hybridization: however, the goal of
maximizing efficiency through recovering brake
energy and operating the engine at low BSFC
points remain the same.
6.8
Inputs and
Parameters
             Electric Traction
             Components
352
The model of electric traction components is not discussed in any
detail, as the only mention in the report is that current technology
systems were altered by "decreasing losses in the electric
machine and power electronics." Given the importance of the
electric motor  and inverter system in hybrids this is not
acceptable.
See significant revisions to section 6.8.
6.8
Recommendations
             Electric Traction
             Components
353
Describe the method used to model electric traction components.
See expanded discussion of hybrid models in
section 6.8.
6.8
Recommendations
             Electric Traction
             Components
354
Provide validation/basis for the process used to generate future
technology versions of these components.
Part of Row 329; see expanded discussion of
hybrid models in section 6.8.
6.8
Recommendations
             Electric Traction
             Components
355
Describe the technique used to scale these components.
Part of Row 329; see expanded discussion of
hybrid models in section 6.8.
6.8
Inputs and
Parameters
             HEV Battery
             Model
356
Battery models for HEVs are necessary to adequately model the
performance of an HEV. The report provides no substantive
description of the battery pack model, other than that the model
was developed by "lowering internal resistance in the battery pack
to represent 2010 chemistries under development."  Battery pack
size is also not a currently a factor in the model - this has a
impact of charge and discharge efficiency of the battery pack.
See significant revisions to section 6.8.
6.8
Recommendations
             HEV Battery
             Model
357
Describe the method used to model the HEV battery.
See revisions to section 6.8.
6.8
Recommendations
             HEV Battery
             Model
358
Provide validation/basis for the process used to generate future
technology versions of the battery.
See revisions to section 6.8.
6.8
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                T
                       Specific       Comment
Charge Question    Assump
Recommendations
                   HEV Battery
                   Model
359
Describe the technique used to scale the HEV battery.
See revisions to section 6.8.
6.8
Inputs and
Parameters
                   Battery Warm up
                   1, Battery Warm
                   up 2
387
The battery model described has the following possible problems:
The model is relatively simple - but could potentially work for the
application and generally is consistent with the fidelity of the rest
of the model.
EPA and Ricardo appreciate the comment; no
further response is required.
6.8
Inputs and
Parameters
                   Battery Warm up
                   1, Battery Warm
                   up 3
388
The battery model described has the following possible problems:
The model references ambient temperature for heat rejection.
Most HEVs pull in cabin air rather than outside air for cooling,
thus, this will cause modeling error.
The drive cycles covered in this study represent
cabin temperatures similar to the ambient test
temperatures.
6.8
Inputs and
Parameters
                   Battery Warm up
                   1, Battery Warm
                   up 4
389
The battery model described has the following possible problems:
Adjusting the Mbat x Cpbat term by 200% is a red flag that
something might be fundamentally wrong with either the model
formulation or the data used in the model.  There should be
minimal errors in the mass estimation of the pack and the specific
heats of battery modules can be found in the literature or through
testing.
These parameters were not part of the Ricardo
study.
6.8
Inputs and
Parameters
                   Battery Warm up
                   1, Battery Warm
                   up 5
390
The battery model described has the following possible problems:
The method of handling battery packs of different classes of
vehicles is not described, nor are the actual parameters for these
different models disclosed.
See revised section 6.8 for details of sizing
battery packs for the study.
6.8
Simulation
methodology
                                     412
            Hybrid: I don't see any effort to model motor/inverter temperature
            effects. One would expect significant degradation of motor
            capability as things heat up during normal operation.
                                                             Motor/Inverter efficiencies were modeled as
                                                             outlined in section 6.8 of the report at normal
                                                             operating temperatures.
                                              6.8
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                T
                 Specific
e Question     Assump
Topic
Comment
Results
                               416
            Motor Efficiency Maps: I am having trouble believing that motor
            efficiency will stay above 90% once temperature effects are
            accounted for. It also seems to me that these numbers don't
            include the inverter even though the authors say that it does. The
            UQM maps seem more reasonable.  As stated in a previous
            comment,  I believe that the cost reductions needed for motors will
            drop their efficiencies in the future.
Motor/Inverter efficiencies were modeled as
outlined in section 6.8 of the report at normal
operating temperatures. The efficiency map
shown includes the inverter efficiency.
6.8
Inputs and
Parameters
                               421
           Carlson, R., etal., Argonne National Laboratory, On-Road
           Evaluation of Advanced Hybrid Electric Vehicles over a Wide
           Range of Ambient Temperatures EVS23 - Paper #275,15 p.
           Paper reports on-road and dynamometer testing of two hybrid
           vehicles at cold (-14 degC) and hot (33 decC) conditions. Fuel
           economy increases with temperature (except for highest
           temperatures with the system which does not limit battery
           temperature).
           Comment: Paper provides data showing importance of
           temperature on hybrid vehicle fuel economy. These data are used
           by Ricardo to validate their battery warm up model, see next
           document.
EPA and Ricardo appreciate the comment; no
response needed.  Background materials
included both highly relevant data and sources
as well as some general information sources
used during the course of the study. Not all
sources  reviewed were of critical  importance to
the study.
6.8
Simulation
methodology
                               422
            Ricardo, Hybrid Battery Warm Up Model Validation - Update,
            Light Duty Vehicle Complex Systems Simulation ,EPA Contract
            No. EP-W-07-064, work assignment 2-2,15 Mar 10, 5 p.
            proprietary) This report presents a simple battery heat transfer
            model for battery warm up and compares with Argonne National
            Laboratory of the previous document.
            Comment: Model produces adequate prediction of battery
            temperature.
EPA and Ricardo appreciate the comment; no
response needed.
6.8
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                T
                       Specific
      e Question     Assump
Comment
Inputs and
Parameters
                                     425
            Ricardo, Engine and Battery Warm-Up Methodology, Light Duty
            Vehicle Complex Systems Simularion, 17 Feb 10,16 p.
            (proprietary) Document reviews engine and battery warm-up
            strategies and provides a simple model.
            Comment: The approach to battery warm-up is uncertain. Points
            to importance of test cycle (FTP for fuel economy compliance
            versus test for EPA label versus real-world).
                                                            Cold FTP was not included in this study.
                                             6.8
                                                                                                             The motor maps used in the study included the
                                                                                                             efficiency of the motor controller.
Other Comments
429
Ricardo, Hybrid Controls Follow-up, 10 Sep 11, 3 p. (proprietary)
Report discussed motor/general efficiency map used for 2020
technology. Projected efficiencies peak at 95% but most P2 hybrid
application if below 90% efficiency.
Comment: I am not qualified to assess if the projected
motor/generator efficiencies are appropriate for 2020-2025 as
reported, but they seem low for 15 years in the future.
                                             6.8
Other Comments
                   Hybrid
                   Technologies
                   Models
266
In contrast, as an example, Staunton et al. (2006) provided a
detailed motor efficiency map, shown below, as well as efficiency
maps of other key components of the Prius hybrid vehicle. Similar
maps for all hybrid subsystems would be expected  in this report.
(See Exhibit 5)
See revisions to section 6.8.
6.8
Other Comments
                   Hybrid
                   Technologies
                   Models
267
In addition, "a Ricardo proprietary methodology was used to
identify the best possible fuel consumption for a given hybrid
powertrain configuration over the drive cycles of interest." (page
29), which precluded an assessment of its suitability.
See revisions to section 6.8.
6.8
Recommendations
                   Hybrid
                   technology
                   selection
349
Better describe the hybrid control strategy and validate against a
current production baseline vehicle.
See revisions to section 6.8.
6.8
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                 T
                 Specific
e Question     Assump
Comment
Recommendations
             Hybrid Controls
             Presentations
400
Several hybrid controls presentations were provided, however, it
was difficult to piece together what information superseded the
other since they were provided out of context. There were several
good slides showing dynamic programming results of different
control scenarios, however, it is assumed that this was not used
for the mass simulation since it would be computationally
impractical. Thus, I expected to see some results comparing the
offline control  results to the actual control used in the vehicle
simulation, however, this was not found. The major concern in
this area is developing a control strategy that is near optimal for a
wide variety of hybrid architectures as well as architectures with
varying component types and sizes.  Without further validation in
this area it is not clear that the hybrid results are valid since the
control has such an important role in this.
See revisions to section 6.8.
6.8
Recommendations
             Warm-Up
             Methodology
334
Cite and/or validate the modeling approach used.
Please refer to the revised report concerning
technology/model validation.
Results
                                42
            For the vehicle performance simulation results shown in Table
            7.1, were there any significant adjustable parameters used to fit
            these vehicles?
                                                             All vehicle parameters (road loads, mass, etc.)
                                                             were the same for both cases in order to validate
                                                             the models.
                                              7.1
Results
                                43
            Even though it appears that the validation results from the
            simulation have "acceptably" close agreement with the test data,
            there are up to 15% off. Even for the small car where all data is
            available, the error is on the order of 5%. These discrepancies are
            usually not negligible and should be taken into account when
            conclusions are drawn from the results, especially if regulation is
            to be proposed based on these.
                                                             EPA will take this into account in how it uses the
                                                             final results to support rulemaking actions.
                                              7.1
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                 T
                       Specific       Comment
Charge Question     Assump
Other Comments
                                     55
            It would be desirable to show the analysis used to convert fuel
            consumption savings to vehicle greenhouse gas (GHG) emissions
            equivalent output. Ultimately, what matters is the GHG savings
            resulting from the combined production and use cycle of
            alternative fuel options for combustion engines.
                                                            Appendix 3 to the final report presents the
                                                            baseline fuel economy and C02 output
                                                            equivalents for all classes of vehicles considered
                                                            in this study. Note that the C02 equivalents used
                                                            in these tables were provided by the EPA as
                                                            9,087 g/gal of fuel for gasoline and 10,097 g/gal
                                                            for diesel.
                                              7.1
Results
                   7.1 Baseline
                   Conventional
                   Vehicle Models
116
Better definition of what "acceptably close" means. This doesn't
meet the criteria for objectivity. Something like, "the advisory
committee determined that the baseline models had to predict
within x% to be usable for this study."
The final report retains this text as is, because
the text represents the approach taken during
the study, during which EPA determined the
results to be acceptable for moving forward. See
revisions to section 7.1 to further describe the full
process used to develop baseline vehicles.
7.1
Inputs and
Parameters
                   Baseline vehicle
                   subsystem
                   models/maps
160
The development of baseline vehicle models with comparison of
the model results to available 2010 EPA fuel economy test data
was appropriate.
EPA and Ricardo appreciate the comment; no
further response is required.
7.1
Simulation
methodology
                   Baseline vehicle
                   model validation
                   results
204
Ricardo developed baseline vehicle simulations for 2010 vehicles
for which EPA fuel economy data were available (page 30). "For
the 2010 baseline vehicles, the engine fueling maps and related
parameters were developed for each specific baseline exemplar
vehicle." (page 25). Even though these are production vehicles,
the models and maps used were not described (including whether
they were derived from actual measurements or models) and they
were not provided in the report so that their appropriateness could
not be assessed.
It is important to note that, following the model
validation phase, baseline vehicles were not
established just using the given EPA Test List
data or the raw validated vehicle fuel economy
results. Rather than using the raw validation
vehicles and corresponding fuel economy
results, a new set of baseline values were
determined to facilitate a uniform comparison
between the advanced (future) concepts and
today's current technologies.
7.1
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                T
                 Specific
e Question     Assump
                  Topic
Comment
Simulation
methodology
             Baseline vehicle
             model validation
             results
205
Table 7.1 shows the calculated vs. EPA test data for the baseline
vehicle fuel economy performance. This table should include
percentage variation of the model calculations vs. the test data.
The agreement of the model with the test data is within 11 %, but
this is a larger error than some of the incremental changes shown
in Appendix 3. A closer agreement would have been expected.
Table 7.1 now compares validation model results
with EPA Test List data for FTP and HWFET. All
of the validation results are within 5%, with the
exception of the Large MPV HWFET result,
which is within 9.5% of the published value. The
purpose of the validation model results is to
provide a benchmarked starting point for the rest
of the analysis.
7.1
Simulation
methodology
             Baseline vehicle
             model validation
             results
206
Recommendation: A closer examination of the reasons for the up
to 11% discrepancies between the models and baseline vehicles'
EPA fuel economy test data should be undertaken so that the
models could be refined to provide better agreement.
EPA and Ricardo, together with the advisory
committee, determined that the degree of
agreement on fuel economy was adequate for
this study.  It is important to note that, following
the model validation phase, baseline vehicles
were not established just using the given EPA
Test List data or the raw validated vehicle fuel
economy results. Rather than using the raw
validation vehicles and corresponding fuel
economy results, a new set of baseline values
were determined to facilitate a uniform
comparison between the advanced (future)
concepts and today's current technologies.
7.1
Recommendations
                               241
            Recommendation: A baseline model of a hybrid vehicle should be
            developed and compared to 2010 EPA fuel economy test data for
            production hybrid vehicles.
                                                            During development of the PowerSplit model a
                                                            modified small car with PS was simulated to
                                                            validate the model but was not formalized for the
                                                            report.
                                             7.1
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                T
                       Specific
Charge Question    Assump
     •'--•--              Topic
Comment
Recommendations
                                     247
            Recommendation: A closer examination of the reasons for the up
            to 11% discrepancies between the models and baseline vehicles'
            fuel economy test data should be undertaken so that the models
            could be refined to provide better agreement.
                                                            Table 7.1 now compares validation model results
                                                            with EPA Test List data for FTP and HWFET. All
                                                            of the validation results are within 5%, with the
                                                            exception of the Large MPV HWFET result,
                                                            which is within 9.5% of the published value. The
                                                            purpose of the validation model results is to
                                                            provide a benchmarked starting point for the rest
                                                            of the analysis.
                                              7.1
Inputs and
Parameters
                   Hybrid
                   technology
                   selection
346
Another factor that must be considered is that a hybrid strategy
that achieves maximum fuel efficiency on FTP, HWFET, and
US06 does not consider many other relevant factors.
Performance metrics like 0-60 time and drivability metrics often
suffer in practice. In today's hybrids, the number of stop-start
events  is sometimes limited from the optimum number for
efficiency because of the emissions concerns. Because of these
factors  and others, a strategy achieving optimal efficiency may be
higher than what can be achieved in practice.
The study approach used 0-60 time, max grade
at different speeds, and other drivability metrics
to make sure that the modeled vehicles had
acceptable performance on core drivability
issues. See the nominal test results in Section
7.1 and Appendix 5.
7.1
Inputs and
Parameters
                   Hybrid
                   technology
                   selection
348
A last comment is that there is no validation of the HEV model
against current production vehicles. At a minimum, the Toyota
Prius has been dissected sufficiently in the public domain to
conduct a validation of this class of hybrid electric vehicle.
No validation was performed for the hybrid
architectures as no P2 hybrid vehicles were in
production during the study. The Small Car with
P2 architecture was simulated at comparable
road loads to the Toyota Prius, and the fuel
economy figures were higher than the current
Prius.
7.1
Simulation
methodology
                   7.2 Nominal Runs
98
Was a separate matrix of simulations run to obtain the nominal
sizes for the advanced engine or was it merely a matter of
matching the peak torque.
See revised section 7.2 for discussion.
7.2
Simulation
methodology
                                     99
            How was a 20% reduction in engine size for the nominal hybrid
            engine arrived at? Even for the micro-hybrid (engine start/stop)?
                                                            The final report clarifies why 20% downsize of P2
                                                            & PS hybrids and all engines. Atkinson sized
                                                            directly for hybrids. See Section 7.2. Adding to
                                                            description of hybrid engine sizing methodology.
                                              7.2
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                T
                       Specific       Comment
Charge Question    Assump
Simulation
methodology
                                     100
            "These summary results... .used to assess the quality of the
            simulation...." Where is the data for this assessment published?
            What were the criteria that said pass or fail?
                                                            Appendix 5 presents the nominal test run results
                                                            data.
                                              7.2
Inputs and
Parameters
                   Battery SOC
                   swing and SOC
191
Achieving neutral SOC (neither net accumulation or depletion) for
hybrid vehicle simulations is appropriate (page 30).
EPA and Ricardo appreciate the comment; no
further response is required.
7.2
Results
                   8.2 RSM
119
A description of how the neural network is deployed is needed,
only the why it was used is discussed in this section. What were
the best fit criteria?  What types of equations did the neural net
have to play with? Where are the fit's published? How was it
determined that the "one fit per transmission" was the best way to
go?
The fit criteria were based on how well the
regression line approximated the real data points
from the DoE, using both the training data as
well as the validation data.
Simulation
methodology
                                     369
            The vehicle simulator is used to generate several thousand
            simulations using a DOE technique.  This data is then fit with a
            neural-network-based response surface model in which the "goal
            was to achieve low residuals while not over-fitting the data." This
            response surface model then becomes the method from which
            vehicle design performance is estimated in the data analysis tool.
            In this case, the response surface model is nothing more than a
            multi-dimensional black-box curve fit. There was no error analysis
            given in the report regarding this crucial step.  By way of example,
            the vehicle simulator could provide near perfect predictions of
            future vehicle performance; however, a bad response surface fit
            could corrupt all of the results.
                                                            See revised section 8.
                                                                                 71

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                 T
                  Specific
e Question     Assump
Topic
Comment
Results
              8.1 Evaluation of
              Design Space
118
Why was Latin hypercube sampling methodology picked over
other sampling methods? While it's attributes are mentioned, what
other methods were considered?
As Section 8.1 states: "The method randomly
samples the multidimensional parameter space
in a way that provides comprehensive and
relatively sparse coverage for best efficiency. It
also allows one to efficiently continue to fill the
multidimensional parameter space by further
random sampling. It provides more flexibility than
traditional multi-level factorial designs for
assessing a large parametric space with an
efficient number of experiments." Other,
traditional, multi-level factorial designs were not
feasible within the number of simulations to be
performed within the scope of this study.
8.1
Recommendations
                                12
            The design space should be expanded to include performance
            parameters, such as power/weight or 0-60 times.
                                                             Performance parameters are available in the
                                                             RSM tool.
Results
                                46
            The plots showing simulation results in blue, red, etc. could be
            better labeled (i.e. legends could be inserted in the plots) and
            possibly presented in a relative format indicating percent
            improvements over the baseline engine rather than absolute
            numbers. This is more of a personal choice for a more clear
            representation of the predicted improvement, rather than stating
            that there is anything wrong with the current representation.
                                                             EPA and Ricardo appreciate the comment; no
                                                             further response is required.
Inputs and
Parameters
              Other inputs
194
The Design Space Query within the Data Visualization Tool allows
the user to set a continuous range of variables within the design
space range.  Although this capability is useful for parametric
studies, the following risks are incurred with some of the
variables.
Ricardo is preparing a user guide for the tool to
help address these types of concerns.
Inputs and
Parameters
              Other inputs
195
The sliders for "Eng. Eff" and "Driveline Eff." would allow the user
to arbitrarily change engine efficiency or driveline efficiency
uniformly over the map without having a technical basis for such
changes.
The justification for the range of use for the input
variables in a given situation is not part of this
study
                                                                                  72

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                T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
             Other inputs
196
The slider for weight would allow the user to add hybrid or diesel
engines with signficant weight increases without incurring any
vehicle weight increase.
The weight of technologies is not part of this
study due to the complex nature and many
opinions regarding this topic.
Inputs and
Parameters
             Other inputs
197
Recommendation: A default weight increase/decrease should be
added for each technology. If weight reductions are to be studied,
then the user should have to input a specific design change, with
the appropriate weight reduction built into the model, rather that
having an arbitrary slider for weight.
The weight of technologies is not part of this
study due to the complex nature and many
opinions regarding this topic.
Results
             9.1 Basic Results
120
Why 10Hz sampling rate? By what criteria was a run considered
good vs bad?
See footnote added to Section 9.1. Bad runs are
those that failed to follow the cycle trace as
described in EPA test procedures.
9.1
Results
             9.3 Exploration of
             the Design Space
121
If boundaries of acceptable performance were applied, a
considerable number of simulation runs could be eliminated.
The additional runs were needed to adequately
fill the design space to allow the RSM tool user
to obtain accurate results when changing input
variables.
9.3
Other Comments
                               13
           The conclusions, Section 11, are a reasonable summary of the
           work conducted.
                                                            EPA and Ricardo acknowledge and appreciate
                                                            the reviewer's comments.
                                             11
Completeness
                               50
           The "Conclusions" section of the report should be renamed
           "Summary" since it does not present any actual conclusions
           based on the results, but it does provide a summary of the project.
                                                            EPA and Ricardo appreciate the comment. The
                                                            section name has been changed.
                                             11
Recommendations
                               10
           There should be a table describing the baseline vehicles.
                                                            See Appendix 3 in final report.
                                             Appendix 3
                                                                                73

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                T
                       Specific
Charge Question    Assump
     •'--•--              Topic
Comment
Completeness
                                     299
            Based on the above, it is clear that this reviewer feels the report is
            inadequate at describing the entire process of modeling work from
            input selection to results. There was not a single subsystem that
            was documented at the level desired. It is understood that, in
            some cases, there are things of a proprietary nature that must be
            concealed. As a trivial example, the frontal area of the vehicle
            classes does not seem to be anywhere in the report or data
            analysis tool. This is one parameter amongst hundreds excluding
            the real details of the models (i.e. equations or block diagrams),
            methods used to generate engine maps, details on control laws,
            etc.  On the topic of proprietary data, there are many ways of
            obscuring data sufficiently that can demonstrate a key point (i.e.
            simulation accuracy) without compromising confidentiality of data
            - this should not be a major barrier to providing some insight into
            the inner working of the simulator.
                                                            Baseline vehicle parameters are tabulated in
                                                            Appendix 3.
                                                                                                                                                            Section
                                                                                                                                                           D pf p rp n CP
                                              Appendix 3
Recommendations
                   Vehicle model
                   issues
305
List all parameters used for each vehicle class for simulation.
Baseline vehicle parameters are tabulated in
Appendix 3.
Appendix 3
Completeness
                                     125
            It said there was a comprehensive list of technologies that the
            group started with, that list should be shown and a comment on
            why it wasn't included.
                                                            Complete technology selection list is now an
                                                            appendix to the report.
                                              Attachment
                                              A
Recommendations
                                     151
            Considerably more time in this effort is required up front in the
            report, to discuss the process of building consensus on data and
            models.  Because this is not really discussed, it gives the
            impression that not much was done.
                                                            Please refer to the technology selection slides
                                                            provided in the appendices to give the
                                                            commenter a sense of the rigor of the technology
                                                            selection process.
                                              Attachment
                                              A
Recommendations
                                     153
            An uncertainty rating for each model/data set should be published
            to highlight the relative differences in the
            assumptions/extrapolation of future technologies.
                                                            Some level of uncertainty is provided in the
                                                            technology selection slides provided in the
                                                            attachment to the final report.
                                              Attachment
                                              A
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                T
                 Specific
e Question     Assump
Inputs and
Parameters
             Engine
             technology
             selection
Comment
166
The engine technologies selected for this study, listed in Table 5.1
(page 22), are appropriate, but are not all-inclusive of possible
future engine technologies.
EPA and Ricardo appreciate the comment; no
further response is required. The program team
selected the set of possible technologies that
appeared to provide the best suite of
improvements and viability in the study time
frame.  See Attachment A to the final report for
the full range of technologies initially evaluated.
Attachment
A
Inputs and
Parameters
             Engine
             technology
             selection
170
Issue: There are many engine technologies that have potential for
reduced GHG emissions that were not included in this study, such
as:
-   Single stage turbocharged engines
-   Diesel hybrids
-   Biofueled spark ignition and diesel engines
-   Natural gas fueled engines
-   Other alternative fuel engines
-   Charge depleting PHEV and EV
EPA and Ricardo appreciate the comment. The
program team selected the set of possible
technologies that appeared to provide the best
suite of improvements and viability in the study
time frame. See Attachment A to the final report
for the full range of technologies initially
evaluated.
Attachment
A
Completeness
                               230
            There are many engine technologies that have potential for
            reduced GHG emissions that were not included in this study, such
            as:
            -   Single stage turbocharged engines
            -   Diesel hybrids
            -   Biofueled spark ignition and diesel engines
            -   Natural gas fueled engines
            -   Other alternative fuel engines
            -   Charge depleting PHEV and EV
                                                            EPA and Ricardo appreciate the comment. The
                                                            program team selected the set of possible
                                                            technologies that appeared to provide the best
                                                            suite of improvements and viability in the study
                                                            time frame. See Attachment A to the final report
                                                            for the full range of technologies initially
                                                            evaluated. Part of the evaluation process
                                                            included expectation of market share based on
                                                            cost, performance, and readily available fuel
                                                            sources.
                                              Attachment
                                              A
Inputs and
Parameters
             Future Friction
             Assessment
392
The provided presentation does not describe how engine friction
projections to 2020 are made or how they are modeled. It
provides some data from 1995 to 2005, however, it does not
provide any useful insight into how this information is used.
Friction reduction improvements were extended
from those used in the 2008 EPA study as
described in Attachment A.
Attachment
A
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                T
                 Specific
e Question     Assump
Comment
Completeness
                               450
            Ricardo, Report on light-duty vehicle technology package
            optimization, 4 Dec 09, 32 p. This is a progress report on
            Ricardo's modeling work for the EPA. A range of engine
            technologies, hybrid technologies, transmission, and vehicle
            technologies are described.
            Comment: A comprehensive list of near term technologies are
            included. The report is incomplete and optimization apparent is
            not included here.
                                                           See Attachment A to final report.
                                             Attachment
                                             A
Recommendations
             Additional
             recommendations
             shown in bold
             print throughout
             other sections of
             this report are
             repeated below
             for completeness
244
Recommendation:  To establish the adequacy of the subsystem
models/maps, derivation details should be provided.
Use of proprietary data was a ground rule of the
study. However, in the final report, we have
added a great deal of detail using publically
available references and sources to provide
further understanding of these issues and how
the study addressed them.
General
Simulation
methodology
                                           Ricardo simulated dynamic vehicle physical behavior using MSC
                                           EasySTM software with 10 Hz time resolution. This software and
                                           the time resolution are appropriate for the computations to show
                                           the effect of component interactions on vehicle performance. 10
                                           Hz time resolution is sufficient to capture both driver behavior and
                                           vehicle response. Should the application of information
                                           technology, as is being implemented, as a means of vehicle
                                           control for reducing fuel consumption become a future strategy,
                                           the model should be able to provide a suitable simulation.
                                                                       EPA and Ricardo acknowledge and appreciate
                                                                       the reviewer's comments.
                                                                                                        General
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                 T
                 Specific
e Question     Assump
Comment
Simulation
methodology
                                            Drivetrain synergistic effects seem to be predicted reasonably.
                                            This was demonstrated by calculation of fuel economy of the
                                            baseline vehicles and comparison with EPA certification test data.
                                            The model does not seem to have  the capability to capture
                                            vehicle weight-drivetrain synergistic effects. Vehicle weight
                                            reductions associated with drivetrain efficiency improvements are
                                            input rather than modeled internally. This is an important
                                            deficiency. Similarly, from the Complex System Tool, weight
                                            reductions do not seem to result in reduction in  engine
                                            displacement.	
                                                                         The mass of technologies was not included in
                                                                         this study due to the evolving nature and
                                                                         complex opinions regarding this topic. The user
                                                                         of the RSM tool is responsible to add or remove
                                                                         mass from the baseline vehicle to obtain the
                                                                         desired results.
General
Results
                                            It is conceivable that BEVs and PHEVs (and less likely FCEVS)
                                            will be a significant part of the 2020-2025 vehicle fleet. That they
                                            are excluded from the model is a deficiency.
                                                                         GHG reductions for PHEVs are calculated by
                                                                         applying a utility factor (percentage of BEV) to
                                                                         the results of this study for the appropriate hybrid
                                                                         vehicle.
General
Completeness
                                            The selection of drivetrain technologies (other than the electric
                                            storage technologies) is comprehensive. The qualitative
                                            description of the drivetrain technologies is complete and clear,
                                            but quantitative performance data are missing. Transparency in
                                            the actual performance data is entirely lacking. This includes
                                            engine performance maps, shift strategies, battery management
                                            in hybrids, and more. That much of that data is proprietary to the
                                            companies that generated it and/or to Ricardo is a problem for
                                            what is proposed as a regulatory tool.
                                                                         Use of proprietary data was a ground rule of the
                                                                         study. However, in the final report, we have
                                                                         added a great deal of detail using publically
                                                                         available references and sources to provide
                                                                         further understanding of these issues and how
                                                                         the study addressed them.
General
Completeness
                                            The assumptions are difficult to extract from the text.
                                                                         Use of proprietary data was a ground rule of the
                                                                         study. However, in the final report, we have
                                                                         added a great deal of detail using publically
                                                                         available references and sources to provide
                                                                         further understanding of these issues and how
                                                                         the study addressed them.
General
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                T
                 Specific
e Question     Assump
Comment
Recommendations
                                          The failure to model the drivetrain-weight interactions is a major
                                          shortcoming. Appendix 2 should clearly state that vehicle weights
                                          are held constant (assuming that I am correct in that assumption).
                                                                       The mass of technologies was not included in
                                                                       this study due to the evolving nature and
                                                                       complex opinions regarding this topic. The user
                                                                       of the RSM tool is responsible to add or remove
                                                                       mass from the baseline vehicle to obtain the
                                                                       desired results.
                                             General
Recommendations
                               11
            Summarizing assumptions in tabular form would be a great
            assistance to the reader.
The final report includes a number of expanded
tables and graphics to address this concern.
General
Other Comments
                               15
           The report is intended to provide administrators, product planners
           and legislators a practical tool for assessing what is achievable,
           as well as insight into the complexity of the path forward to reach
           those advances that will be useful for productive discussions
           between EPA and the manufacturers. This path forward involves
           trade-offs among many design choices involving available, and
           soon-to-be-available advances in engine technologies,
           hybridization, transmissions and accessories. The current version
           of the simulation effort seems reasonably balanced in the
           attention paid to each of these areas. The range of improvements
           shown in the technologies considered and examples is
           encouraging.
EPA and Ricardo acknowledge and appreciate
the reviewer's comments.
General
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                 Specific
e Question     Assump
Other Comments
Comment
                                16
            Overall, the project attempts to undertake an analytical technology
            assessment study of significant scope. It does a fairly competent
            job at analyzing a select number of technologies and packages,
            mostly aimed at improving the gasoline 1C engine, and to a less
            extent the diesel engine. It complements improvements on the
            engine side with  synergistic developments on the transmissions,
            hybrids and accessories. The main shortcoming of the study is
            that the methodology relies extensively on proprietary and
            undisclosed data, as well as empirical rules, correlations and
            modifiers without citing published reference sources. Beyond the
            perceived lack of transparency, keeping up with new technologies
            or approaches will necessarily involve new versions of the
            program since the actual models of the technologies used are
            proprietary and the choice and range of parameters available to
            users is fixed and to some extent hidden.  Due to these
            constraints, the simulation tool is limited in its ability to provide
            fundamental insight; this will require a more basic thermodynamic
            approach, perhaps best  carried out by universities.
The technology selections and combinations
were selected to provide a representative group
of combinations that reflect the thinking of the
program team of some of the most common
expected combinations across the range of light
duty classifications. The full slate of options
considered is set forth in Attachment A to the
final report. In addition, while the use of
proprietary data was a fundamental element  of
the study design, Ricardo has added significant
details and graphics, including a number of
publically available reference materials, to
increase the  transparency and overall utility of
the final report. While EPA agrees that additional
combinations are of interest, the project scope
was a significant undertaking, both in terms of
budget and time, with the options selected. The
report is one of the technical studies relevant to
EPA's ongoing rulemaking efforts, and the scope
was designed to support that effort.  EPA
anticipates that others and perhaps EPA will
continue to explore these issues with further
studies that add scope.
General
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                 Specific
e Question     Assump
Comment
Other Comments
                                18
            The report is lengthy at places, for instance in the description of
            technologies which users of the simulation software are likely to
            be already familiar with, while too laconic at other places, e.g. how
            the selected technologies were modeled in some detail. The draft
            can benefit from better balancing of its sections. There should
            also be more words summarizing the illustrative results (e.g.,
            provide ranges of benefits), and assessing them critically (e.g.,
            which technologies seem to incrementally or additively contribute
            the most), rather than just stating that the results are in Table 7.1
            or in Appendix 3. A discussion of uncertainties present in the
            analysis should be presented so as to enable the reader to place
            the findings into proper perspective.
The final report addresses some of these
comments by adding discussion and examples to
some of the modeling-focused sections.
However, the results are presented as they were
found, without significant discussion of
uncertainty or critical assessment. That was the
study objective for EPA and the Agency believes
that the final report satisfies that objective.
General
Inputs and
Parameters
                                20
            The report describes a comprehensive set of engine and vehicle
            technologies for the prediction of GHG emissions and
            performance. However, the full range of inputs and parameters is
            not explicitly presented. It requires the reader to refer to the Data
            Visualization Tool figures to simulation environment, it is
            impossible to extract details on, or judge the basis for a number of
            critical inputs. In some occasions, the report mentions that
            published data have been used, but there are no references to the
            source. Baseline engine maps, torque converter maps and
            shifting maps, electric machine efficiency maps, and control
            strategies for hybrids, which have very direct effects on vehicle
            performance and emissions, should be presented in the report, at
            least in a limited format.
To address this concern, the final report uses
public fueling maps concepts, and then illustrates
the technical transformation of baseline
technologies to the future. See especially revised
Sections 4.1 and revised Section 4.2. New
Section 4.2.6 provides case studies for EGR Dl
Turbo and Atkinson engines.  The hybrid
sections (especially section 6.8) are significantly
expanded as well.
General
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                T
                 Specific
e Question     Assump
                  Topic
Comment
Inputs and
Parameters
                               27
            Alternative fuels are currently a key research topic and very
            important for future energy independence. Because usage of
            these fuels can have an impact on efficiency and emissions, the
            study would be enhanced if engine performance maps with
            various fuels were included.
The technology selections and combinations
were selected to provide a representative group
of combinations that reflect the thinking of the
program team of some of the most common
expected combinations across the range of light
duty classifications. This includes the fuel use.
The full slate of options considered is set forth in
Attachment A to the final report. While EPA
agrees that additional combinations are of
interest,  the project scope was a significant
undertaking, both in terms of budget and time,
with the options selected. The report is one of
the technical studies relevant to EPA's ongoing
rulemaking efforts, and the scope was designed
to support that effort.  EPA anticipates that
others and perhaps EPA will continue to explore
these issues with further studies that add  scope.
General
Simulation
methodology
                               28
            The RSM approach is certainly a good way to provide quick
            access to wide range of results, but it has the limitation that a
            large number of assumptions have to be made ahead of time in
            order to determine the design space. Also, creating these
            encompassing RSM's requires a significant amount of
            simulations, and all the results will not necessarily be of interest. If
            a more flexible model/simulation was created and coupled to a
            user-friendly interface, users might be able to obtain and analyze
            the desired results instead of being constrained by the design
            space previously determined.
The RSM approach was a foundational aspect of
this study. While the reviewer's option may
provide another valuable approach, no specific
report or study change is needed in response to
this comment.
General
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                 T
                 Specific
e Question     Assump
                  Topic
Comment
Simulation
methodology
                               29
            Even though the authors attempt to describe the simulation
            methodology and assumptions in the report, it lacks details of the
            models employed, which makes it hard to determine if
            refinements need to be made, or even if more appropriate
            models/methods should be used. It is understandable that, due to
            the proprietary data, it is not possible to present everything.
            However, without any of this information, the RSM results are
            more difficult to interpret.
To address this concern, the final report uses
public fueling maps concepts,  and then illustrates
the technical transformation of baseline
technologies to the future. See especially revised
Sections 4.1 and revised Section 4.2. New
Section 4.2.6 provides case studies for EGR Dl
Turbo and Atkinson engines.  The hybrid
sections (especially section 6.8) are significantly
expanded as well.
General
Results
                               45
            It would be desirable to include a complete test case with the
            appropriate inputs, analysis and outputs as part of the report. The
            sample results presented in figures seem to have been included
            to indicate the RSM and Data Visualization Tool's capabilities, but
            they do not provide a complete picture from which to draw solid
            conclusions.
The new user manual for the RSM tool<
present a complete test case.
General
Completeness
                               47
            Some of the aspects lacking form the report have already been
            mentioned and discussed in the relevant sections.
EPA and Ricardo appreciate the comment; no
further response is required.
General
Completeness
                               48
            In general, the report provides a fair description of the modeling
            process. Unfortunately, there are no equations, plots or maps
            showing any specific modeling item, thus making this part of the
            report vague.
The final report adds detail to both the
technology discussions and the modeling
discussions to better articulate the scope and
approach of the study.
General
Completeness
                               49
            It might be possible to shorten the descriptions related to the
            individual technologies implemented and their improvements and
            add more details on how they have been modeled. People using
            this tool will most likely not use the brief descriptions of the
            various technologies to draw conclusions and make decisions.
The final report adds detail to both the
technology discussions and the modeling
discussions to better articulate the scope and
approach of the study.
General
Recommendations
                               51
            Various suggestions have already been included in the relevant
            sections.
EPA and Ricardo appreciate the comment; no
further response is required.
General
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                T
                 Specific
e Question     Assump
Recommendations
Comment
                               52
           The authors should expand the modeling sections. In particular,
           they should cite literature references (where possible) and provide
           more detail when empirical data, modifiers, or scaling laws are
           used.
The final report adopts many of these
suggestions.
General
Recommendations
                               53
            Flexibility should be added to the models. Some engine
            technologies, such as variable cam phasing, HCCI and alternative
            fuels should be considered.
EPA and Ricardo appreciate the comment.
Future analyses could expand the scope to
include these technologies. VCT and HCCI were
incorporated in the previous study.
General
Recommendations
                               54
           A self-contained study should be presented as a test case for the
           results so that specific conclusions can be drawn and the utility of
           the approach more easily understood.
The new user manual for the RSM tool<
present a complete test case.
General
Inputs and
Parameters
                               72
            How were baseline BFSC maps modified? Was it across the
            board improvement or were improvements only attributed to
            certain parts of the map?
Baseline BSFC maps were never modified.
General
Simulation
methodology
                               78
            Some assessment of the model uncertainty would be helpful.
            This could be a qualitative rating assigned by the advisory
            committee or a more rigorous method could be used.
For future consideration in any follow-up work
General
Simulation
methodology
                               79
            More detail on the types of models is required.  Do some models
            use first principals of physics and others lumped parameter?
Has be addressed with inclusion of additional
EASY5 model description/citations in report
General
Simulation
methodology
                               80
           ANOVA or some other analytical approach to consider technology
           interactions needs to be deployed.
For future consideration in any follow-up work
General
Simulation
methodology
                               81
            It says a statistical analysis was used to correlate variations in the
            input factors to variations in the output factors. This is
            ambiguous. What analysis method was used? Where is it
            reported? I didn't see anything in the results about this.  It was
            used to generate the RSM, but what was the measure of fitment?
            How did the  RSM fit compare from vehicle config to vehicle
            config.
Has be addressed with revisions to Section 3.4
of report
General
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                T
                 Specific
e Question     Assump
Comment
Completeness
                               148
           When it comes to GHG reductions why weren't plug-in hybrids
           considered?
GHG reductions for PHEVs are calculated by
applying a utility factor (percentage of BEV) to
the results of this study for the appropriate hybrid
vehicle.
General
Recommendations
                               149
            Instead of using proprietary Ricardo data/models/control
            algorithms citable data should be used.
Use of proprietary data was a ground rule of the
study. However, in the final report, we have
added a great deal of detail using publically
available references and sources to provide
further understanding of these issues and how
the study addressed them.
General
Recommendations
                               150
           Without stating how this model is going to be used in the
           regulatory decision making process, it is very difficult to assess its
           appropriateness.
The following EPA documentation in support of
the 2017-2025 rule is relevant to responding to
this comment: Chapter 3 of the Joint Technical
Support Document, and Chapter 2 of the EPA's
Regulatory Impact Analysis.
General
Recommendations
                               152
           Guidelines for appropriate use should be given.
The new user manual for the RSM tool will
present instructions for use and a complete test
                                                                                                           case.
General
Recommendations
                               155
            In terms of acceptable use: rather that trying to use the model to
            assess the boundaries of the envelope (or which technology is
            better), the tool could be used to find the areas of maximum
            overlap. In other words, knowing that the same performance and
            fuel economy is achievable using different technologies lends
            more confidence that the result is achievable. Theoretically this
            number could be a calculated value generated from the RSM's.
EPA and Ricardo appreciate the comment; no
response needed.
General
Recommendations
                               156
            Recommend allowing "real world" drive cycles to assess the
            robustness of the results. Could be a user generated result from a
            composite of the data sets already generated.
EPA and Ricardo appreciate the comment; no
response needed.
General
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                 Specific
e Question     Assump
Comment
Recommendations
                               157
            Should define the process for data selection... .eventually you'll be
            asked by a manufacturer, 'how do we get 'x' technology included
            for consideration in the study.
                                                           EPA and Ricardo appreciate the comment; no
                                                           response needed.
                                             General
Other Comments
                               159
            Having conducted a similar effort for USCAR on the PNGV
            program, I understand that considerable effort is required to
            develop such a model. I don't want to diminish all the hard work
            that was done, by only offering criticism in the above sections.  It
            appears that the intent of the approach to this activity is in the
            right place, just better documentation is needed and appropriate
            use guidelines.
                                                           EPA and Ricardo appreciate the comment; no
                                                           further response is required.
                                             General
Inputs and
Parameters
             Baseline vehicle
             subsystem
             models/maps
161
The models/maps for the subsystems used in these vehicle
models were not provided in the report so that their adequacy
could not be assessed.
Use of proprietary data was a ground rule of the
study. However, in the final report, we have
added a great deal of detail using publically
available references and sources to provide
further understanding of these issues and how
the study addressed them. Also,  on specific
maps relevant to the engine model, we note that
the effects of the valve actuation  system, fueling
system, and boost system were integrated into
the final torque curves and fueling maps,
therefore subsystem performance maps, such as
turbine and compressor efficiency maps, are not
relevant to this study.
General
Inputs and
Parameters
             Baseline vehicle
             subsystem
             models/maps
162
Including these baseline models in the report would assist in
assessing the development process as well as the adequacy of
the new technology subsystem models/maps, which was not
possible in this peer review.
See response to Comment Excerpt 161.
General
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                 Specific
e Question     Assump
Comment
Inputs and
Parameters
             Engine
             technology
             selection
169
Issue: The technology "package definitions" precluded an
examination of the individual effects of a variety of technologies
such as a single stage turbocharger vs. series-sequential
turbochargers.
EPA and Ricardo acknowledge this limitation.
As with any study, there is a need to balance the
ability to evaluate each variable, with the ability
to contain the study to a manageable scope.
Ricardo subject matter experts determined the
type of turbochargers used in the study.
General
Inputs and
Parameters
                               181
            None of the subsystem models/maps were provided for review so
            comments on their adequacy are not possible.
                                                            See response to Comment Excerpt 161.
                                             General
Inputs and
Parameters
                               182
            Issue:  Insufficient reasons are presented to justify why the
            models/maps for subsystems are not provided in the report,
            especially when one of the goals of the report was to provide
            transparency (per Jeff Cherry, May 5, 2011 teleconference and
            Item 5, below).
                                                            See response to Comment Excerpt 161.
                                             General
Inputs and
Parameters
                               184
            Recommendation: To establish the adequacy of the subsystem
            models/maps, derivation details should be provided.
                                                            See response to Comment Excerpt 161.
                                             General
Simulation
methodology
                               198
            Concern:  Methodologies used in simulating the subsystems and
            the overall vehicles were not provided, so that the validity and
            applicability of these methodologies cannot be assessed.
                                                            See response to Comment Excerpt 161.
                                             General
Simulation
methodology
              Major
             deficiencies in the
             report
200
Technical descriptions of how the subsystems and vehicle
models/maps for the baseline vehicles were developed were not
provided.
See response to Comment Excerpt 161.
General
Simulation
methodology
              Major
             deficiencies in the
             report
201
Most importantly, only non-technical descriptions of how each of
the advanced technology subsystem models/maps was
developed were provided.
See response to Comment Excerpt 161.
General
Simulation
methodology
              Major
             deficiencies in the
             report
203
Descriptions of how synergistic effects were handled were not
provided.
Synergistic effects are inherent to the proprietary
Ricardo vehicle models.
General
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                 Specific
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Topic
Comment
Results
             Overview of
             results
211
The results from this work could be useful in evaluating possible
GHG emission reductions in the 2020-2025 timeframe if the
issues throughout this peer review were addressed and the
recommendations in Item 5 (below) were implemented.  However,
even if the foregoing deficiencies were resolved, the foregoing
caveat that there are numerous technologies that have potential
for reduced GHG emissions that were not included in this study
must be recognized (see Item 1B, above).
EPA believes that the overall revisions in the
final report address the core concerns raised by
the reviewers during the peer review. EPA
agrees that other technologies could also reduce
GHG emissions (see the full set of technologies
considered in Attachment A to the final report),
but also must develop study boundaries that
enable a report such as this one to focus on
specific options within the confines of a cost-
effective study design.
General
Results
             Sample runs of
             CSM
212
In the review process, several sample runs of the Complex
Systems Model (CSM) for the Standard Car (Toyota Camry) were
made and the results are shown in the attached chart (at the end
of this peer review) and summarized below: Baseline engine with
AT6-2010 to Stoichiometric Dl Turbo, Stop-Start, AT8-2020
-   38.7% improvement in M-H mpg
-   Lumsden et al. (2009) identified a 25-30% improvement in
   mpg for a 50% downsized, Dl, Turbo engine.
-   The remaining 9-14% potentially could be explained by stop-
   start and the change from AT6-2010 to AT8-2020 (although
   the details of the systems and the models used would be
   needed to make this assessment).
Baseline engines cannot be combined with
advanced technologies in the RSM tool; the RSM
tool has been modified to prevent this issue.
General
Results
             Sample runs of
             CSM
213
In the review process, several sample runs of the Complex
Systems Model (CSM) for the Standard Car (Toyota Camry) were
made and the results are shown in the attached chart (at the end
of this peer review) and summarized below: AT8-2020 to DCT
-   3.3% improvement in M-H mpg
-   This improvement appears reasonable.
EPA and Ricardo appreciate the comment; no
further response is required.
General
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                 Specific
,e Question     Assump
Topic
Comment
Results
             Sample runs of
             CSM
214
In the review process, several sample runs of the Complex
Systems Model (CSM) for the Standard Car (Toyota Camry) were
made and the results are shown in the attached chart (at the end
of this peer review) and summarized below: Stoichiometric Dl
Turbo with Stop-Start to P2 Hybrid
-   18.2% improvement in M-H mpg
-   This improvement appears reasonable.
EPA and Ricardo appreciate the comment; no
further response is required.
General
Results
             Issue with CSM
219
Some examples where the model did not allow a buildup of
comparison cases are:
-   Baseline engine with AT-2010 to AT-2020 to DCT
-   Baseline engine without stop-start to with/stop-start
Baseline engines cannot be combined with
advanced technologies in the RSM tool; the RSM
tool has been modified to prevent this issue.
General
Results
             Other issues
222
When the baseline cases were run in the Complex Systems
Model, incorrect values of displacement and architecture were
shown in the output.
-   As an example shown on the attached chart (copied from the
   output of the CSM), the baseline for the Standard Car with a
   2.4L engine shows a displacement of 1.04L.
-   For the same example, the architecture is shown as
   "conventional SS", whereas the baseline was understood to
   not have the stop-start feature (page 22, Table 5-2).
Baseline engines cannot be combined with
advanced technologies in the RSM tool; the RSM
tool has been modified to prevent this issue.
General
Completeness
                               224
           An overall schematic and description of the powertrain and
           vehicle models and the associated subsystem models/maps were
           not provided.  Only vague descriptions were included in the text of
           the report.
                                                          See Figure 6.1 in the final report, as well as the
                                                          numerous changes made to provide further detail
                                                          on these types of issues throughout the report.
                                            General
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                 Specific
e Question    Assump
                  Topic
Comment
Completeness
                              225
           Technical descriptions of how the subsystems and vehicle
           models/maps for the baseline vehicles were developed were not
           provided.
                                                          Use of proprietary data was a ground rule of the
                                                          study. However, in the final report, we have
                                                          added a great deal of detail using publically
                                                          available references and sources to provide
                                                          further understanding of the modeling and
                                                          related issues, and how the study addressed
                                                          them.
                                            General
Completeness
                              226
           None of the overall or subsystem models/maps were provided for
           review so comments on their adequacy are not possible.
                                                          See response to Comment Excerpt 225.
                                            General
Completeness
                              227
           Most importantly, only minimal descriptions were provided of how
           each of the advanced technology subsystem models/maps was
           developed.
                                                          See response to Comment Excerpt 225.
                                            General
Completeness
                              228
           Descriptions of the algorithms used for engine control,
           transmission control, hybrid system control, and accessory control
           were not provided.
                                                          See response to Comment Excerpt 225.
                                            General
Completeness
                              229
           Descriptions of how synergistic effects were handled were not
           provided.
                                                          The synergistic effects are inherent in the
                                                          Ricardo proprietary vehicle models.
                                            General
Recommendations
                              231
           This report needs major enhancements to reach the stated goal of
           being open and transparent in the assumptions made and the
           methods of simulation. Recommendations to rectify the
           deficiencies in these areas are provided in the previous four
           items.
                                                          See response to Comment Excerpt 225.
                                            General
Recommendations
             Overall
             recommendations
232
Overall Recommendation: Provide all vehicle and powertrain
models/maps and subsystem models/maps used in the analysis in
the report so that they can be critically reviewed.
See response to Comment Excerpt 161.
General
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                 Specific
e Question     Assump
                  Topic
Comment
Recommendations
             Overall
             recommendations
233
Overall Recommendation:  Expand the technology "package
definitions" to enable evaluation of the individual effects of a
variety of technologies.
The technology selections and combinations
were selected to provide a representative group
of combinations that reflect the thinking of the
program team of some of the most common
expected combinations across the range of light
duty classifications.  The full slate of options
considered is set forth in Attachment A to the
final report. In addition, while the use of
proprietary data was a fundamental element of
the study design, Ricardo has added significant
details and graphics, including a number of
publically available reference materials, to
increase the transparency and overall utility of
the final report. While EPA agrees that additional
combinations are of interest, the project scope
was a significant undertaking, both in terms of
budget and time, with the options selected. The
report is one of the technical studies relevant to
EPA's ongoing rulemaking efforts, and the scope
was designed to support that effort. EPA
anticipates that others and perhaps EPA will
continue to explore these issues with further
studies that add scope.
General
Recommendations
             Specific
             recommendations
             for improvements
235
Provide technical descriptions of how the subsystems and vehicle
models/maps for the baseline vehicles were developed.
See response to Comment Excerpt 225.
General
Recommendations
             Specific
             recommendations
             for improvements
236
 Provide overall system and subsystem models/maps in the
report.
See response to Comment Excerpt 225.
General
Recommendations
             Specific
             recommendations
             for improvements
237
Provide detailed technical descriptions of how each of the
advanced technology subsystem models/maps was developed.
See response to Comment Excerpt 225.
General
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                 Specific
e Question    Assump
Comment
Recommendations
             Specific
             recommendations
             for improvements
239
Provide detailed descriptions of how synergistic effects were
handled.
This is inherent to Ricardo's proprietary vehicle
models.
General
Recommendations
                              243
           Recommendation: Subsystem models/map should be added to
           this report and another peer review conducted to assess their
           adequacy before this report is released.
                                                           See response to Comment Excerpt 225.
                                            General
Other Comments
                              248
           The vehicle model and powertrain model were developed and
           implemented by Ricardo in the MSC.EasyS software package.
           The model reacts to driver input to provide the torque levels and
           wheel speeds required to drive a specified vehicle over specified
           driving cycles.  The overall model consists of subsystem models
           that determine key component outputs such as torque, speeds,
           heat rejection, and efficiencies.  Subsystem models are expected
           to be required for the engine, accessories, transmission, hybrid
           system (if included), final drive, tires and vehicle, although the
           report did not clearly specify the individual subsystem models
           used.
                                                           See response to Comment Excerpt 225.
                                            General
Other Comments
                              249
           A design of experiments (DOE) matrix was constructed and the
           vehicle models were used to generate selected performance, fuel
           economy and GHG emission results over the design space of the
           DOE matrix.  Response surface modeling (RSM) was generated
           in the form of neural networks. The output from each model
           simulation run was used to develop the main output factors used
           in the fit of the RSM.  The resulting Complex Systems Model
           (CSM) provides a useful tool for viewing the results from this
           analysis that included over 350,000 individual vehicle simulation
           cases.
                                                           EPA and Ricardo acknowledge and appreciate
                                                           the reviewer's comments.
                                            General
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                 Specific
e Question     Assump
                  Topic
Comment
Other Comments
                               250
           The vehicle and powertrain models/maps and subsystem
           models/maps used in the analysis were not provided in the report
           and could not be reviewed.  In most cases, the report stated that
           the models/maps were either proprietary to Ricardo or at least
           elements were proprietary so that they could not be provided for
           review.  Without having these models/maps and subsystem
           models/maps, their adequacy and suitability cannot be assessed.
                                                           See response to Comment Excerpt 225.
                                             General
Other Comments
                               251
           Overall Recommendation:  Provide all vehicle and powertrain
           models/maps and subsystem models/maps used in the analysis in
           the report so that they can be critically reviewed.
                                                           See response to Comment Excerpt 225.
                                             General
Other Comments
                               252
           The technology "package definitions" preclude an examination of
           the individual effects of a variety of technologies. For example,
           for the Stoichiometric Dl Turbo engine, only the version with a
           series-sequential turbocharger could be evaluated whereas a
           lower cost alternative with a single turbocharger could not be
           evaluated. Likewise, only the AT8-2020 transmission could be
           evaluated with the Stoichiometric Dl  Turbo engine, while the
           substitution of the AT6-2010, as a lower cost alternative, could not
           be evaluated.
                                                           See response to Comment Excerpt 233.
                                             General
Other Comments
                               253
           Overall Recommendation:  Expand the technology "package
           definitions" to enable evaluation of the individual effects of a
           variety of technologies.
                                                           See response to Comment Excerpt 252.
                                             General
Other Comments
                               291
           Sample Output From Complex System Model (CSM)
           5/4/2011
           Relative Percentage Differences Were Added by W. R. Wade
           (see Exhibit 9)
                                                           EPA and Ricardo acknowledge and appreciate
                                                           the reviewer's comments.
                                             General
References Used
             References
             (Used for this
             Review that are
             also listed in the
             Report)
293
Reference that summarizes the 2008 study by Perrin Quarles
Associates (PQA) that provided the 2010 baseline cases for five
LDV classes (Page 30 of the report):
4.  PQA and Ricardo (2008), "A Study of Potential Effectiveness
   of Carbon Dioxide Reducing Vehicle Technologies"
EPA and Ricardo acknowledge and appreciate
the reviewer's comments.
General
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                 T
                 Specific
e Question     Assump
                  Topic
Comment
Executive
Summary
                                295
            For the purpose of describing the modeling approach used in the
            forecasting of the performance of future technologies, the report
            reviewed is inadequate.  In virtually every area, the report lacks
            sufficient information to answer the charge questions provided for
            the reviewer. It is entirely possible that the approach used is
            satisfactory for the intended purpose.  However, given the
            information provided for the review, it is not possible for this
            reviewer to make any statement  regarding the suitability of this
            approach.
See response to Comment Excerpt 225.
General
Inputs and
Parameters
                                296
            From a high level, it is clear what the inputs to the design space
            tool are, which are listed in tables 8.1 and 8.2. At the next level
            down (i.e. the vehicle and subsystem models) there is no
            comprehensive handling of inputs in parameters in the report.
            Some models are partially fleshed out in this area but most are
            lacking. By way of example, the engine models are described as
            maps which are "defined by their torque curve, fueling map, and
            other input parameters" where "other input parameters" are never
            defined.
See response to Comment Excerpt 225.
General
Results
                                298
            The third charge questions deals with the validity and the
            applicability of the resulting prediction. The difficulty in this task is
            that it is an extrapolation from present technology that uses an
            extrapolation method (i.e. the model) and a set of inputs to the
            model (i.e. future powertrain data.) Since it is not possible to
            validate the results against vehicles and technology that do not
            exist, one can only ensure that the model and the model inputs
            are appropriate for the task. Because of the lack of transparency
            in the model and inputs it is difficult to make any claims regarding
            the results. In trying to validate results, one example is cited in
            the body of the report that shows the baseline engine getting
            superior HWFET and US06 fuel economy than all of the other
            non-HEV powertrains with other factors being the same - this
            leaves some  skepticism regarding the results.
The advanced turbo engines, when heavily
downsized, operates outside of the most
optimum range on the more demanding drive
cycles (such as the US06). Likewise, naturally
aspirated engines tend to have their best
efficiency at high load conditions (cf. Figure 4.10)
General
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                 Specific
e Question     Assump
Comment
Recommendations
                               300
            Given the low level of detail given in the report, it does seem that
            the strategy used is consistent with the goal of the work and what
            others in the field are doing.  That being said, the  report is
            inadequate in nearly every respect at documenting model inputs,
            model parameters, modeling methodology, and the sources and
            techniques used to develop the technology performance data.
            Given the need for transparency in this effort, this reviewer feels
            that the detail in the report is wholly inadequate to document the
            process used.  The organization responsible for the modeling has
            expertise in this area it is certainly possible that the methodology
            is sound, however, given just the information in the report there is
            simply no way for an external reviewer to make this conclusion.
                                                            See response to Comment Excerpt 225.
                                             General
Recommendations
                               301
            Because of the lack of hard information to answer the charge
            questions, this peer review evolved mainly into a suggested list of
            details that should be brought forward in order to allow the charge
            questions to be answered properly. With this information, it is
            hoped that a person with expertise in the appropriate areas will be
            able comment on the work more fully.
                                                            See response to Comment Excerpt 225.
                                             General
Recommendations
             Aftertreatment/
             Emissions
             Solutions
316
Provide better evidence that powertrain packages have credible
paths to meet emissions standards.
The modeling ground rules state that "2020-
2025 vehicles will meet future California LEV III
requirements for criteria pollutants, which are
assumed to be equivalent to current SULEVII (or
EPA Tier 2 Bin 2) levels." These parameters
were used in the proprietary Ricardo vehicle
models.
General
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                 T
                       Specific       Comment
Charge Question     Assump
Recommendations
                   Aftertreatment/
                   Emissions
                   Solutions
317
Provide evidence that fuel enrichment strategies are consistent
with emissions regulations.
The modeling ground rules state that "2020-
2025 vehicles will meet future California LEV III
requirements for criteria pollutants, which are
assumed to be equivalent to current SULEVII (or
EPA Tier 2 Bin 2) levels." These parameters
were used in the proprietary Ricardo vehicle
models. No enrichment was used in the
development of any of the boosted engines,
following data from Mahle.
General
Recommendations
                   Hybrid
                   technology
                   selection
351
Validate that other vehicle performance metrics, like emissions
and acceleration, are not adversely impacted by an algorithm that
focuses solely on fuel economy. The emission side of things will
challenge to validate with this level of model, however, some kind
of assurance should be made to these factors which are currently
not addressed at all.
The ground rules for the project state that all
simulations meet Tier 2 Bin 2 emissions.
Performance metrics were held constant for all
vehicles.
General
Simulation
methodology
                                     370
            Provide error metrics for the neural network RSMs (i.e. R2, min
            absolute error, max absolute error, error histograms, error
            standard deviation, etc.) before combining the fit and validation
            data sets.
                                                             Methodology was to fit the RSM using two-thirds
                                                             of the available data and test the RSM using the
                                                             remaining data. Fits were within acceptable limits
                                                             (3-5%).
                                              General
Simulation
methodology
                                     371
            Provide the error metrics described above for the RSMs after
            combining the fit and validation data sets.
                                                             See response to Comment Excerpt 370.
                                              General
Simulation
methodology
                                     372
            Provide validation that the data analysis tool correctly uses the
            RSM to predict results very close to the source data (i.e.
            demonstrate the GUI software behaves as expected).
                                                             The RSM fit quality is represented by the R2
                                                             values. The predicted data was checked against
                                                             the source data to ensure good predictability.
                                              General
Results
                                     373
            As outlined in the executive summary, it was not possible to
            answer the charge questions provided for this peer review due to
            lack of completeness in the report. Thus, this report was aimed at
            providing feedback on what information would be helpful to allow
            a reviewer to truly evaluate the spirit of the charge questions. With
            the above in mind, the following conclusions are made.
                                                             In the final report, we have added a great deal of
                                                             detail using publically available references and
                                                             sources to provide further understanding of these
                                                             issues and how the study addressed them.
                                              General
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                 Specific
e Question     Assump
Topic
Comment
Results
                               374
           The modeling approach describe in the report could be
           appropriate for the simulation task required and is generally
           consistent with approaches used by other groups in this field.  The
           conclusions from the report could very well be sound; however,
           there is insufficient information and validation provided in the
           report to determine if this is the case. The technique used to
           analyze the mass simulation runs could also be sound, although
           the accuracy of the response surface model is not cited  in the
           report.
See response to Comment Excerpt 373.
General
Results
                               375
           The process of arriving at the performance of the future
           technologies is not well described.
See response to Comment Excerpt 373.
General
Results
                               376
           The majority of models are only described qualitatively making it
           hard or impossible to judge the soundness of the model.
See response to Comment Excerpt 373.
General
Results
                               377
           Some of the qualitative descriptions of the models indicate that
           models do not consider some important factors.
See response to Comment Excerpt 373.
General
Results
                               378
            Because of the qualitative nature of the model descriptions, there
            is a major lack of transparency in the inputs and parameters in the
            models.
See response to Comment Excerpt 373.
General
Results
                               379
           Where precise value(s) are given for parameters in the model, the
           report generally does not cite the source of the value(s) or provide
           validation of the particular value.
See response to Comment Excerpt 373.
General
Results
                               380
           Validation of the model and sub-models is not satisfactory (It is
           acknowledged that many of these technologies do not exist, but
           the parameters and structure of the model have to be based on
           something.)
See response to Comment Excerpt 373.
General
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                T
                       Specific       Comment
Charge Question     Assump
Executive
Summary
                                     383
            The supplemental review material provided some answers to
            questions posed above, but in general, did not provide the level of
            detail necessary to ensure a thorough review of the process.  The
            conclusion of this reviewer remains similar as on the original
            review, which is that there were no serious flaws found in the
            work, however, there were enough omissions that it is not
            possible to accurately judge if the predictions made are accurate.
            The biggest concern in this work is the lack of validation and/or
            citation of where data and models are coming from. There are
            numerous maps that are presented in the follow-up material,
            however, these  maps had to have originated from some process
            (which needs documented) and should be compared against
            some kind of validation. Despite the lack of documentation
            provided, the work is generally that of a project team that is
            competent in this field of study.
                                                            See response to Comment Excerpt 373.
                                             General
Inputs and
Parameters
                   SI Engine Maps
                   and Diesel
                   Engine Maps
394
The baseline engine map data is shown in a series of figures and
references are provided for the specific vehicle that the map is for.
It is assumed that this indicates that this data has been measured
experimentally. If this is the case, then this is well documented.
EPA and Ricardo appreciate the comment; no
further response is required.
General
Inputs and
Parameters
                                     407
            Curious about why no discussion of advanced materials in
            engines to achieve improvements.
                                                            Advanced materials were considered only to the
                                                            extent that they facilitated other improvements,
                                                            such as in friction or mass. The benefits of
                                                            advanced materials were not explicitly
                                                            considered separately from other technologies.
                                             General
Inputs and
Parameters
                                     409
            Future Developments in Engine Friction -1 think it would be
            worthwhile to point out that there are technologies that are more
            driven by increased durability rather than fuel economy but they
            could play off one another. Engine friction reduction is one of
            those areas.
                                                            EPA and Ricardo acknowledge and appreciate
                                                            the reviewer's comments.
                                             General
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                T
                 Specific
e Question     Assump
Comment
Simulation
methodology
                               414
            EHVA: The paper addresses the potential of the technology
            nicely. Since it was published in 2003 has any more recent work
            been done to address the durability and issues brought up in the
            conclusions?
Durability is beyond the scope of this study.
General
Results
                               417
            After reading the papers and presentations I come to the
            assumption that the papers were used to guide the selection of
            technology, but it's not clear which maps were generated from
            model and which maps were generated in the test cell. It's
            evident that there is a heavy concentration on engine technology
            and the fidelity of the engine models, which is appropriate. I  have
            a slight concern about the impression I'm left with; that there is not
            much attention to the interaction of systems effects. This is most
            likely because of cost and availability of data.  I would like to  see
            the EPA articulate a process for looking at system interactions,
            continuous improvement and model compatibility.  For example  if
            the study were to run over several years the researches should
            feel confident comparing a result generated with the models in
            2013 to modeling results generated today.
All of the advanced engine maps used in the
models were generated using Ricardo
experience with engine design and engine
dynamometer test results from experimental
engines and are meant to represent a specific
engine calibration. The engine maps contain fuel
mass flow rates based on engine speed and
load. Any vehicle system or interactions of
several systems that would reduce the
powertrain work required are accounted for in the
models by operating the engine at the reduced
speed or load.
General
Completeness
                               418
            Hybrid: Ricardo asserts that electric machine design activities of
            the future will most like concentrate around cost reductions;
            however I see machine efficiency dropping in order to meet cost
            reductions. Therefore I think it premature to assume that
            efficiency will stay the same and cost will drop.
Please refer to EPA's 2017-2025 rule (Chapter 3
of the joint TSD) to reference how electric
component efficiency and costs are handled by
the agencies.
General
Inputs and
Parameters
                               419
            Ricardo, Action Item Response, 16 Feb 10,15 p. (proprietary): A
            response to an EPA inquiry, this document deals with engine
            maps, engine map comparisons, engine map plots, transmissions,
            batteries, motor and generator efficiency maps.
            Comment: Ricardo responses and data selection seem
            reasonable.
EPA and Ricardo appreciate the comment; no
response needed.
General
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                Specific
e Question    Assump
Comment
Inputs and
Parameters
                              420
           Ricardo, Baseline Camry with Alternator Regen and Shift
           Optimizer Development of Optimized Shifting Strategy Light Duty
           Vehicle Complex Systems Simulation EPA Contract No. EP-W-
           07-064, work assignment 2-2,15 Apr 10,10 p. (proprietary): This
           document provides data on effectiveness of shift optimizer,
           including alternator regen, over the FTP and HWFET.
           Comment: Seems reasonable, improvements are greater on FTP
           than HWFET.
EPA and Ricardo appreciate the comment; no
response needed.
General
Recommendations
                              423
           Ricardo, BSFC Map Commparisons, LBDI vs EGR Boost & DVA
           for STDI, OBDI, & EGR Boost, Light Duty Vehicle Complex
           Systems Simulation, EPA Contract No. EP-W=07=064, work
           assignment 2-2, 24 Feb 10, 20 p. (proprietary) Comparison of
           engine technologies in terms of maps of percent difference in bsfc
           in bmep vs rpm space allows visualization Comment: Straight
           forward data analysis, presumably as requested by USEPA.
           Should aid in understanding technology performance differences.
EPA and Ricardo appreciate the comment; no
response needed.
General
Inputs and
Parameters
                              424
           Mischker, K. and Denger, D., Requirements of a Fully Variable
           Valvetrain and implementation using the Electro-Hydraulic Valve
           Control System EHVS, 24th International Vienna Engine
           Symposium 2003,17 p. This paper describes an electro-hydraulic
           valve system (EVHS) and limited data on reduction in bsfc.
           Comment: This would seem to be of limited quantitative value
           since technology is well advanced beyond 2003.
EPA and Ricardo appreciate the comment; no
response needed. Background materials
included both highly relevant data and sources
as well as some general information sources
used during the course of the study. Not all
sources reviewed were of critical importance to
the study.
General
Recommendations
                              426
           Ricardo, Response to EPA Questions on the Diesel Engine Fuel
           Maps, Supplemental Graphs for Word Document, 16 Feb 10,11
           p. (proprietary) Document presents proposed diesel engine maps
           for MY2020+ vehicles.
           Comment: Anticipated technologies are listed but how the maps
           were generated is not described. Maps seem reasonable.
EPA and Ricardo appreciate the comment; no
response needed.
General
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                 Specific
e Question     Assump
Comment
Completeness
                               427
            Ricardo, Assessment of Technology Options, Technologies
            related to Diesel Engines, 23 Nov 09,17 p. Overview predicts
            continuation of low uptake in the U.S. IDA and LOT markets.
            Review deals with various engine technologies to improve
            efficiency. Individual improvements <1-5%. Most promising is
            electric turbo-compounding (bottoming cycle to recover exhaust
            thermal energy to produce electricity).
            Comment: Individual technology assessments seem reasonable.
            There is no analysis of integrating several technologies.
EPA and Ricardo appreciate the comment; no
response needed.
General
Inputs and
Parameters
                               428
            Ricardo, EBDI Project Overview, Ethanol Boosted Direct Injection,
            Nov 09, 8 p. This study examines ethanol boosted direct injection
            (EBDI) to optimize engine operation of E85 fuel. Possibility exists
            to match or exceed diesel performance and reduce C02
            emissions.
            Comment: It is not clear if comparison of EBDI and diesel is a
            equal technology level.
See response to Comment Excerpt 424.
General
Inputs and
Parameters
                               430
            UOM, HiTor®forelecgtric, hybrid electric, and fuel cell powered
            vehicles, 18 Aug 09, based on test data map, 5 p. Describes
            power electronics for motor generator control, including an
            efficiency map for combined controller and motor based on test
            data.
            Comment: Efficiency maps seem reasonable.
EPA and Ricardo appreciate the comment.
General
Recommendations
                               431
           Odvarka, E., et al., Electgric motor-generator for a hybrid electric
           vehicle, Engineering Mechanics, 16,131-139, 2009, 9 p.
           Describes electrical machine options of hybrid electric vehicles.
           Includes efficiency maps for four technologies.
           Comment: Data are of general interest, but date from 2003.
See response to Comment Excerpt 424.
General
Inputs and
Parameters
                               432
            UOM, PowerPhase®75 for electric, hybrid electric, and fuel cell
            powered vehicles, not dated, 6 p. Described power electronics of
            vehicle electric power. Comment: Similar to earlier brochure on
            power electronics, including efficiency map.
See response to Comment Excerpt 424.
General
                                                                               100

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                                                 Table 1: Response to Individual Peer Review Comments
                T
                 Specific
e Question    Assump
Comment
Completeness
                               433
           Ricardo, Future Engine Friction Assessment—Response to Action
           Item Question SI Engine #4,18 Feb 11, 4 p. (proprietary) Projects
           continued reduction in engine friction, 2010-2020.
           Comment: Data provide confirm projection.
EPA and Ricardo appreciate the comment; no
response needed.
General
Completeness
                               434
           Ricardo, Revised Follow-up Answers to 8 April 2010 Meeting
           with EPA and Ricardo, 19 Apr 10, 8 p. (proprietary) Presents
           fueling maps for several technologies.
           Comment: Adds to documentation of engine map data.
EPA and Ricardo appreciate the comment; no
response needed.
General
Completeness
                               435
           Alger, T., Southwest Research Institute, Examples of HEDGE
           Engines, 2009, 4 p. Presents engine map for a 2.4 L 14 High-
           -Efficiency Dilute Gasoline Engine (HEDGE) engine and
           compares with TC  GDI engine, diesel engine.
           Comment: Adds to documentation of engine map data.
EPA and Ricardo appreciate the comment; no
response needed.
General
Completeness
                               436
           Ricardo, Hybrid Controls Peer Review, 18 Feb 10, 31 p.
           (proprietary)
           Review of hybrid control technologies for various architectures.
           Review of battery operation in cold weather.
           Comment: Thorough description of technologies and their
           operation characteristics. Battery discussion covers similar
           material to an earlier paper.
EPA and Ricardo appreciate the comment; no
response needed.
General
Inputs and
Parameters
                               437
           Ricardo, Hybrids Control Strategy, 6 Aug 10, 41 p. (proprietary)
           Discusses development of control strategies for P2 and Power
           Split hybrids.
           Comment: Includes efficiency maps and substantial technical
           detail including vehicle mass effect.
See response to Comment Excerpt 424.
General
Completeness
                               438
           Ricardo, Simulation Input Data Review, 4 Feb 10,14 p.
           (proprietary) Described hybrid architectures with emphasis on
           machine-inverter combine efficiencies, including efficiency maps.
           Comment: More data, seems reasonable.
EPA and Ricardo appreciate the comment; no
response needed.
General
                                                                               101

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                                                                                                                             November 29, 2011
                                                 Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question    Assump
Comment
Inputs and
Parameters
                              439
           Ricardo, Assessment of Technology Options, 18 Nov 09,14 p.
           (proprietary) Assessment of hybrid technologies using evaluation
           template.
           Comment: Treats a range of hybrid technologies, including series
           hydraulic, giving projections of C02 reduction benefits.
EPA and Ricardo appreciate the comment; no
response needed.
General
Inputs and
Parameters
                              440
           Ricardo, Simulation Input Data Review, 2 Feb 10, 30 p.
           (proprietary) Document review modeling parameters for vehicle
           performance simulations, including engine efficiency maps for a
           range of engine and transmission technologies.
           Comment: This is the kind of data that we requested. Includes
           shift strategies. Seems reasonable and well-documented.
EPA and Ricardo appreciate the comment; no
response needed.
General
Simulation
methodology
                              441
           Trapp, C., et al., Lean boost and NOx—strategies to control
           nitrogen oxide emissions, (no date), 23 p. Technical paper that
           describes lean burn direct injection (LBDI) engines, SCR NOx
           control, and more. Includes some emission control cost data.
           Comment: Not clear how this related to Ricardo's model
           development for EPA.
See response to Comment Excerpt 424.
General
Completeness
                              442
           Trapp, C., et al., NOx emission control options for the Lean Boos
           downsized gasoline engine, (2 Feb 07), 34 p. Paper compares
           lean NOx trap and selective catalytic reduction technologies.
           Includes some engine map data for NOx emissions. Includes cost
           data for aftertreatment.
           Comment: Good academic paper with useful data. Not clear what
           or how Ricardo used.
See response to Comment Excerpt 424.
General
Completeness
                              443
           Trap, C., et al., NOx emission control options for the lean boost
           downsized gasoline engine, (2 Feb 07), 27 p. Paper review
           international emissions regulation and technologies to meet.
           Comment: This paper contains some of the same information as
           the preceding two. Simulated date presented, again for SCR and
           LNT technologies.
See response to Comment Excerpt 424.
General
                                                                              102

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    Peer Review Response Document
                                                                                                                            November 29, 2011
                                                 Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question    Assump
Comment
Recommendations
                              444
           Ricardo, Lean/Stoichiometric switching load for 2020 Hybrid Boost
           Concept, (no date), 2 p. Presents space velocity and fuel maps.
           Comment: Relevance not clear.
See response to Comment Excerpt 424.
General
Recommendations
                              445
           Ricardo, Proposed Lean/Stoichiometric switching load for hybrid
           boost concept, 29 Apr 10,1 p. Identifies proposed lean zone
           operating region on engine map.
           Comment: Relevance not clear.
See response to Comment Excerpt 424.
General
Results
                              446
           Lymburner, J.A., et al., Fuel consumption and NOx Trade-offs on
           a Port-Fuel-lnjected SI Gasoline Engine Equipped with a Lean
           NOx Trap, 4 Aug 09, 20 p. This technical paper examines the
           trade-off between NOx control and C02 emissions.
           Comment: Good work but relevance not clear.
See response to Comment Excerpt 424.
General
Results
                              447
           Lotus(?), (from Kapus, P.E. etal., May 2007), Comparison to
           other downsized engines This one figure is a partial engine map
           with context vague.
           Comment: Significance is not clear.	
See response to Comment Excerpt 424.
General
Completeness
                              448
           Turner, J.W.G., et al., Sabre: a cost-effective engine technology
           combination of high efficiency, high performance and low C02
           emissions, Low Carbon Vehicles, May 09, IMechE Proceedings,
           14 p. This paper describes a technology for reducing COs
           emissions in a downsized engine. The Sabre engine is a
           collaboration between Lotus Engineering and Continental
           Automotive Systems.
           Comment: Limited performance data provided.
See response to Comment Excerpt 424.
General
Inputs and
Parameters
                              449
           Ricardo, Conventional Automatic Nominal Results, 16 Mar 10,17
           p. (proprietary) This presentation includes mileage versus 0-60
           mph time maps for a range of vehicles (light duty to large truck).
           Also presented are comparisons of fuel economy for different
           regulatory test cycles and technologies.
           Comment: Significance is not clear.
See response to Comment Excerpt 424.
General
                                                                              103

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    Peer Review Response Document
                                                                                                                             November 29, 2011
                                                 Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
                               451
           Ricardo, Revised follow-up answers for hybrid action items, 23
           Jun 10,16 p. (proprietary) This report answers questions on
           electric drive train efficiency, battery characteristics, and available
           braking energy, and more.
           Comment: Interesting data, but implication not clear.	
See response to Comment Excerpt 424.
General
Completeness
                               452
           Ricardo, Response to questions regarding the generation of the
           diesel fuel maps for fuel efficiency simulation, 16 Feb 10,10 p.
           (proprietary) Paper answers a series of EPA questions on how the
           diesel fuel maps were generated.
           Comment: This is relevant information and provides a convincing
           description of the technical basis for the diesel fuel maps.
EPA and Ricardo appreciate the comment; no
response needed.
General
Simulation
methodology
                               453
           Ricardo, Scaling Methodology Review, 19 Jan 10, 9 p. This
           document explains the scaling methodology used in the EASY5
           vehicle model.
           Comment: This description in clear and useful.
EPA and Ricardo appreciate the comment; no
response needed.
General
Completeness
                               454
           Ricardo, SCR as an Enabler for Low C02 Gasoline Applications,
           no date, 35 p. This presentation describes technology and
           implementation for exhaust NOx reduction for lean burn gasoline
           engines.
           Comment: Comprehensive discussion of technology, but if and
           how inconcorporated in the model not clear.
See response to Comment Excerpt 424.
General
Completeness
                               455
           Ricardo, Simulation Input Data Review, 18 Mar 10,17 p.
           (proprietary) This document reviews the engine maps used in the
           model. Includes are examples of the baseline maps plus
           modifications associated with a range of technologies. Data apply
           to all 7 vehicle classes.
           Comment: This is the documentation that was missing in the
           earlier review material. Looks reasonable and is reassuring.
EPA and Ricardo appreciate the comment; no
response needed.
General
                                                                               104

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    Peer Review Response Document
                                                                                                                            November 29, 2011
                                                 Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question    Assump
Comment
Other Comments
                              456
           Ricardo, Assessment of Technology Options, 19 Nov 09, 22 p.
           (confidential) This document reviews and rates a range of spark-
           ignition adaptable technologies to reduce C02 emissions.
           Biofuels are included.
           Comment: An interesting compendium but some previously
           reported.
EPA and Ricardo appreciate the comment; no
response needed.
General
Completeness
                              457
           Shimizu, R., et al., Analysis of a Lean Burn Combustion Concept
           for Hybrid Vehicles, 2009,13 p. A technical paper, this document
           describes early (1984) and more recent Toyota lean burn engines.
           Comment: Interesting technical description but no clear if or how
           used in the Ricardo model.
See response to Comment Excerpt 424.
General
Simulation
methodology
                              458
           Takoaka, T., et al., Toyota, Super high efficient gasoline engine
           for Toyota hybrid system, (no date), 16 p. This paper describes
           the hybrid system,  1C engine interaction that allows increased 1C
           engine efficiency.
           Comment: Of general interest but application to the model not
           clear.
See response to Comment Excerpt 424.
General
Inputs and
Parameters
                              459
           Ricardo, Assessment of Technology Options, Technologies
           related to Transmission and Driveline, 19 Nov 09, 21 p. This
           document described transmission technologies, including timing
           of their introduction.
           Comment: Seems reasonable.
EPA and Ricardo appreciate the comment; no
response needed.
General
Recommendations
                              460
           Ricardo, Transient Performance of Advanced Turbocharged
           Engines, 15 Sep 10,19 p. (proprietary) This report reviews
           expected advances in boosting technologies and anticipated
           effects on vehicle performance.
           Comment: Interesting information but how it impacts model is not
           clear.
See response to Comment Excerpt 424.
General
                                                                              105

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    Peer Review Response Document
                                                                                                                             November 29, 2011
                                                 Table 1: Response to Individual Peer Review Comments
                T
                 Specific
e Question    Assump
Comment
Completeness
                               461
                                                                       Comment
           Kapus, P., Potential of WA Systems for Improvement of C02
           Pollutant Emission and Performance of Combustion Engines, 30
           Nov 2006, 9 p. This is a technical paper describing variable valve
           actuation approaches and performance effects.
           Comment: Useful general technical information.
EPA and Ricardo appreciate the comment; no
response needed.
General
Inputs and
Parameters
                               462
           Ricardo, Assessment of Technology Options, Technologies
           related to Vehicle-level  Systems, 24 Nov 09,16 p. This review of
           vehicle technologies that can improve vehicle efficiencies
           provides a basic description and information on expected levels of
           C02 reduction.
           Comment: This is a clear description of anticipated improvements
           in vehicle technologies that reduce load and fuel consumption.
EPA and Ricardo appreciate the comment; no
response needed.
General
Executive
Summary
                               463
           Ricardo has provided material, which is stated to be the data
           incorporated in the computer simulation. These data are
           consistent with the data expected to be the basis of the
           simulation. It is impossible to establish  a precise correspondence
           between the data and the model. The performance data covered
           by the 44 separate documents seem reasonable and provide
           additional assurance that the simulation is soundly based on
           measured performance. There is no reason to doubt either the
           integrity or capability of Ricardo in their incorporation of
           appropriate data into their simulation model.
EPA and Ricardo appreciate the comment; no
response needed.
General
                                                                               106

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    Peer Review Response Document
                                                                                                                                 November 29, 2011
                                                   Table 1:  Response to Individual Peer Review Comments
                 T
                 Specific
e Question     Assump
Comment
Other Comments
                                17
            For the most part, the right technologies are being considered.
            However, certain promising technologies and fuel options for 1C
            engine technologies (other than gasoline and diesel) that can
            make a significant contribution to the improvement of mpg and
            reduction of C02 emissions have not been considered, or even
            mentioned at all. Primary examples are advanced combustion
            technologies, such as high pressure, dilute burn, low temperature
            combustion  (e.g., Homogeneous Charge Compression Ignition,
            Partially Premixed Compression Ignition, Spark-Assisted
            Compression Ignition), and closed-loop, in-cylinder pressure
            feedback. Some of these combustion technologies have the
            potential to improve fuel economy by up to 25%. Another
            significant assumption is that fuels used are equivalent to either
            87 octane pump gasoline or 40 cetane pump  diesel. However,
            advanced biofuels, particularly from  cellulosic or lingo-cellulosic
            bio-refinery processes, which from the standpoint of a life cycle
            analysis have strong potential for reduction of C02 emissions,
            can have significantly different properties (including octane and
            cetane numbers) and combustion characteristics than the current
            fuels. Note that over 13 billion gallons of renewables were used in
            2010, primarily from corn-ethanol and some biodiesel. According
            to the Renewable Fuel Standard, 36 billion gallons of renewables
            need to be used by 2022. Also, a joint study carried-out by Sandia
            and General Motors has shown that ninety billion gallons of
            ethanol (the energy equivalent of approximately 60 billion gallons
            of gasoline)  can be produced in the US by year 2030 under an
            aggressive biofuels deployment schedule.
The technology selections and combinations
were selected to provide a representative group
of combinations that reflect the thinking of the
program team of some of the most common
expected combinations across the range of light
duty classifications. The full slate of options
considered is set forth in Attachment A to the
final report. While EPA agrees that additional
combinations are of interest, the project scope
was a significant undertaking,  both in terms of
budget and time, with the options selected. The
report is one of the technical studies relevant to
EPA's ongoing rulemaking efforts, and the scope
was designed to support that effort.  EPA
anticipates that others and perhaps EPA will
continue to explore these issues with further
studies that add scope.
General
                                                                                 107

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    Peer Review Response Document
                                                                                                                                November 29, 2011
                                                   Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Comment
Inputs and
Parameters
                               183
            Recommendation:  Subsystem models/map should be added to
            this report and another peer review conducted to assess their
            adequacy before this report is released.
                                                            Use of proprietary data was a ground rule of the
                                                            study. However, in the final report, we have
                                                            added a great deal of detail using publically
                                                            available references and sources to provide
                                                            further understanding of these issues and how
                                                            the study addressed them. Also, on specific
                                                            maps relevant to the engine model, we note that
                                                            the effects of the valve actuation system, fueling
                                                            system,  and boost system were integrated into
                                                            the final torque curves and fueling maps,
                                                            therefore subsystem performance maps, such as
                                                            turbine and compressor efficiency maps, are not
                                                            relevant to this study.
                                              General
Completeness
                               223
            Concern:  This report has significant deficiencies in its description
            of the entire process used in the modeling work.  Many of these
            deficiencies have been previously discussed, but are listed here
            for completeness.
                                                            Use of proprietary data was a ground rule of the
                                                            study. However, in the final report, we have
                                                            added a great deal of detail using publically
                                                            available references and sources to provide
                                                            further understanding of the modeling and
                                                            related issues, and how the study addressed
                                                            them.
                                              General
Completeness
             Section 2
             Objectives
122
A discussion of appropriate/anticipated use of the results is
required.
Please refer to the 2017-2025 rule documents:
Chapter 2 of the Joint TSD and Chapter 1 of
EPA's draft Regulatory Impact Analysis.
General
Inputs and
Parameters
             Engine Models
309
This reviewer took some time to look at the data via the tool
provided. One table is shown in Figure 1 which shows some
unexpected results. The results are for a small car with the dry
clutch transmission and it shows the baseline engine having
superior fuel economy over all other non-hybrid powertrain
options. This is unexpected behavior and, since there is minimal
transparency in the model, it cannot be investigated any further.
(See Exhibit 10)
The baseline engine may not be selected with
advanced technologies.  The tool has been
corrected to avoid this issue.
General
                                                                                 108

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                                                 Table 1:  Response to Individual Peer Review Comments
                T
                 Specific
e Question     Assump
Topic
Comment
Results
                               117
           On the performance runs, a few tenths of a second represent
           measurable difference in engine torque for example.
EPA and Ricardo appreciate the comment.
General
References
Coltman, et al. (2008), "Project Sabre: A Close-Spaced Direct Injection 3-Cylinder Engine with Synergistic Technologies to Achieve Low C02 Output", SAE Paper 2008-01-0138.
Hellenbroich, et al. (2009), "FEV's New Parallel Hybrid Transmission with Single Dry Clutch and Electric Torque Support."
Lumsden, etal. (2009), "Development of a Turbocharged Direct Injection Downsizing Demonstrator Engine", SAE Paper 2009-01-1503.
PQAand Ricardo (2008), "A Study of Potential Effectiveness of Carbon Dioxide Reducing Vehicle Technologies."
Staunton, et al. (2006), "Evaluation of 2004 Toyota Prius Hybrid Electric Drive System", ORNL technical report TM-2006/423.
Turner, et al. (2009), 'Sabre: A Cost-Effective Engine Technology Combination for High Efficiency, High Performance and Low C02 Emissions", IMechE conference
proceedings.
                                                                             109

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Supplement

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                        Peer Review of
Ricardo, Inc. Draft Report, "Computer Simulation of Light-Duty
Vehicle Technologies for Greenhouse Gas Emission Reduction
                 in the 2020-2025 Timeframe"
                           Final Report
                         September 30,2011
                            Prepared by
                           ICF International
                           9300 Lee Highway
                             Fairfax, VA
                               and
                         620 Folsom Street, Suite 200
                           San Francisco, CA

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This report was prepared by ICF International for the U.S. Environmental Protection Agency (EPA),
Office of Transportation and Air Quality under EPA Contract No. EP-C-06-094, Work Assignment 4-04,
at the direction of EPA Work Assignment Manager Jeff Cherry.

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Contents

1.   Introduction	1
2.   The Peer Review Process	1
3.   Verbatim Peer Reviewer Comments in Response to Charge Questions	3
4.   References	74
Appendix A. Charge to Peer Reviewers	A-l
Appendix B. Peer Reviewer CVs	 B-l
Appendix C. Peer Reviewer Comments as Submitted Round 1	 C-l
Appendix D. Peer Reviewer Comments as Submitted Round 2	 D-l
Appendix E. Draft Project Report by Ricardo	E-l

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                                          Introduction
As the U.S. Environmental Protection Agency (EPA) develops programs to reduce greenhouse gas
(GHG) emissions and increase fuel economy of light-duty highway vehicles, there is a need to evaluate
the costs of technologies necessary to bring about such improvements. Some potential technology paths
that manufacturers might pursue to meet future standards may include advanced engines, hybrid electric
systems, and mass reduction, along with additional road load reductions and accessory improvements.
One method of assessing the effectiveness of future light duty vehicle (LDV) technologies on future
vehicle performance and GHG emissions in the near-term timeframe is through modeling assessments.

Ricardo, Inc. (2011) developed such simulation models and documented the relevant technologies, inputs,
modeling techniques, and results of the study in its April 6, 2011, report, Computer Simulation of Light-
Duty Vehicle Technologies for Greenhouse Gas Emission Reduction in the 2020-2025 Timeframe.
Ricardo performed this work under a subcontract to Systems Research and Applications Corporation
(SRA) under EPA contract EP-W-07-064. The report documented both LDV technologies likely to be
available within the specified timeframe and the development of a visualization tool that allows users to
evaluate the effectiveness of such technology packages in both reducing GHG emissions and their
resulting effect on vehicle performance. The technologies addressed including conventional and hybrid
powertrains, transmissions, engine technologies and displacement, final drive ratio, vehicle weight, and
rolling resistance were examined for seven light-duty vehicle classes.

EPA contracted with ICE International (ICE) to coordinate an external peer review of the inputs,
methodologies, and results described in this report. The review was broad and encouraged reviewers to
address  the adequacy of the model's inputs and parameters, the simulation methodology, and its
predictions as well as the report's completeness and adequacy for the stated goals.

This report documents the peer review process and provides comments by the peer reviewers in a table
sorted by charge question topic and subtopics.
From March to September 2011, EPA contracted with ICE to coordinate this peer review. ICE
coordir
2006).
coordinated the peer review in compliance with EPA's Peer Review Handbook (3rd Edition) (U.S. EPA,
EPA requested that the peer reviewers represent subject matter expertise in advanced engine technology,
hybrid vehicle technology, and vehicle modeling. ICE developed a list of qualified candidates from the
following sources: (1) ICE experts in this field with knowledge of industry, academia, and other
organizations, and (2) suggestions from EPA staff.  ICE identified ten qualified individuals as candidates
to participate in the peer review. ICE sent each of these individuals an introductory screening email to
describe the needs of the peer review and to gauge the candidate's interest and availability. ICE asked
candidates to provide an updated resume or curriculum vitae (CV).  Several candidate reviewers were
unable to participate in the peer review due to previous commitments, and one did not respond. ICE
reviewed the responses and evaluated the resumes/CVs of the interested and available individuals for
relevant experience and demonstrated expertise in the above areas, as demonstrated by educational

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                                    The Peer Review Process
degrees attained, research and work experience, publications, awards, and participation in relevant
professional societies.

ICF reviewed the interested, available, and qualified candidates with the following concerns in mind. As
stated in the EPA's Peer Review Handbook (U.S. EPA, 2006), the group of selected peer reviewers
should be "sufficiently broad and diverse to fairly represent the relevant scientific and technical
perspectives and fields of knowledge; they should represent a balanced range of technically legitimate
points of view."  As such, ICF selected peer reviewers to provide a complimentary balance of expertise of
the above criteria (see Table 1). EPA reviewed and approved ICF's slate of candidate peer reviewers.

The following five individuals agreed to participate in the peer review:

    1.   Dr. Dennis Assanis, University of Michigan
    2.   Mr. Scott McBroom, Fallbrook Technologies, Inc.
    3.   Dr. Shawn Midlam-Mohler, The Ohio State University
    4.   Dr. Robert Sawyer, University of California at Berkeley
    5.   Mr. Wallace Wade, Ford Motor Company (Retired)

                 Table 1. Chart of Peer Reviewer Expertise Areas and Affiliation
Peer Reviewers
D. Assanis,
Academic
S. McBroom,
Industry
S. Midlam-Mohler,
Academic
R. Sawyer,
Academic
W. Wade,
Industry (Retired)
LDV
Technology
^
^
^
^
^
Computer
Simulations
^
^
^


HEV
Technology
^
^
^
^
^
Prior to distributing the review materials, ICF sent each of the reviewers a conflict of interest (COI)
disclosure and certification form to confirm that no real or potential conflicts of interests existed. The
disclosure form addressed topics such as employment, investment interests and assets, property interests,
research funding, and various other relevant issues. Upon review of each form, ICF determined that each
peer reviewer had no COI issues and then executed subcontract agreements with all reviewers.

ICF provided reviewers with the following materials:
    •  Draft proj ect report by Ricardo (2011);
    •  The Ricardo Computer Simulation tool;

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                        Verbatim Peer Reviewer Comments in Response to
                                       Charge Questions
    •  The Peer Reviewer Charge to guide their evaluation; and
    •  A template for the comments organized around the Peer Reviewer charge.

The Peer Reviewer Charge provided peer reviewers with general guidelines for preparing their overall
review, with particular emphasis on inputs, methodologies, and results. The charge to peer reviewers is
provided in Appendix A.  The CVs for the reviewers are included in Appendix B.

A mid-review teleconference was held on May 5, 2011, to discuss the charge, the purpose of the review,
and to answer any outstanding questions the reviewers might have. The call was moderated by ICF and
attended by reviewers Dr. Assanis,  Mr. McBroom, Dr. Midlam-Mohler, Dr. Sawyer, and Mr. Wade, as
well as EPA staff Jeff Cherry, and Ricardo staff who were familiar with the report. During the mid-
review teleconference, several reviewers expressed some concerns about the level of detail provided in
the report, but no one requested additional information beyond some cited references.

The consensus of the first review was that reviewers needed more information than was provided in the
Ricardo report to complete their review.

EPA requested a second round of peer review in which the peer reviewers would be provide more
detailed information. Ricardo provided 45 additional PowerPoint presentations and documents, which
included more  clarity on assumptions, pictures of engine maps,  and other pertinent information.  ICF
contacted all five reviewers for interest and availability for this additional review. However, only three
reviewers confirmed their availability,  one  could not commit to a five-year term of confidentiality, and
one did not respond to the inquiry.

Three individuals agreed to participate in the second round of peer review:

    1.  Mr. Scott McBroom, Fallbrook Technologies, Inc
    2.  Dr. Shawn Midlam-Mohler, Ohio State University
    3.  Dr. Robert Sawyer, University of California, Berkeley

ICF executed non-disclosure agreements (NDA) with Mr. McBroom, Dr. Midlam-Mohler, and Dr.
Sawyer.  Once the NDAs were in place, ICF sent them the 45 additional review documents, plus the
reviewer  charge and the reviewer charge template.
Table 2 presents the verbatim comments received by the subject matter experts.  Comments are sorted by
charge question and then topic/categories. Cited exhibits and references are provided starting on page 69
and 74, respectively. In addition, Appendix C provides the first round of peer reviewer comments as
they were submitted by the peer reviewers, and Appendix D provides the second round of peer reviewer
comments as they were submitted.

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    Verbatim Peer Reviewer Comments in Response to
                  Charge Questions
Table 2. Sorted, Verbatim Comments from Reviewers
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic
6.3 Accessories
6.4 Transmission
Models
Accessory load
assumptions
Accessory load
assumptions
Accessory load
assumptions
Accessory load
assumptions
Accessory load
assumptions
Comment
Excerpt
No
73
76
335
336
337
185
186
Review
Round
1
1
1
1
1
1
1
Reviewer
McBroom
McBroom
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Wade
Wade
Comment
I think the assumption that LOT cooling fans will be engine driven is incorrect. The new
F150's have electric fans.
no efficiency maps, no description of the efficiency maps. What was efficiency a function of?
Typically it's gear ratio, torque and speed.
The accessory model is divided into electrical and mechanical loads. The electrical sub-
model assumes alternator efficiency's of 55% and 70% for the baseline and advanced
vehicles respectively. Given the required simplicity of the model, a simple model like this is
likely acceptable, however, there is no source described for the alternator efficiencies. The
base electrical load of the vehicle is mentioned briefly, however, no numerical values are
given for each vehicle class or any type of model described.
The electrical system also includes an advanced alternator control which allows for increased
alternator usage during decelerations for kinetic energy recovery. The control description
given is valid but simplistic, but seems to fit the expected level of accuracy required for the
purpose. There is an issue regarding with the approach for modeling the battery during this
process. When charging the battery at the stated level of 200 amps, the charging efficiency
of the battery will be relatively poor. During removal of the energy later, there will once again
be an efficiency penalty. There is no description of a low-voltage battery model in the report
nor any explicit reference to such charge/discharge efficiencies. Additionally, an arbitrary
limit of a 200 amp alternator is defined for all vehicle classes - it is unlikely that a future small
car and a future light heavy duty truck will have an alternator with the same rating.
On the mechanical side, it is assumed that "required accessories" (e.g. engine water pump,
engine oil pump) are included in the engine maps. The mechanical loading of a mechanical
fan is mentioned but no description of the model which, at a minimum, should be adjusted
based on engine speed and engine power.
The accessory selections listed in Table 5-2 (page 22) appear to be adequate except for the
following issue: Belt driven air conditioning for the stop-start powertrain configuration is not
acceptable for driver comfort. Electrically driven air conditioning is required for the stop-start
powertrain configuration to provide driver comfort for extended idle periods.
Input values
Alternator efficiency was increased from the current level of 55% to 70% to reflect "an
improved efficiency design" (page 26 and 27).

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question Specific Comment R .
Excerat Reviewer Comment

Inputs and Accessory load
187
Parameters assumptions

Inputs and
Parameters
Inputs and
Parameters
Inputs and

Accessory load
assumptions
Accessory load
assumptions
Actual
Parameters models/maps for







Inputs and
subsystems
(engine,
transmission,
hybrid system,
accessories, final
drive, tires and
vehicle)
Actual
Parameters models/maps for
subsystems






(engine,
transmission,
hybrid system,
accessories, final
drive, tires and
vehicle)

188

189

181








182








1


1

1

1








1








Wade
Comment: Justification for the increase in alternator efficiency from 55% to 70% should be
added to the report with references provided. Alternator efficiency as a function of speed

Wade

Wade

Wade








Wade








and load may be more appropriate than a constant value.
Accessory power requirements were not provided, such as shown in Figure 3-3 PQA and
Ricardo (2008), for example.
Recommendation: Both mechanically driven and electrically driven accessory power
requirements should be clearly provided in the report.
None of the subsystem models/maps were provided for review so comments on their
adequacy are not possible.







Issue: Insufficient reasons are presented to justify why the models/maps for subsystems are
not provided in the report, especially when one of the goals of the report was to provide
transparency (per Jeff Cherry, May 5, 201 1 teleconference and Item 5, below).







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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Hommpnt
Charge Question Specific v-ommeni
Excerat Reviewer Comment

Inputs and
Actual
183
Parameters models/maps for







Inputs and
subsystems
(engine,
transmission,
hybrid system,
accessories, final
drive, tires and
vehicle)
Actual







184
Parameters models/maps for







Inputs and
subsystems
(engine,
transmission,
hybrid system,
accessories, final
drive, tires and
vehicle)
Advanced
Parameters Valvetrains






(Section 4. 1.1)












318







1








1








1







Wade
Recommendation: Subsystem models/map should be added to this report and another peer
review conducted to assess their adequacy before this report is released.







Wade







Recommendation: To establish the adequacy of the subsystem models/maps, derivation
details should be provided.







Midlam-







Two types of advanced valvetrains were included in the study, cam-profile switching and
Mohler digital valve actuation. Both of these technologies are aimed at reducing pumping losses at






part-load. The impact of these technologies is difficult to predict using simplified modeling
techniques and typically require consideration of compressible flow and a 1-D analysis at a
minimum. Even with an appropriate fidelity model, these systems require significant
amounts of optimization in order to determine the best possible performance across the
torque-speed plane of the engine. It is unclear how these systems were used to generate
accurate engine maps given the level of detail provided in the report.

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Quest on Specfc Comment R
%. . . .. „. . Excerpt 0 . Reviewer Comment
Topic Assumption/Topic .. K Round
Inputs and Aftertreatment/
Parameters Emissions












Inputs and
Solutions











Alternator Regen
315













385
Parameters Shift Optimizer




Inputs and




Baseline vehicle
Parameters subsystem

Inputs and
models/maps
Baseline vehicle




160


161
Parameters subsystem

models/maps

Inputs and Baseline vehicle 162
Parameters subsystem

Inputs and
Parameters
models/maps
Baseline vehicle
subsystem
models/maps


163


1













2





1


1


1


1


Midlam-
Based on the report, it seems that emissions solutions are assumed to be available for all
Mohler powertrain technology packages selected. The report discusses this in some qualitative












Midlam-
detail in section 4.2.2 with respect to lean-stoichiometric switching. This discussion is
somewhat incomplete, in that the way it is written it assumes operating at stoichiometry
lowers exhaust gas temperature. In reality, switching from lean to stoichiometric operation at
constant load results in higher exhaust gas temperatures. Despite this factual inconsistency,
it is indeed generally better to operate a temperature sensitive catalyst hot and stoichiometric
or rich rather than hot and lean - so the concept of lean-stoich switching is valid even if the
explanation provided is not. Even without this factual inconsistency, some additional
discussion of aftertreatment systems would be of benefit given that lean-burn gasoline
engines are at present a well-known technology for many years that is still problematic with
respect to emissions control. A separate issue is the topic of fuel enrichment for exhaust
temperature management which will have an important impact on emissions and, if
emissions are excessive, reduce the peak torque available from an engine.
The alternator regeneration strategy is not well documented. The key system specifications,
Mohler such as max alternator output and efficiency, are listed as assumptions without a data source




Wade


Wade
for validation. The efficiency of the battery is not mentioned in this nor other presentations
that this reviewer has read - battery efficiency for a lead acid battery at high currents is poor,
this would have an impact on the recovery of energy. Strategies like this are disruptive to
drivability and this issue is not discussed in the presentation.
The development of baseline vehicle models with comparison of the model results to
available 2010 EPA fuel economy test data was appropriate.

The models/maps for the subsystems used in these vehicle models were not provided in the
report so that their adequacy could not be assessed.


Wade Including these baseline models in the report would assist in assessing the development


Wade


process as well as the adequacy of the new technology subsystem models/maps, which was
not possible in this peer review.
Recommendation: Since the baseline vehicles modeled were 2010 production vehicles, the
models/maps for the subsystems used in these vehicle models should be included in the
report before it is released.

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic
Baseline vehicle
subsystem
models/maps
Baseline vehicle
subsystem
models/maps
Battery SOC swing
and SOC
Battery SOC swing
and SOC
Battery Warm up 1,
Battery Warm up 2
Battery Warm up 1 ,
Battery Warm up 3
Battery Warm up 1 ,
Battery Warm up 4
Battery Warm up 1,
Battery Warm up 5
Boosting System
(4. 1.3 and 6.3)
Comment
Excerpt
M«
164
165
190
191
387
388
389
390
326
Review
Round
1
1
1
1
2
2
2
2
1
Reviewer
Wade
Wade
Wade
Wade
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Comment
A major omission was that a baseline model of a hybrid vehicle, which is significantly more
complex than the baseline vehicle, was not developed and compared to available EPA fuel
economy test data for production hybrid vehicles.
Recommendation: A baseline model of a hybrid vehicle should be developed and compared
to 2010 EPA fuel economy test data for production hybrid vehicles.
Although not contained in the report, an email from Jeff Cherry (EPA) on May 5, 201 1
revealed that the SOC swing was 30% SOC to 70% SOC or 40% total, which appears to be
appropriate.
Achieving neutral SOC (neither net accumulation or depletion) for hybrid vehicle simulations
is appropriate (page 30).
The battery model described has the following possible problems: The model is relatively
simple - but could potentially work for the application and generally is consistent with the
fidelity of the rest of the model.
The battery model described has the following possible problems: The model references
ambient temperature for heat rejection. Most HEVs pull in cabin air rather than outside air for
cooling, thus, this will cause modeling error.
The battery model described has the following possible problems: Adjusting the Mbatx
Cpbat term by 200% is a red flag that something might be fundamentally wrong with either
the model formulation or the data used in the model. There should be minimal errors in the
mass estimation of the pack and the specific heats of battery modules can be found in the
literature or through testing.
The battery model described has the following possible problems: The method of handling
battery packs of different classes of vehicles is not described, nor are the actual parameters
for these different models disclosed.
Boosting was applied to many of the different powertrain packages simulated. Beyond
stating what maximum BMEP that was achievable, very little is mentioned in how the
efficiency of the boosted engines were determined. Among other factors, boosting often
creates a need for spark retard which costs efficiency if compression ratio is fixed. These
complex issues are tied to combustion which is inherently difficulty to model. This aspect of
the engine model is not well documented in the report.

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic
Direct Injection
Fuel Systems
DOE ranges
DOE ranges
Electric Traction
Components
Engine Downsizing
Engine Models
Comment
Excerpt
Mn
322
192
193
352
329
306
Review
Round
1
1
1
1
1
1
Reviewer
Midlam-
Mohler
Wade
Wade
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Comment
Because of the availability of research and production data in this area, it is expected that
performance from this technology was used to predict performance rather than any type of
modeling approach. That being said, the report does not describe where or how this data
might have been used to develop the fuel consumption map of the engines simulated nor
what data sources were used.
The following DOE ranges for Baseline and Conventional Stop-Start (page 23) appear to be
appropriate, with the exception of Engine Displacement. Since the default for the
Stoichiometric Dl Turbo engine appears to be greater than 50% reduction in displacement
(Standard Car baseline of 2.4L is reduced to 1 .04L for the Stoichiometric Dl Turbo (page
46)), the opportunity should be provided to start with a displacment near the baseline engine
(2.4L) and progressively decrease it to approximatly 50% (1 .04L). This would require an
Engine Displacement upper range of over 200%. The model should also have the capabilty
of increasing the boost pressure as the displacement is reduced. (See Exhibit 1).
The following DOE ranges for P2 and PS hybrid vehicles (page 24) appear to be appropriate
(See Exhibit 2)
The model of electric traction components is not discussed in any detail, as the only mention
in the report is that current technology systems were altered by "decreasing losses in the
electric machine and power electronics." Given the importance of the electric motor and
inverter system in hybrids this is not acceptable.
Engine scaling is used extensively in the report. Basic scaling based on brake mean
effective pressure is common in modeling at this level of fidelity, thus, this does not need any
special description. However, the report mentions some means of modeling the increased
relative heat loss with small displacement engines which is not a standard technique. The
model or process used to account for this effect should be explicitly described given that
engine size is one of the key parameters in the design space.
The engine model is the most important element in successfully modeling the capability of
future vehicles, since it is the responsible for the largest loss of energy. It is also one of the
most difficult aspect to predict since it involves many complicated processes (i.e.
combustion, compressible flow) which must be considered in parallel with emissions
compliance (i.e. in-cylinder formation, catalytic reduction.) Because of this, this sub-model
must be viewed with extreme scrutiny in order to ensure quality outputs from the model.

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic
Engine Models
Engine Models
Engine Models
Engine technology
selection
Engine technology
selection
Comment
Excerpt
Mn
307
308
309
342
166
Review
Round
1
1
1
1
1
Reviewer
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Wade
Comment
The engine models are "defined by their torque curve, fueling map, and other input
parameters." This implies that the maps are static representations of fuel consumption
versus torque, engine speed, and other unknown input parameters. Generally speaking,
representing engine performance in this fashion is consistent with typical practice for this
class of modeling. This comment deals only with the representation of the engine
performance in simulation, the generation of the data contained within the map is much more
challenging.
The report outlines two methods were used to produce engine models. The first method was
used for boosted engines and relied upon published data on advanced concept engines
which would represent production engines in the 2020-2025 timeframe. The second method
was used with Atkinson and diesel engines and somehow extrapolated from current
production engines to the 2020-2025 time frame. The description of both of these methods
in the report is unsatisfactory. It also fails to address how the various technologies are used
to build up to a single engine map for a specific powertrain. Validation, to the extent possible
with future technologies, is also lacking in this area.
This reviewer took some time to look at the data via the tool provided. One table is shown in
Figure 1 which shows some unexpected results. The results are for a small car with the dry
clutch transmission and it shows the baseline engine having superior fuel economy over all
other non-hybrid powertrain options. This is unexpected behavior and, since there is minimal
transparency in the model, it cannot be investigated any further. (See Exhibit 10)
There are a host of different technologies superimposed to create the future powertrain
technologies. There is not a clear process described on how this technology "stack-up" is
achieved. For instance, an advanced engine technology may allow for greatly improved
BMEP. Greatly improved BMEP often comes at the expense of knock limits which are
difficult to model even with sophisticated modeling techniques. In this simulation, many
layers of powertrain technology are being compounded upon each other which will not simply
sum up to the best benefits of all of the technologies - there are simply too many
interactions. At the level of modeling described, which are maps which are altered in various
unspecified ways; it is not clear how the technology stack-up is captured..
The engine technologies selected for this study, listed in Table 5.1 (page 22), are
appropriate, but are not all-inclusive of possible future engine technologies.
                     10

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic
^
Engine technology
selection
Engine technology
selection
Engine technology
selection
Engine technology
selection
Engine technology
selection
Engine technology
selection
Future Friction
Assessment
Comment
Excerpt
M«
167
168
169
170
171
172
392
Review
Round
1
1
1
1
1
1
2
Reviewer
Wade
Wade
Wade
Wade
Wade
Wade
Midlam-
Mohler
Comment
Setting the minimum per-cylinder volume at 0.225L and the minimum number of cylinders at
3 is appropriate. However, achieving customer acceptable NVH with 3 cylinder engines
continues to be problematic.
Issue: The description of the derivation of all of the engine models/maps was insufficient.
Issue: The technology "package definitions" precluded an examination of the individual
effects of a variety of technologies such as a single stage turbocharger vs. series-sequential
turbochargers.
Issue: There are many engine technologies that have potential for reduced GHG emissions
that were not included in this study, such as:-Single stage turbocharged engines - Diesel
hybrids- Biofueled spark ignition and diesel engines- Natural gas fueled engines- Other
alternative fuel engines- Charge depleting PHEV and EV
The feasibility of the following assumptions for the engines modeled should be re-examined
as indicated below: None of the Stoichiometric Dl Turbo engines listed as references by
Ricardo (201 1) limited the turbine inlet temperature to a value as low as the 950C limit in the
Ricardo model (Coltman et al., 2008; Turner et al., 2009; Lumsden et al., 2009). Reducing
the turbine inlet temperature to reach this limit is expected to result in BMEP levels below the
assumed 25-30 bar level in the model (which were obtained in the referenced engine with a
turbine inlet temperature of 1025C).
The feasibility of the following assumptions for the engines modeled should be re-examined
as indicated below: Turbocharger delays of the magnitude assumed in the model will result in
significant driveability issues for engines that are downsized approximately 50%. Although
Ricardo (201 1) assumed a turbocharger delay of approximately 1 .5 seconds, the comparable
delay published for a research engine was significantly longer at 2.5 seconds (Lumsden et
al., 2009).
The provided presentation does not describe how engine friction projections to 2020 are
made or how they are modeled. It provides some data from 1995 to 2005, however, it does
not provide any useful insight into how this information is used.
                     11

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic
HEV Battery Model
Hybrid technology
selection
Hybrid technology
selection
Hybrid technology
selection
Hybrid technology
selection
Comment
Excerpt
Mn
356
345
346
347
348
Review
Round
1
1
1
1
1
Reviewer
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Comment
Battery models for HEVs are necessary to adequately model the performance of an HEV.
The report provides no substantive description of the battery pack model, other than that the
model was developed by "lowering internal resistance in the battery pack to represent 2010
chemistries under development." Battery pack size is also not a currently a factor in the
model - this has a impact of charge and discharge efficiency of the battery pack.
Hybrid vehicles are particularly challenging to model because of the extra components which
allow multiple torque sources, and thus, require som form of torque management strategy
(i.e. a supervisory control.) The report briefly describes a proprietary supervisory control
strategy that is used to optimize the control strategy for the FTP, HWFET, and US06 drive
cycle. The strategy claims to provide the "lowest possible fuel consumption" which seems to
be somewhat of an exaggeration - this implies optimality which is quite a burden to achieve
and verify for such a complicated problem. The strategy also is reported to be "SOC neutral
over a drive cycle" which is also difficult to achieve in practice in a forward looking model.
Once can get SOC with a certain window, however, short of knowing the future or simply not
using the battery - it is impossible to develop a totally SOC neutral control strategy.
Another factor that must be considered is that a hybrid strategy that achieves maximum fuel
efficiency on FTP, HWFET, and US06 does not consider many other relevant factors.
Performance metrics like 0-60 time and drivability metrics often suffer in practice. In today's
hybrids, the number of stop-start events is sometimes limited from the optimum number for
efficiency because of the emissions concerns. Because of these factors and others, a
strategy achieving optimal efficiency may be higher than what can be achieved in practice.
Without even basic details on the hybrid control strategy, it is simply not possible to evaluate
this aspect of the work. Because of the batch simulations with varying component sizes and
characteristics, this problem is not trivial. Supervisory control strategies used in practice and
in the literature require intimate knowledge of the efficiency characteristics and performance
characteristics of all of the components (engine, electric motors/inverters, hydraulic braking
system, and energy storage system) to develop control algorithms. This concern is amplified
by the lack of validation of the hybrid vehicle model against a known production vehicle. It is
unclear how a "one-size fits all" control strategy can be truly be perform near optimal over
such widely varying vehicle platforms.
A last comment is that there is no validation of the HEV model against current production
vehicles. At a minimum, the Toyota Prius has been dissected sufficiently in the public
domain to conduct a validation of this class of hybrid electric vehicle.
                     12

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic
Hybrid technology
selection
Hybrid technology
selection
Hybrid technology
selection
Hybrid technology
selection
Input Data Review
Input Data Review
Input Data Review
Other inputs
Comment
Excerpt
M«
177
178
179
180
397
398
399
194
Review
Round
1
1
1
1
2
2
2
1
Reviewer
Wade
Wade
Wade
Wade
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Wade
Comment
The hybrid technologies selected for this study, listed in Table 5.2 (page 22) are appropriate.
Issue: The adequacy of the P2 Parallel and PS Power Split Hybrid systems cannot be
determined without having, at a minimum, schematics and operational characteristics of the
each system together with comparisons with today's hybrid systems.
Although not contained in the report, the teleconference call with Jeff Cherry (EPA) on May
5, 201 1 revealed that 90% of the deceleration kinetic energy would be recovered.
Kinetic energy recovery is limited by the following:
- Maintaining high generator efficiency over the range of speeds and resistive torques
encountered during deceleration
- Limitations on the rate at which energy can be stored in the battery
-Losses in the power electronics
-Some energy is lost when energy is withdrawn from the battery for delivery to the motor.
- Inefficiencies in the motor at the speeds and torques required.
The inefficiencies of each of these four subsystems are in series and are compounded. If
each subsystem had 90% efficiency, the kinetic energy recovery efficiency would be only
66%.
Issue: Capturing 90% of the deceleration kinetic energy is a significantly goal. The
technology to be used to achieve this goal needs to be explained and appropriate references
added to the report.
The documentation on the Diesel engine maps was helpful; however, it did not discuss how
the 2020 engine maps were developed. This is critical for having confidence in the
predictions made for the Diesel powertrains in 2020.
The shift strategy is discussed qualitatively; however, it is not described in enough detail to
understand exactly how it is accomplished. Shift schedules are shown, however, no
validation is shown that would indicate that these shift schedules are optimal as claimed.
The torque converter models are standard models, thus, the provided documentation is
adequate.
The Design Space Query within the Data Visualization Tool allows the user to set a
continuous range of variables within the design space range. Although this capability is
useful for parametric studies, the following risks are incurred with some of the variables.
                     13

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic
Other inputs
Other inputs
Other inputs
Section 3.2 Ground
Rules for Study
Section 4
Section 4. 1.1.1
CPS
Section 4. 1.1. 2
DVA
Section 4. 1.3
Boosting Systems
Section 4. 1.4 Other
Engine
Technologies
Section 4.2 Engine
Configurations
Comment
Excerpt
Mn
195
196
197
63
64
65
66
67
68
71
Review
Round
1
1
1
1
1
1
1
1
1
1
Reviewer
Wade
Wade
Wade
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
Comment
The sliders for "Eng. Eff" and "Driveline Eff." would allow the user to arbitrarily change engine
efficiency or driveline efficiency uniformly over the map without having a technical basis for
such changes.
The slider for weight would allow the user to add hybrid or diesel engines with signficant
weight increases without incurring any vehicle weight increase.
Recommendation: A default weight increase/decrease should be added for each technology.
If weight reductions are to be studied, then the user should have to input a specific design
change, with the appropriate weight reduction built into the model, rather that having an
arbitrary slider for weight.
The vehicle and technology selection process needs further discussion. My experience in
these large simulation studies is that the vast majority of the time needs to be spent on the
selection and once selected agreeing upon the model/data.
There was no model data provided. Engine maps, transmission efficiency maps, battery
efficiency maps etc need to be in the Appendices. The black box nature of the inputs is
disconcerting.
How were the profiles selected? Was there an optimization process for each engine size of a
given engine type?
Was the actuation power requirement accounted for? What were the timing/lift profiles and
what control strategy was used to select the timing/lift profile? Was this an active model or
was the timing/lift profile preset and then unchangeable. I would expect that as the engine
size changes and the boost changes the timing/lift profile will have to change with it.
What about superchargers? Eaton's AMS supercharger systems offer high efficiency
supercharges that are comparable to turbo's and don't have the lag problem.
regarding global engine friction reduction, what value(s) was assigned to that? Was it the
same across all engines? If so, why?
Quantification needed ..."The combinations of technologies encompassed in each advanced
engine concept provide benefits to the fueling map...."
                     14

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic
Shift Optimizer
SI Engine Maps
and Diesel Engine
Maps
SI Engine Maps
and Diesel Engine
Maps
Transmission
technology
selection
Transmission
technology
selection
Transmission
technology
selection
Transmission
technology
selection
Comment
Excerpt
Mn
386
394
395
173
174
175
176
Review
Round
2
2
2
1
1
1
1
Reviewer
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Wade
Wade
Wade
Wade
Comment
Shifting strategy impacts efficiency, performance, and drivability. Manufacturers are aware
of this and balance all three when calibrating shift maps. Changing baseline shift maps to
improve efficiency will have an impact on the other metrics which are also important to the
vehicle. Additionally, it is not clear how the optimized shift strategy was developed, what the
shift strategy is, or how it will be applied to the range of transmissions in the study. It is
stated that is optimizes BSFC, however, there are other constraints that must be applied in
addition to this.
The baseline engine map data is shown in a series of figures and references are provided for
the specific vehicle that the map is for. It is assumed that this indicates that this data has
been measured experimentally. If this is the case, then this is well documented.
For the 2020 engine maps, there is insufficient detail in this presentation on how the maps
were generated. Getting accurate simulation requires careful validation of the model as well
as the data in the model - these engine maps are not sufficiently well documented for me to
make a judgment on their suitability for the overall goal of the simulator. I am well aware that
these future engines do not exist, but there had to be some process of generating these
engine maps. Without more information on this process it is simply not possible to comment
on their accuracy.
The transmission technologies selected for this study, listed in Table 5.3 (page 23) are
appropriate.
The forecast that current 4-6 speed automatic transmissions will have 7-8 speeds by 2020-
2025 is appropriate for all except the smallest and/or low cost vehicles (page 19).
The report mentions that the transmissions include dry sump, improved component
efficiency, improved kinematic design, super finish, and advanced driveline lubricants (page
22).
Recommendation: The detailed assumptions showing how the benefits of dry sump,
improved component efficiency, improved kinematic design, super finish, and advanced
driveline lubricants were added to the transmission maps should be added to the report
before it is released.
                     15

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic
Transmissions
Turbo Lag
Vehicle model
issues
Warm-Up
Methodology
Comment
Excerpt
M«
360
391
303
332
Review
Round
1
2
1
1
Reviewer
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Comment
This peer reviewer is not as well-practiced in transmissions as in other areas in this review.
Because of this, a more limited review was conducted of this aspect of the report. As with
the other areas of the report, the general concern in this area is the inadequacy of
documentation of the modeling approach and validation.
The data and methods used in modeling turbo lag are appropriate and there is sufficient
explanation and data to support the model.
The vehicle model is described as "a complete, physics-based vehicle and powertrain
system model" developed in the MSC.EasySTM simulation environment. This description is
not particularly helpful in defining the type of model as portions of the model are clearly not
physics based, such as the various empirical maps used or sub-models like the warm-up
model which is by necessity an empirical model due to the complexity of the warm-up
process compared to the expected level of fidelity of the model. It is assumed that a
standard longitudinal model accounts for rolling losses, aero losses, and grade is used to
model the forces acting on the vehicle. Input parameters for the vehicle model are not
described. The baseline vehicle platforms are listed, however, the relevant loss coefficients
are not provided (rolling resistance, drag coefficient, inertia.)
The report describes a 20% factor applied to bag 1 of the FTP-75 for baseline vehicles and a
10% factor applied to the advanced vehicles. The motivation for these factors is described
qualitatively and is valid, as many organizations are currently investigating strategies to
selectively heat powertrain components to combat friction effects. However, the values for
these factors that were selected are not backed up with any data or citation. It is suspicious
that the two values cited are such round numbers - the data from which these numbers are
derived should be cited. Because of the complexity of this phenomenon, some type of
empirical model is justified. The model described in the report is not sufficiently validated to
judge its suitability.
                     16

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                                                 Verbatim Peer Reviewer Comments in Response to
                                                                   Charge Questions
Charge Question
Inputs and
     Specific
Assumption/Topic
Comment
 Excerpt
Review
Round
                                                             Reviewer
Comment
Parameters


Inputs and
Parameters
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Parameters
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Inputs and
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21
22

23

24
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26




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Assanis
predic
pararr
Toolf
basis
datar
torque
strate
shouk
Some
follow
numb
well, v
Assanis Some

follow
norms
Assanis 1 Some

Assanis
Assanis


Assanis

follow
coolin
simulc
Some
follow
perce
Some
follow
warm
reject
Thee
comb
variab
not in
techn
pararr
indivic
                           20 |       1 |  Assanis      The report describes a comprehensive set of engine and vehicle technologies for the
                                                      prediction of GHG emissions and performance. However, the full range of inputs and
                                                      parameters is not explicitly presented. It requires the reader to refer to the Data Visualization
                                                      Tool figures to simulation environment,  it is impossible to extract details on, or judge the
                                                      basis for a number of critical inputs. In some occasions, the report mentions that published
                                                      data have been used, but there are no references to the source. Baseline engine maps,
                                                      torque converter maps and shifting maps, electric machine efficiency maps, and control
                                                      strategies for hybrids, which have very direct effects on vehicle performance and emissions,
                                                      should be presented in the report, at least in a limited format.
                                                                         Some examples of the types of inputs and parameters that would be helpful to include the
                                                                         following in the report: Any published fuel economy maps, or other related data, with actual
                                                                         numbers. For proprietary maps and data, a normalized representation would be useful, as
                                                                         well, without the actual bsfc values shown on the map.
                                                                         Some examples of the types of inputs and parameters that would be helpful to include the
                                                                         following in the report: Baseline maps used to represent turbomachinery, in actual or
                                                                         normalized form.
                                                                         Some examples of the types of inputs and parameters that would be helpful to include the
                                                                         following in the report: The baseline vehicle cooling system and accessory schematic vs.
                                                                         cooling system and accessory load schematics of the future engines considered in the
                                                                         Some examples of the types of inputs and parameters that would be helpful to include the
                                                                         following in the report: Details of EGR modeling parameters, such as maps showing
                                                                         percentage of EGR being used at various loads.
                                                                         Some examples of the types of inputs and parameters that would be helpful to include the
                                                                         following in the report: Details of warm-up model parameters, such as ambient temperature;
                                                                         warm up friction correction; cold start fuel consumption correction factor; generation of heat
                                                                         rejection maps for various combinations in the simulation matrix.
                                                                         The engine technology selection appears somewhat limited in terms of the selected
                                                                         combinations. For example, why is the Atkinson engine not boosted as well? Moreover, a
                                                                         variable valve actuation technology, as common and important as variable cam phasing, is
                                                                         not included. As already stated in the introductory comments, advanced combustion
                                                                         technologies, such as HCCI, are worth considering. More flexibility in the engine and vehicle
                                                                         parameters would also allow better understanding of the improvements obtained for
                                                                         individual technologies and possibly even show some potential synergies not currently
                                                                           17

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                                          Verbatim Peer Reviewer Comments in Response to
                                                         Charge Questions
Charge Question
    Topic
    Specific
Assumption/Topic
Comment
 Excerpt
Review
Round
Reviewer
Comment
                                                              identified.

Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
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Parameters
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Parameters











27
69
70
72
74
75
401
402
403

1
1
1
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1
2
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2

Assanis
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom

Alternative fuels are currently a key research topic and very important for future energy
independence. Because usage of these fuels can have an impact on efficiency and
emissions, the study would be enhanced if engine performance maps with various fuels were
included.
How was the FEAD electrification energy balance accomplished? Was additional load
placed on the alternator?
No mention or consideration of cylinder deactivation technologies. This seems like pretty low
hanging fruit, even on downsized boosted engines, especially if you deploy DVA.
How were baseline BFSC maps modified? Was it across the board improvement or were
improvements only attributed to certain parts of the map?
Limiting the alternator to 200A is very conservative, particularly if the system voltage stays at
14V.
Is there any accounting for the energy conversion on hybrids from the high voltage bus to the
low voltage?
Battery Model: Overall the battery model is sound; however, I don't understand why cold
modeling is included. The FTP testing doesn't include cold testing therefore only 25C and
up should be included and the battery is consistent at those temps.
Engine Model: I see data on the HEDGE engine technology but no mention of it in the list of
engine technologies unless it's the high EGR Dl gasoline engine.
Engine Model: The trend in engine technology is forced induction (engine downsizing). I think
the selection of turbo only is too limiting. I anticipate variable speed supercharging and other
combination of forced induction. I think the study would do well to include this.
                                                                18

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic









Comment
Excerpt
Mn
404
405
406
407
408
409
296
302
1
Review
Round
2
2
2
2
2
2
1
1
1
Reviewer
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
Midlam-
Mohler
Midlam-
Mohler
Sawyer
Comment
Rgen Alternator: Ricardo (201 1) states - 70% efficient alternator; however, alternator
efficiency is a function of temp, speed and load. 70% is probably the best, but it's highly
unlikely that it will operate there for the duration of the conditions.
Diesel Engine Fuel Maps: The presentation shows the technologies to be deployed, but
doesn't discuss how the 2020 bsfc maps were arrived at. It might be helpful to also use the
same method for comparison that the authors used to show LBDI vs EGR.
Diesel Technology: Curious about the author's comment regarding supercharging, "advances
to avoid variable speed". Why not variable speed?
Curious about why no discussion of advanced materials in engines to achieve improvements.
EBDI Engine: Couldn't find fuel economy benefit discussion in presentation. Should be done
as gasoline or energy equivalent. I know C02 is proportional, but....
Future Developments in Engine Friction - 1 think it would be worthwhile to point out that there
are technologies that are more driven by increased durability rather than fuel economy but
they could play off one another. Engine friction reduction is one of those areas.
From a high level, it is clear what the inputs to the design space tool are, which are listed in
tables 8.1 and 8.2. At the next level down (i.e. the vehicle and subsystem models) there is
no comprehensive handling of inputs in parameters in the report. Some models are partially
fleshed out in this area but most are lacking. By way of example, the engine models are
described as maps which are "defined by their torque curve, fueling map, and other input
parameters" where "other input parameters" are never defined.
The simulation methodology is generally not described in the report in sufficient detail to
assess the validity and accuracy of the approach. The models and approach are described
qualitatively; however, this is insufficient to truly evaluate the ability of the modeling approach
to perform the desired function. The following subsections address specific issues with the
models, inputs, and parameters and suggest possible corrective actions to address these
issues.
The vehicle classes and baseline exemplars are reasonably chosen, within the constraint
that vehicle size, footprint, and interior volume for each class be locked to the 2010 base
year. It is likely that new vehicle classes will emerge by 2025 and/or that these "locking"
restraints will be relaxed.
                     19

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic





Comment
Excerpt
Mn
2
419
420
421
424
Review
Round
1
2
2
2
2
Reviewer
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Comment
The design of experiment (DoE) ranges, Tables 5.4, 5.5, 8.1, and 8.2, are reasonable and do
not exclude likely sizings. The assumed alternator baseline and advanced alternator
efficiencies are reasonable. The assumed reduction in automatic transmission losses is
reasonable, but not aggressive for 15 development years from the baseline year. Similarly
the state-of-charge swing
for hybrid modeling of 30-70% is reasonable, but does not reflect improved battery
technology for the 2020-25 period, which should allow a greater swing for reduced battery
size, weight, and cost.
Ricardo, Action Item Response, 16 Feb 10, 15 p. (proprietary): A response to an EPA
inquiry, this document deals with engine maps, engine map comparisons, engine map plots,
transmissions, batteries, motor and generator efficiency maps.
Comment: Ricardo (201 1) responses and data selection seem reasonable.
Ricardo, Baseline Camry with Alternator Regen and Shift Optimizer Development of
Optimized Shifting Strategy Light Duty Vehicle Complex Systems Simulation EPA Contract
No. EP-W-07-064, work assignment 2-2, 15 Apr 10, 10 p. (proprietary): This document
provides data on effectiveness of shift optimizer, including alternator regen, over the FTP and
HWFET.
Comment: Seems reasonable, improvements are greater on FTP than HWFET.
Carlson, R., etal., Argonne National Laboratory, On-Road Evaluation of Advanced Hybrid
Electric Vehicles over a Wide Range of Ambient Temperatures EVS23 - Paper #275, 15 p.
Paper reports on-road and dynamometer testing of two hybrid vehicles at cold (-14 degC)
and hot (33 decC) conditions. Fuel economy increases with temperature (except for highest
temperatures with the system which does not limit battery temperature). Comment: Paper
provides data showing importance of temperature on hybrid vehicle fuel economy. These
data are used by Ricardo to validate their battery warm up model, see next document.
Mischker, K. and Denger, D., Requirements of a Fully Variable Valvetrain and
implementation using the Electro-Hydraulic Valve Control System EHVS, 24th International
Vienna Engine Symposium 2003, 17 p. This paper describes an electro-hydraulic valve
system (EVHS) and limited data on reduction in bsfc.
Comment: This would seem to be of limited quantitative value since technology is well
advanced beyond 2003.
                     20

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Specific
Assumption/Topic







Comment
Excerpt
Mn
425
428
430
432
437
439
440
Review
Round
2
2
2
2
2
2
2
Reviewer
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Comment
Ricardo, Engine and Battery Warm-Up Methodology, Light Duty Vehicle Complex Systems
Simularion, 17 Feb 10, 16 p. (proprietary) Document reviews engine and battery warm-up
strategies and provides a simple model.
Comment: The approach to battery warm-up is uncertain. Points to importance of test cycle
(FTP for fuel economy compliance versus test for EPA label versus real-world).
Ricardo, EBDI Project Overview, Ethanol Boosted Direct Injection, Nov 09, 8 p. This study
examines ethanol boosted direct injection (EBDI) to optimize engine operation of E85 fuel.
Possibility exists to match or exceed diesel performance and reduce C02 emissions.
Comment: It is not clear if comparison of EBDI and diesel is a equal technology level.
UOM, HiTor® for elecgtric, hybrid electric, and fuel cell powered vehicles, 18 Aug 09, based
on test data map, 5 p. Describes power electronics for motor generator control, including an
efficiency map for combined controller and motor based on test data.
Comment: Efficiency maps seem reasonable.
UOM, PowerPhase®75 for electric, hybrid electric, and fuel cell powered vehicles, not dated,
6 p. Described power electronics of vehicle electric power. Comment: Similar to earlier
brochure on power electronics, including efficiency map.
Ricardo, Hybrids Control Strategy, 6 Aug 10, 41 p. (proprietary) Discusses development of
control strategies for P2 and Power Split hybrids.
Comment: includes efficiency maps and substantial technical detail including vehicle mass
effect.
Ricardo, Assessment of Technology Options, 18 Nov 09, 14 p. (proprietary) Assessment of
hybrid technologies using evaluation template.
Comment: Treats a range of hybrid technologies, including series hydraulic, giving
projections of C02 reduction benefits.
Ricardo, Simulation Input Data Review, 2 Feb 10, 30 p. (proprietary) Document review
modeling parameters for vehicle performance simulations, including engine efficiency maps
for a range of engine and transmission technologies.
Comment: This is the kind of data that we requested. Includes shift strategies. Seems
reasonable and well-documented.
                     21

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Specific
Assumption/Topic




Major deficiencies
in the report
Major deficiencies
in the report
Major deficiencies
in the report
1 Major deficiencies
in the report
Major deficiencies
in the report
4.4 Transmission
Technologies
Comment
Excerpt
Mn
449
451
459
462
199
200
201
202
203
88
Review
Round
2
2
2
2
1
1
1
1
1
1
Reviewer
Sawyer
Sawyer
Sawyer
Sawyer
Wade
Wade
Wade
Wade
Wade
McBroom
Comment
Ricardo, Conventional Automatic Nominal Results, 16 Mar 10, 17 p. (proprietary) This
presentation includes mileage versus 0-60 mph time maps for a range of vehicles (light duty
to large truck). Also presented are comparisons of fuel economy for different regulatory test
cycles and technologies.Comment: Significance not clear.
Ricardo, Revised follow-up answers for hybrid action items, 23 Jun 10, 16 p. (proprietary)
This report answers questions on electric drive train efficiency, battery characteristics, and
available braking energy, and more.
Comment: Interesting data, but implication not clear.
Ricardo, Assessment of Technology Options, Technologies related to Transmission and
Driveline, 19 Nov 09, 21 p. This document described transmission technologies, including
timing of their introduction.
Comment: Seems reasonable.
Ricardo, Assessment of Technology Options, Technologies related to Vehicle-level Systems,
24 Nov 09, 16 p. This review of vehicle technologies that can improve vehicle efficiencies
provides a basic description and information on expected levels of C02 reduction.
Comment: This is a clear description of anticipated improvements in vehicle technologies
that reduce load and fuel consumption.
An overall schematic and description of the powertrain and vehicle models and the
associated subsystem models/maps were not provided. Only vague descriptions were
included in the text of the report.
Technical descriptions of how the subsystems and vehicle models/maps for the baseline
vehicles were developed were not provided.
Most importantly, only non-technical descriptions of how each of the advanced technology
subsystem models/maps was developed were provided.
Descriptions of the algorithms used for engine control, transmission control, hybrid system
control, and accessory control were not provided.
Descriptions of how synergistic effects were handled were not provided.
How were the gear ratios selected? What about shift logic?
                     22

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
••
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Specific
Assumption/Topic
6.3 Engine Models
6.3.1 Warm-up
Methodology
6.3.2 Accessories
6.8 Hybrids
7.2 Nominal Runs
Accessories
Models (Section
6.3.2)
Accessories
Models (Section
6.3.2)
Baseline vehicle
model validation
results
Baseline vehicle
model validation
results
Comment
Excerpt
hi.
92
95
96
97
98
38
39
204
205
Review
Round
•
1
1
1
1
1
1
1
1
Reviewer
McBroom
McBroom
McBroom
McBroom
McBroom
Assanis
Assanis
Wade
Wade
Comment
two methods to develop engine models were discussed. It is not disclosed which approach
was used for which engine. I recommend that one approach be developed for all engines or
both approaches be applied to each engine to converge to a solution.
How was the engine warmup modeled? Is it a first order transfer function with a time
constant? It said proprietary data was used, but how? Does the method allow for different
warmup depending on size and engine technology?
Constant alternator efficiency and load is not a very good assumption. New alternator
technologies and higher alternator loads due to electrification and increased electrical
demands. Will the future still continue to use 14V or will higher voltages be used?
Were separate optimization runs to determine the best control strategy done? How are we
assured the best control strategy is implemented?
Was a separate matrix of simulations run to obtain the nominal sizes for the advanced
engine or was it merely a matter of matching the peak torque.
Specific suggestions regarding models that need more detailed coverage: Alternator
efficiency has been assumed to be constant around 55% for baseline. In the current baseline
vehicles the alternator efficiencies do vary with the temperature and load.
Specific suggestions regarding models that need more detailed coverage: Has AC
compressor load been considered in any of the simulations? In some of the new cycles being
proposed by EPA, it is required that AC remains ON throughout the cycle. Hence,
management of the AC load is very critical.
Ricardo (201 1) developed baseline vehicle simulations for 2010 vehicles for which EPA fuel
economy data were available (page 30). "For the 2010 baseline vehicles, the engine fueling
maps and related parameters were developed for each specific baseline exemplar vehicle."
(page 25). Even though these are production vehicles, the models and maps used were not
described (including whether they were derived from actual measurements or models) and
they were not provided in the report so that their appropriateness could not be assessed.
Table 7.1 shows the calculated vs. EPA test data for the baseline vehicle fuel economy
performance. This table should include percentage variation of the model calculations vs.
the test data. The agreement of the model with the test data is within 1 1 %, but this is a
larger error than some of the incremental changes shown in Appendix 3. A closer agreement
would have been expected.
                     23

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question Specific Comment R .
Topic Assumption/Topic E™r* Round Reviewer Comment
Simulation
methodology
Simulation
Baseline vehicle
model validation
results
Cold Start
methodology Correction















Simulation
Methodology














Constraints
methodology




206
384
















41



1
2
















1



Wade
Midlam-
Recommendation: A closer examination of the reasons for the up to 1 1 % discrepancies
between the models and baseline vehicles' EPA fuel economy test data should be
undertaken so that the models could be refined to provide better agreement.
The correction used to adjust fuel economy for cold start is described in this presentation.
Mohler The method is based on two pieces of information:! A set of three tests from a single















Assanis
vehicle's instantaneous fuel multiplication correction factor2. A piece of EPA data which
shows a fleet-wide average for 2007 of the instantaneous fuel multiplication correction
factorThe instantaneous fuel multiplication correction factor is not described in the
presentation, however, it is assumed to be the sum of the "short term fuel trim" and "long
term fuel trim." If this is the case, then this value doesn't correlate to increased fuel
consumption, but rather, to errors in the injector characterizations, fuel property assumptions,
and air estimation algorithm in the engine controller. The engine controller is going to
maintain stoichiometry based on oxygen sensor measurements, these trim values are the
simply the feedback correction values required to do this based on the feedforward algorithm
in the ECU. By way of example, I could alter the fuel tables of an ECU by 15% which would
cause the feedback control system to correct by an opposite 15%. This would not change
the fuel consumption of the vehicle once the control system has corrected it, which would
happen in seconds. I don't disagree necessarily with the magnitude of the outcomes, since
they are based mostly on EPA bag fuel economy data. If I am correct in my understanding of
the correction factor then the method is not valid.
Specific suggestions regarding models that need more detailed coverage: There is no
discussion in the report that discusses the constraints on the combinations that can be


implemented in real life. For example, would a multi-air system that is currently designed for
small size engines work for a full size car?
                     24

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question Specific Comment R .
Excerat Reviewer Comment

Simulation Engines and
30
methodology Engine Models














Simulation
(Sections 4.1 and
6.3)












Engines and
methodology Engine Models





Simulation
(Sections 4.1 and
6.3)



Engines and
methodology Engine Models
(Sections 4.1 and





6.3)


















31






32







1















1






1







Assanis
Specific suggestions regarding models that need more detailed coverage:
It is not clear whether the engine maps in the simulation tool were generated based on














Assanis
simulations or existing experimental data, somehow fitted and scaled to the various
configurations. In general, the explanation on how maps were obtained is vague for such an
important component. In one section, the report states that the fueling maps and other
engine model parameters used in the study were based on published data. If so, it would be
nice to have a list of the published materials that have been used as the resource. In Section
4.2, the report states that the performance of the engines in 2020-25 were developed by
taking the current research engines and assuming the performance of the 2020 production
engines will match that of the research engine under consideration. Does this assumption
take into account the emission standards in 2020, and do the current research engines
match those emission standards? What is the systematic methodology that has been
adopted to scale the performance and fuel economy of current baseline engines to engine
models for 2020-25? Also, the report lacks detail concerning the methodology of
extrapolating from available maps to maps reflecting the effects on overall engine
performance of the combination of the future technologies considered.
Specific suggestions regarding models that need more detailed coverage: The report lacks
detail on the specifics on the different engine design and operating choices. For instance,





Assanis







what was the compression ratio (and limit) that was used? What is the equivalence ratio, or
range considered, for the lean burn engine? How much EGR has been used across the
speed and load range? What constraints, if any, were applied to the simulations to account
for combustions limitations such as knock and flammability limits? The NOx
aftertreatment/constraints section could also be expanded.
Specific suggestions regarding models that need more detailed coverage: In cases where
engine models have been used to generated maps, how was combustion modeled? For
instance, discussion is made as to the heat transfer effect resulting from surface to volume
changes connected to downsizing. More detail on the heat transfer assumptions that go into
the applied heat transfer factor would be helpful. Was heat transfer modeled based on
Woschni's correlation? What about friction scaling with piston speed? This would change
with stroke at a constant RPM. Also friction would change with the number of bearings and
cylinders.
                     25

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Specific
Assumption/Topic
Intelligent Cooling
Systems (Section
4.3.1)
Intelligent Cooling
Systems (Section
4.3.1)
Intelligent Cooling
Systems (Section
4.3.1)
Scaling
Methodology
Review
Section 3.4 CSM
Approach
Section 4. 1.1
Advanced
Valvetrains
Section 4.2.1
Stoich Dl Turbo
Comment
Excerpt
Mn
34
35
36
393
77
82
83
Review
Round
1
1
1
2
1
1
1
Reviewer
Assanis
Assanis
Assanis
Midlam-
Mohler
McBroom
McBroom
McBroom
Comment
Specific suggestions regarding models that need more detailed coverage: The report
describes intelligent cooling systems, but does not provide any estimates of the anticipated
reductions in fuel consumption over the FTP cycle, though related papers have been
published in the open literature.
Specific suggestions regarding models that need more detailed coverage: Sizing of various
cooling components plays a very crucial role in fuel economy predictions. The report does
not provide any detail on how the optimum cooling flow required for a given engine-
transmission combination was determined. This would significantly affect the oil, coolant and
transmission oil pump RPMs, which would in turn significantly change the accessory loads.
Specific suggestions regarding models that need more detailed coverage: In addition, the
report does not have any discussion on how modified cooling components (radiator,
condenser, etc.) would be sized for more efficient powertrains. For instance, a more efficient
engine that would reject less heat would likely need a smaller radiator and lesser airflow
through the radiator; hence, the grill opening could be reduced to cut down on aero drag. A
high efficiency transmission will not reject a lot of heat to the transmission oil; thus, a smaller
transmission oil cooler could be used.
With one exception, the scaling methodology appears to be sound given the information
provided in the presentation. The curve used to adjust BSFC with displacement ratio is not
supported with data or any citation of where it originated. The motivation for this correction
seems valid, however, it needs to be supported with data.
Is the CSM approach used in other applications? If so it would be helpful to give citations. If
it was developed by Ricardo, that should be stated. The discussion refers to physics based
models, but other than that very little about the type of modeling is discussed. I recall on the
phone call that lumped parameter models were mentioned. There is no discussion of that.
There is no explanation of how CPS and DVA systems were modeled. There was only a
description of what CPS and DVA is.
Quantify how did the cooled exhaust manifold/lower turbine inlet temp improved the BSFC
map. This is a good example of technology interaction. ..how did the radiator size grow to
accommodate the additional heat rejection; how did the frontal area of the vehicle change to
accommodate the larger radiator?
                     26

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Topic
••
Simulation
methodology
Simulation
methodology
Simulation
methodology
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methodology
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Section 4.2.2 Lean
Stoich Switching
Section 4.2.4
Atkinson Cycle
Section 4.2.5
Advanced Diesel
Section 6 Vehicle
Models
Transmission
Models (Section
6.4)
Transmission
optimization
Transmission
optimization
Turbocharger
systems (Section
4.1.3)
Vehicle model
issues
Vehicle model
issues
Comment
Excerpt
hi.
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McBroom
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McBroom
McBroom
Assanis
Wade
Wade
Assanis
Wade
Wade
Comment
This type of tech points to one of the dangers of optimizing configuration/technology/control
strategy to the drive cycles; that is that it has the potential to over constrain the design and
effect the "real world" performance/fuel economy.
How do the 2020-2025 maps differ from the 2010 maps?
Why were only the benefits of improved pumping losses or friction considered? What
improvements were assigned to these benefits? Was it across the board or regional? What
about advanced boosting technology for these engines?
No discussion of how driveline inertia is handled. This is important in forward-looking
models.
Specific suggestions regarding models that need more detailed coverage: The transmission
efficiencies vary by almost 10-15% based on the transmission oil temperature. How have
these effects been modeled?
A transmission shift optimization strategy is presented in the report and the results are shown
in Figure 6.1 (page 28). This figure shows very frequent shifting, especially for 4th, 5th and
6th gears.
Issue: Optimized shift strategies of the type used by Ricardo (201 1) have been previously
evaluated and found to provide customer complaints of "shift busyness". Customers are
likely to reject such a shift strategy.
Specific suggestions regarding models that need more detailed coverage: There is no
discussion of turbocharger efficiencies and their range. Did the simulations assume current
boosting technologies? Were maps used for this simulation or some other representation?
Was scaling used? What were the allowed boost levels?
Although the report described the major powertrain subsystems included in the vehicle
models (page 24), a description of the vehicle model was not provided.
Issue: A description of how aerodynamic losses, tire rolling losses and weight are handled in
the model was not provided.
                     27

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 Excerpt
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Reviewer
Comment
Simulation
methodology
Simulation
methodology
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Warm-up
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Specific suggestions regarding models that need more detailed coverage: This section talks
about using engine warm-up profile during the cold start portion to ascertain additional
fueling requirements. It talks about a correction factor to account for this additional fuel. How
was this factor determined? Has a different correction factor been used for various engines?
For instance, for a lean-burn engine that reject less heat, the oil warm-up is slower compared
to a baseline engine. Was a new heat rejection map generated to account for start-up
enrichment while modeling the warm-up? What is the ambient temperature that has been
considered while performing the FTP 75 fuel economy test? Have the viscous effects of
engine oil considered in the warm up simulation? How have the friction losses for various
valvetrain engine combinations been modeled?
The RSM approach is certainly a good way to provide quick access to wide range of results,
but it has the limitation that a large number of assumptions have to be made ahead of time in
order to determine the design space. Also, creating these encompassing RSM's requires a
significant amount of simulations, and all the results will not necessarily be of interest. If a
more flexible model/simulation was created and coupled to a user-friendly interface, users
might be able to obtain and analyze the desired results instead of being constrained by the
design space previously determined.
Even though the authors attempt to describe the simulation methodology and assumptions in
the report, it lacks details of the models employed, which makes it hard to determine if
refinements need to be made, or even if more appropriate models/methods should be used.
It is understandable that, due to the proprietary data, it is not possible to present
everything. However, without any of this information, the RSM results are more difficult to
interpret.
Some assessment of the model uncertainty would be helpful. This could be a qualitative
rating assigned by the advisory committee or a more rigorous method could be used.
More detail on the types of models is required. Do some models use first principals of
physics and others lumped parameter?
ANOVA or some other analytical approach to consider technology interactions needs to be
deployed.
It says a statistical analysis was used to correlate variations in the input factors to variations
in the output factors. This is ambiguous. What analysis method was used? Where is it
reported? I didn't see anything in the results about this. It was used to generate the RSM,
but what was the measure of fitment? How did the RSM fit compare from vehicle config to
                                                               28

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 Excerpt
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Comment
                                                              vehicle config.

Simulation
methodology
Simulation
methodology
Simulation
methodology
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McBroom
McBroom
McBroom

Ricardo's expectation for pace and direction: I thought there was an advisory committee
making these decisions. I'm surprised that they think boost will be limited to 17-23bar.
There are several types of rolling resistance models, what type was used?
Was coast-down data from the baseline vehicles obtained or where the coefficients of rolling
resistance and Cd modified to get the data to match?
Regarding engine downsizing, I'm not sure that the scaling approach applies to boosted
engines, especially engine with multiple compressors as well as DVT and CPS technology.
Turbo lag applied as a first order transfer function with a time constant. How was the time
constant selected? Was it validated? How was the improvement attributed to turbo
compounding modeled?
How was a 20% reduction in engine size for the nominal hybrid engine arrived at? Even for
the micro-hybrid (engine start/stop)?
"These summary results. . . .used to assess the quality of the simulation. . . ." Where is the data
for this assessment published? What were the criteria that said pass or fail?
Transmission Model: Ricardo (201 1) describes an approach that asserts that using an
average efficiency value vs a 3D efficiency map yields insignificant differences over the
CAFE drive cycles, but offers no results to validate the claim.
Transmission Model: Ricardo (201 1) offers no discussion of how inertial changes are
managed during shifts. This may have greatest impact on the shift strategies where the
transmission shifts to put the engine at the best bsfc for the given load.
Hybrid: I don't see any effort to model motor/inverter temperature effects. One would expect
significant degradation of motor capability as things heat up during normal operation.
Regen Alternator: Alternator model is too simplistic. On average the efficiency is too high as
identified and it's unrealistic to assume that the battery will be able to accept 100% of the
charge.
                                                                29

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Verbatim Peer Reviewer Comments in Response to
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Topic
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
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Comment
Excerpt
Mn
414
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297
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2
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McBroom
McBroom
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Comment
EHVA: The paper addresses the potential of the technology nicely. Since it was published in
2003 has any more recent work been done to address the durability and issues brought up in
the conclusions?
Accessories: I don't see any discussion on the treatment of accessories. I believe from my
review of the previous material, that the authors assume that all accessories will be electric. I
think that engine driven accessories will play a key role in 2020.
The vehicle model is reported as "a complete, physics-based vehicle and powertrain system
model" - which it is not. The modeling approach used relies heavily on maps and empirically
determined data which is decidedly not physics-based. This nomenclature issue aside, the
model is not described in sufficient detail in the report to make an assessment in this area.
An excellent example of this is the electric traction drives and HEV energy storage system for
which the report mentions no details, even qualitative ones, on the structure of the models.
The vehicle simulator is used to generate several thousand simulations using a DOE
technique. This data is then fit with a neural-network-based response surface model in
which the "goal was to achieve low residuals while not over-fitting the data." This response
surface model then becomes the method from which vehicle design performance is
estimated in the data analysis tool. In this case, the response surface model is nothing more
than a multi-dimensional black-box curve fit. There was no error analysis given in the report
regarding this crucial step. By way of example, the vehicle simulator could provide near
perfect predictions of future vehicle performance; however, a bad response surface fit could
corrupt all of the results.
Provide error metrics for the neural network RSMs (i.e. R2, min absolute error, max absolute
error, error histograms, error standard deviation, etc.) before combining the fit and validation
data sets.
Provide the error metrics described above for the RSMs after combining the fit and validation
data sets.
Provide validation that the data analysis tool correctly uses the RSM to predict results very
close to the source data (i.e. demonstrate the GUI software behaves as expected).
                     30

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Comment
Simulation
methodology
Simulation
methodology
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Ricardo (201 1) simulated dynamic vehicle physical behavior using MSC Easy5TM software
with 10 Hz time resolution. This software and the time resolution are appropriate for the
computations to show the effect of component interactions on vehicle performance. 10 Hz
time resolution is sufficient to capture both driver behavior and vehicle response. Should the
application of information technology, as is being implemented, as a means of vehicle control
for reducing fuel consumption become a future strategy, the model should be able to provide
a suitable simulation.
Drivetrain synergistic effects seem to be predicted reasonably. This was demonstrated by
calculation of fuel economy of the baseline vehicles and comparison with EPA certification
test data. The model does not seem to have the capability to capture vehicle weight-
drivetrain synergistic effects. Vehicle weight reductions associated with drivetrain efficiency
improvements are input rather than modeled internally. This is an important deficiency.
Similarly, from the Complex System Tool, weight reductions do not seem to result in
reduction in engine displacement.
Ricardo, Hybrid Battery Warm Up Model Validation - Update, Light Duty Vehicle Complex
Systems Simulation ,EPA Contract No. EP-W-07-064, work assignment 2-2, 15 Mar 10, 5 p.
proprietary) This report presents a simple battery heat transfer model for battery warm up
and compares with Argonne National Laboratory of the previous document.Comment: Model
produces adequate prediction of battery temperature.
Trapp, C., et al., Lean boost and NOx— strategies to control nitrogen oxide emissions, (no
date), 23 p. Technical paper that describes lean burn direct injection (LBDI) engines, SCR
NOx control, and more. Includes some emission control cost data.
Comment: Not clear how this related to Ricardo's model development for EPA.
Ricardo, Scaling Methodology Review, 19 Jan 10, 9 p. This document explains the scaling
methodology used in the EASY5 vehicle model.
Comment: This description in clear and useful.
Takoaka, T., et al., Toyota, Super high efficient gasoline engine for Toyota hybrid system,
(no date), 16 p. This paper describes the hybrid system, 1C engine interaction that allows
increased 1C engine efficiency.
Comment: Of general interest but application to the model not clear.
                                                               31

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Topic
Simulation
methodology
Results
Results
Results
Results
Results
Results
Results
Results
Results
Specific
Assumption/Topic

5.2 Vehicle
Configuration and
technology
combinations
6.1 Baseline
Conventional
Vehicle Model
6.3.1 Engine
Warmup
Methodology
6.4 Transmission
Models
6.5 torque
Converter models
6.6 Final Drive
Model
6.7 Driver Model
7.1 Baseline
Conventional
Vehicle Models
8.1 Evaluation of
Design Space
Comment
Excerpt
Mn
198
105
106
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Wade
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
Comment
Concern: Methodologies used in simulating the subsystems and the overall vehicles were
not provided, so that the validity and applicability of these methodologies cannot be
assessed.
Also there is no scientific or objective reason given for the DoE ranges. It appears that I can
make any vehicle 60% less mass, 70% less rolling resistance etc.... This will skew the results
towards that end of the DoE, when they may not be practically achievable.
Results were compared to the EPA Vehicle Certification Database. These results often
include correction factors and allowances that aren't documented on the sticker.
Recommend that actual testing be run to perform the benchmark.
Were there hot and cold engine maps? No mention.
Fig 6.1 appears to be a comparison of desired cvt ratio vs desired 6spd gear ratio. Should be
stated as such. The shift logic controller should take into account the time to shift and
whether or not the desired shift is achievable.
The lockup strategy seems very conservative. Large gains are achievable with more
sophisticated control and are in use today.
Only discussed the baseline, what improvements for 2020 and what final drive selection
criteria for the future vehicles was used?
How was the soak modeled? Were there hot engine maps and cold engine maps?
Better definition of what "acceptably close" means. This doesn't meet the criteria for
objectivity. Something like, "the advisory committee determined that the baseline models had
to predict within x% to be usable for this study."
Why was Latin hypercube sampling methodology picked over other sampling methods?
While it's attributes are mentioned, what other methods were considered?
                     32

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Results
Results
Results
Results
Results
Results
Results
Results
Results
Specific
Assumption/Topic
8.2 RSM
9.1 Basic Results
9.3 Exploration of
the Design Space
Issue with CSM
Issue with CSM
Other issues
Other issues
Other issues
Overview of results
Comment
Excerpt
M«
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Reviewer
McBroom
McBroom
McBroom
Wade
Wade
Wade
Wade
Wade
Wade
Comment
A description of how the neural network is deployed is needed, only the why it was used is
discussed in this section. What were the best fit criteria? What types of equations did the
neural net have to play with? Where are the fit's published? How was it determined that the
"one fit per transmission" was the best way to go?
Why 10Hz sampling rate? By what criteria was a run considered good vs bad?
If boundaries of acceptable performance were applied, a considerable number of simulation
runs could be eliminated.
Issue: The technology "package definitions" (page 22 and 23) precluded an examination of
the individual effects of a variety of technologies.
Some examples where the model did not allow a build up of comparison cases are:
- Baseline engine with AT-2010 to AT-2020 to DCT
- Baseline engine without stop-start to with/stop-start
The Advanced Diesel does not appear to be modeled for the Standard Car and Small MPV
(page 46 and 47), yet no reason was provided.
The P2 and PS hybrid system was not modeled for the LHDT (page 47), yet no reason was
provided.
When the baseline cases were run in the Complex Systems Model, incorrect values of
displacement and architecture were shown in the output.
o As an example shown on the attached chart (copied from the output of the CSM), the
baseline for the Standard Car with a 2.4L engine shows a displacement of 1 .04L.
o For the same example, the architecture is shown as "conventional SS", whereas the
baseline was understood to not have the stop-start feature (page 22, Table 5-2).
The results from this work could be useful in evaluating possible GHG emission reductions in
the 2020-2025 timeframe if the issues throughout this peer review were addressed and the
recommendations in Item 5 (below) were implemented. However, even if the foregoing
deficiencies were resolved, the foregoing caveat that there are numerous technologies that
have potential for reduced GHG emissions that were not included in this study must be
recognized (see Item 1B, above).
                     33

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Verbatim Peer Reviewer Comments in Response to
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Topic
Results
Results
Results
Results
Results
Specific
Assumption/Topic
Sample runs of
CSM
Sample runs of
CSM
Sample runs of
CSM
Sample runs of
CSM
Sample runs of
CSM
Comment
Excerpt
Mn
212
213
214
215
216
Review
Round
1
1
1
1
1
Reviewer
Wade
Wade
Wade
Wade
Wade
Comment
In the review process, several sample runs of the Complex Systems Model (CSM) for the
Standard Car (Toyota Camry) were made and the results are shown in the attached chart (at
the end of this peer review) and summarized below: Baseline engine with AT6-2010 to
Stoichiometric Dl Turbo, Stop-Start, AT8-2020-38.7% improvement in M-H mpg- Lumsden,
et al. (2009) identified a 25-30% improvement in mpg for a 50% downsized, Dl, Turbo
engine. The remaining 9-14% potentially could be explained by stop-start and the change
from AT6-2010 to AT8-2020 (although the details of the systems and the models used would
be needed to make this assessment).
In the review process, several sample runs of the Complex Systems Model (CSM) for the
Standard Car (Toyota Camry) were made and the results are shown in the attached chart (at
the end of this peer review) and summarized below: AT8-2020 to DCT
-3.3% improvement in M-H mpg
- This improvement appears reasonable.
In the review process, several sample runs of the Complex Systems Model (CSM) for the
Standard Car (Toyota Camry) were made and the results are shown in the attached chart (at
the end of this peer review) and summarized below: Stoichiometric Dl Turbo with Stop-Start
to P2 Hybrid
- 18.2% improvement in M-H mpg
- This improvement appears reasonable.
In the review process, several sample runs of the Complex Systems Model (CSM) for the
Standard Car (Toyota Camry) were made and the results are shown in the attached chart (at
the end of this peer review) and summarized below: Stoichiometric Dl Turbo with Stop-Start
to PS Hybrid
- 1 1 .1 % improvement in M-H mpg
- A detailed explanation of the differences in the improvements between the P2 and PS
hybrids should be provided in the report, especially considering that the P2 hybrid has better
fuel economy and uses a 70% smaller electric motor (24 vs. 80 kW).
In the review process, several sample runs of the Complex Systems Model (CSM) for the
Standard Car (Toyota Camry) were made and the results are shown in the attached chart (at
the end of this peer review) and summarized below: Stoichiometric Dl Turbo PS Hybrid to
Naturally Aspirated Atkinson CPS Hybrid
- Loss of 2.3% M-H mpg (From Stoichiometric Dl Turbo PS Hybrid)
- The details of the Naturally Aspirated Atkinson CPS Hybrid should be provided to explain
                     34

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Comment
 Excerpt
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Round
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Comment
                                                               the nearly equal fuel economy to the Stoichiometric Dl Turbo PS Hybrid.

Results
Results
Results
Results
Results
Results
Results

Sample runs of
CSM
Section 4.4. 11
Lubrication
Section 4.4.6
Shifting Clutch
Technology
Section 4.4.7
Improved
Kinematic Design
Section 4.5.1
Intelligent Cooling
System



217
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Wade
McBroom
McBroom
McBroom
McBroom
Assanis
Assanis

In the review process, several sample runs of the Complex Systems Model (CSM) for the
Standard Car (Toyota Camry) were made and the results are shown in the attached chart (at
the end of this peer review) and summarized below: Stoichiometric Dl Turbo PS Hybrid to
Naturally Aspirated Atkinson DVA Hybrid
- 2.1% M-H mpg improvement in M-H mpg (From Stoichiometric Dl Turbo PS Hybrid)
- The details of the Naturally Aspirated Atkinson DVA Hybrid should be provided to explain
the nearly equal fuel economy to the Stoichiometric Dl Turbo PS Hybrid
Assumes a sweeping improvement without identifying a clear rationale. . .doesn't appear to
describe a scientific or objective approach.
"The technology will be best suited to smaller vehicle segments because of reduced
drivability expectations" - not in the US market.
Assumes a sweeping improvement without identifying a clear rationale. . .doesn't appear to
describe a scientific or objective approach.
The system as described seems more appropriate for regulated emissions reduction
opportunity rather than fuel economy or GHG. I think these systems enable engine control
strategies that aren't part of this study that would have a greater impact on fuel economy
than warming up the engine faster.
For the vehicle performance simulation results shown in Table 7.1, were there any significant
adjustable parameters used to fit these vehicles?
Even though it appears that the validation results from the simulation have "acceptably" close
agreement with the test data, there are up to 15% off. Even for the small car where all data is
available, the error is on the order of 5%. These discrepancies are usually not negligible and
should be taken into account when conclusions are drawn from the results, especially if
regulation is to be proposed based on these.
                                                                 35

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Verbatim Peer Reviewer Comments in Response to
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Topic
Results
Results
Results
Results
Results
Results
Results
Results
Results
Specific
Assumption/Topic









Comment
Excerpt
Mn
44
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109
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113
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Round
1
1
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Reviewer
Assanis
Assanis
Assanis
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
Comment
There is also no baseline hybrid configuration and no validation of the hybrid model. Due to
the increased complexity of these vehicle systems, it is important to ensure the parameters
and assumptions are valid.
It would be desirable to include a complete test case with the appropriate inputs, analysis
and outputs as part of the report. The sample results presented in figures seem to have been
included to indicate the RSM and Data Visualization Tool's capabilities, but they do not
provide a complete picture from which to draw solid conclusions.
The plots showing simulation results in blue, red, etc. could be better labeled (i.e. legends
could be inserted in the plots) and possibly presented in a relative format indicating percent
improvements over the baseline engine rather than absolute numbers. This is more of a
personal choice for a more clear representation of the predicted improvement, rather than
stating that there is anything wrong with the current representation.
What are the shift optimizer inputs? What are it's basic decision criteria?
There is no discussion of engine downspeeding.
There is no discussion of gear ratio selection.
What was the basis for the minimum rpm's for lockup sited? Should be based on lugging the
engine. The controller should recognize when it needs to unlock the TC based on the
engines ability to keep up.
On the performance runs, a few tenths of a second represent measurable difference in
engine torque for example.
Motor Efficiency Maps: I am having trouble believing that motor efficiency will stay above
90% once temperature effects are accounted for. It also seems to me that these numbers
don't include the inverter even though the authors say that it does. The UQM maps seem
more reasonable. As stated in a previous comment, I believe that the cost reductions
needed for motors will drop their efficiencies in the future.
                     36

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Topic
Results
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Comment
Excerpt
Mn
417
298
373
374
375
Review
Round
2
1
1
1
1
Reviewer
McBroom
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Comment
After reading the papers and presentations I come to the assumption that the papers were
used to guide the selection of technology, but it's not clear which maps were generated from
model and which maps were generated in the test cell. It's evident that there is a heavy
concentration on engine technology and the fidelity of the engine models, which is
appropriate. I have a slight concern about the impression I'm left with; that there is not much
attention to the interaction of systems effects. This is most likely because of cost and
availability of data. I would like to see the EPA articulate a process for looking at system
interactions, continuous improvement and model compatibility. For example if the study
were to run over several years the researches should feel confident comparing a result
generated with the models in 2013 to modeling results generated today.
The third charge questions deals with the validity and the applicability of the resulting
prediction. The difficulty in this task is that it is an extrapolation from present technology that
uses an extrapolation method (i.e. the model) and a set of inputs to the model (i.e. future
powertrain data.) Since it is not possible to validate the results against vehicles and
technology that do not exist, one can only ensure that the model and the model inputs are
appropriate for the task. Because of the lack of transparency in the model and inputs it is
difficult to make any claims regarding the results. In trying to validate results, one example is
cited in the body of the report that shows the baseline engine getting superior HWFET and
US06 fuel economy than all of the other non-HEV powertrains with other factors being the
same - this leaves some skepticism regarding the results.
As outlined in the executive summary, it was not possible to answer the charge questions
provided for this peer review due to lack of completeness in the report. Thus, this report was
aimed at providing feedback on what information would be helpful to allow a reviewer to truly
evaluate the spirit of the charge questions. With the above in mind, the following conclusions
are made.
The modeling approach describe in the report could be appropriate for the simulation task
required and is generally consistent with approaches used by other groups in this field. The
conclusions from the report could very well be sound; however, there is insufficient
information and validation provided in the report to determine if this is the case. The
technique used to analyze the mass simulation runs could also be sound, although the
accuracy of the response surface model is not cited in the report.
The process of arriving at the performance of the future technologies is not well described.
                     37

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Results
Results
Results
Results
Results
Results
Results
Results
Results
Completeness
Completeness
Specific
Assumption/Topic









4.4 Transmission
Technologies
4.4.1 Automatic
Transmission
Comment
Excerpt
Mn
376
377
378
379
380
5
6
446
447
136
138
Review
Round
1
1
1
1
1
1
1
2
2
1
1
Reviewer
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Sawyer
Sawyer
Sawyer
Sawyer
McBroom
McBroom
Comment
The majority of models are only described qualitatively making it hard or impossible to judge
the soundness of the model.
Some of the qualitative descriptions of the models indicate that models do not consider some
important factors.
Because of the qualitative nature of the model descriptions, there is a major lack of
transparency in the inputs and parameters in the models.
Where precise value(s) are given for parameters in the model, the report generally does not
cite the source of the value(s) or provide validation of the particular value.
Validation of the model and sub-models is not satisfactory (It is acknowledged that many of
these technologies do not exist, but the parameters and structure of the model have to be
based on something.)
Performance calculations tied to the FTP, HWFET, and US06 test cycles do not adequately
capture vehicle behavior under real-world operation. Therefore, technologies that address
improving fuel economy under real-world operation are either excluded or their contribution
not included. The application of a 20% reduction in fuel economy to the FTP75 bag 1 portion
of the drive cycle for 2010 baseline vehicles and 10% for 2020-2025 is crude, arbitrary, and
treats only one of many problems with the driving simulation in the test cycles. Test cycle
difficulties carry over into the simulation of hybrid control strategies.
It is conceivable that BEVs and PHEVs (and less likely FCEVS) will be a significant part of
the 2020-2025 vehicle fleet. That they are excluded from the model is a deficiency.
Lymburner, J.A., et al., Fuel consumption and NOx Trade-offs on a Port-Fuel-lnjected SI
Gasoline Engine Equipped with a Lean NOx Trap, 4 Aug 09, 20 p. This technical paper
examines the trade-off between NOx control and C02 emissions.
Comment: Good work but relevance not clear.
Lotus(?), (from Kapus, P.E. et al., May 2007), Comparison to other downsized engines This
one figure is a partial engine map with context vague. Comment: Significance is not clear.
What types of CVT's were in the original mix? Toroidals, push-belts, Miller?
No logical explanation for the 20-33% improvement... how was this number arrived at?
                     38

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Specific
Assumption/Topic
4.4.10 Super
Finishing
4.4.3 Wet clutch
4.5 Vehicle
Technologies
5.2 Vehicle
Configuration and
technology
combinations
6.8 Hybrid Models
Section 2
Objectives
Section 3.3 Ground
Rules
Section 3.3
Technology
Selection Process
Section 4.
Technology
Review and
Selection
Section 4.1. 2 Dl
Fuel Systems
Section 4. 1.3
Boosting Systems
Comment
Excerpt
hi.
140
139
141
142
145
122
123
124
127
131
132
Review
Round
1
1
1
1
1
1
1
1
1
1
1
Reviewer
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
Comment
How much improvement is attributed to super finishing?
It said these were expected to be heavier, cost more and be less efficient than DCT's so why
where they included?
No values for mass, rolling resistance or drag given. No discussion of the improvement
possibilities. This would be a good place to use historical trends for vehicle mass reduction,
aero improvements and parasitic loss improvement.
While the tables show the vehicle configurations, more discussion regarding the selection
criteria for each vehicle is warranted. In some cases this discussion was attempted in the
technology sections, but I don't think it should go there.
Too much data is missing. What were the pack voltages? What were the battery
technologies? Was there only one or more? Other than improved resistance, what other
future improvements were included, like improved power density, improved usable SOC
range? What was the control strategy for each type?
A discussion of appropriate/anticipated use of the results is required.
How did the group arrive at the seven vehicles? While it show comprehensiveness, it's
possible to see that there could be some overlap. If one looks at the engine and
transmissions packages available in these vehicles already you can see the overlap.
Reducing the number of vehicles might save on the number of runs you'll need to make.
Who is on the Advisory Committee? Is it independent? How did the program team come up
with the comprehensive list of potential technologies? (From the phone call it sounded like it
was based on what models Ricardo (201 1) had in their library. This is concerning.)
Regarding qualitative evaluation of technology "Potential of the technology to improve GHG
emissions on a tank to wheels basis", since this was a qualitative assessment I think it would
be better to include well to wheels.
No discussion of Dl control strategy. How was it selected? Was there a separate optimization
of Dl control or was it one size fits all?
It says that other boosting systems were included in the study, but only turbocharging is
discussed.
                     39

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Specific
Assumption/Topic
Section 4.3 Hybrids
Section 4.3.1 Micro
Hybrids
Section 4.3.2 P2
Hybrid
Section 6 Vehicle
Models
Sections 4.1 and
4.2







Comment
Excerpt
hi.
133
134
135
143
130
47
48
49
50
125
126
128
Review
Round
•
1
1
1
1
1
1
1
1
1
1
1
Reviewer
McBroom
McBroom
McBroom
McBroom
McBroom
Assanis
Assanis
Assanis
Assanis
McBroom
McBroom
McBroom
Comment
Don't see any data on the battery technology, battery management, SOC control strategies.
No discussion of regen braking strategies.
It is implied that electrified accessories aren't used in this configuration. I don't see that as
the case.
No discussion of why DCT was only transmission used for P2 hybrids instead of CVT and
AMI.
No discussion of how driveline inertia is handled. This is important in forward-looking
models.
There's no descriptions of the models. There are only descriptions of the technologies and
their perceived benefits. The reader has to assume that the same modeling approach was
used to model each technology, but I know from personal experience this is very difficult and
most likely not the case.
Some of the aspects lacking form the report have already been mentioned and discussed in
the relevant sections.
In general, the report provides a fair description of the modeling process. Unfortunately, there
are no equations, plots or maps showing any specific modeling item, thus making this part of
the report vague.
It might be possible to shorten the descriptions related to the individual technologies
implemented and their improvements and add more details on how they have been modeled.
People using this tool will most likely not use the brief descriptions of the various
technologies to draw conclusions and make decisions.
The "Conclusions" section of the report should be renamed "Summary" since it does not
present any actual conclusions based on the results, but it does provide a summary of the
project.
It said there was a comprehensive list of technologies that the group started with, that list
should be shown and a comment on why it wasn't included.
Why wasn't HCCI technology considered? From the publications this seems to be a
candidate for production in the next 10 yrs.
Regarding "Current (2010) maturity of the technology", how was maturity ranked?
                    40

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Specific
Assumption/Topic








Comment
Excerpt
M«
129
137
144
146
147
148
418
299
Review
Round
1
1
1
1
1
1
2
1
Reviewer
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
Midlam-
Mohler
Comment
Citations required for statement " SI engine efficiency to approach Cl efficiency in the time
frame considered" This represents relatively large gains in SI technology compared to Cl,
however EU and Japanese engine companies are making big improvements on Cl as well.
No transmission data was shown. No mass, no inertia to efficiency maps, no gear ratios.
There are several types of rolling resistance models, what type was used?
Load leveling the engine by charging the batteries has been shown to not be a very good
idea because the round trip efficiency hit is a killer. Should only be used when SOC falls
below a certain level.
We're left to assume that SOC leveling is accomplished, but there is no description of how?
Was an EPA/SAE method used.
When it comes to GHG reductions why weren't plug-in hybrids considered?
Hybrid: Ricardo (201 1) asserts that electric machine design activities of the future will most
like concentrate around cost reductions; however I see machine efficiency dropping in order
to meet cost reductions. Therefore I think it premature to assume that efficiency will stay the
same and cost will drop.
Based on the above, it is clear that this reviewer feels the report is inadequate at describing
the entire process of modeling work from input selection to results. There was not a single
subsystem that was documented at the level desired. It is understood that, in some cases,
there are things of a proprietary nature that must be concealed. As a trivial example, the
frontal area of the vehicle classes does not seem to be anywhere in the report or data
analysis tool. This is one parameter amongst hundreds excluding the real details of the
models (i.e. equations or block diagrams), methods used to generate engine maps, details
on control laws, etc. On the topic of proprietary data, there are many ways of obscuring data
sufficiently that can demonstrate a key point (i.e. simulation accuracy) without compromising
confidentiality of data - this should not be a major barrier to providing some insight into the
inner working of the simulator.
                    41

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Specific
Assumption/Topic







Comment
Excerpt
Mn
7
8
427
433
434
435
436
Review
Round
1
1
2
2
2
2
2
Reviewer
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Comment
The selection of drivetrain technologies (other than the electric storage technologies) is
comprehensive. The qualitative description of the drivetrain technologies is complete and
clear, but quantitative performance data are missing. Transparency in the actual
performance data is entirely lacking. This includes engine performance maps, shift
strategies, battery management in hybrids, and more. That much of that data is proprietary to
the companies that generated it and/or to Ricardo (201 1) is a problem for what is proposed
as a regulatory tool.
The assumptions are difficult to extract from the text.
Ricardo, Assessment of Technology Options, Technologies related to Diesel Engines, 23
Nov 09, 17 p. Overview predicts continuation of low uptake in the U.S. IDA and LOT
markets. Review deals with various engine technologies to improve efficiency. Individual
improvements <1-5%. Most promising is electric turbo-compounding (bottoming cycle to
recover exhaust thermal energy to produce electricity). Comment: Individual technology
assessments seem reasonable. There is no analysis of integrating several technologies.
Ricardo, Future Engine Friction Assessment— Response to Action Item Question SI Engine
#4, 18 Feb 1 1, 4 p. (proprietary) Projects continued reduction in engine friction, 2010--2020.
Comment: Data provide confirm projection.
Ricardo, Revised Follow-up Answers to 8 April 2010 Meeting with EPA and Ricardo, 19 Apr
10, 8 p. (proprietary) Presents fueling maps for several technologies.
Comment: Adds to documentation of engine map data.
Alger, T., Southwest Research Institute, Examples of HEDGE Engines, 2009, 4 p. Presents
engine map for a 2.4 L 14 High-Efficiency Dilute Gasoline Engine (HEDGE) engine and
compares with TC GDI engine, diesel engine.
Comment: Adds to documentation of engine map data.
Ricardo, Hybrid Controls Peer Review, 18 Feb 10, 31 p. (proprietary)
Review of hybrid control technologies for various architectures. Review of battery operation
in cold weather. Comment: Thorough description of technologies and their operation
characteristics. Battery discussion covers similar material to an earlier paper.
                    42

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Specific
Assumption/Topic






Comment
Excerpt
Mn
438
442
443
448
450
452
Review
Round
2
2
2
2
2
2
Reviewer
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Comment
Ricardo, Simulation Input Data Review, 4 Feb 10, 14 p. (proprietary) Described hybrid
architectures with emphasis on machine-inverter combine efficiencies, including efficiency
maps.
Comment: More data, seems reasonable.
Trapp, C., et al., NOx emission control options for the Lean Boos downsized gasoline engine,
(2 Feb 07), 34 p. Paper compares lean NOx trap and selective catalytic reduction
technologies. Includes some engine map data for NOx emissions. Includes cost data for
aftertreatment.
Comment: Good academic paper with useful data. Not clear what or how Ricardo (201 1)
used.
Trap, C., et al., NOx emission control options for the lean boost downsized gasoline engine,
(2 Feb 07), 27 p. Paper review international emissions regulation and technologies to meet.
Comment: This paper contains some of the same information as the preceding two.
Simulated date presented, again for SCR and LNT technologies.
Turner, J.W.G., et al. (2009), Sabre: a cost-effective engine technology combination of high
efficiency, high performance and low C02 emissions, Low Carbon Vehicles, May 09, IMechE
Proceedings, 14 p. This paper describes a technology for reducing COs emissions in a
downsized engine. The Sabre engine is a collaboration between Lotus Engineering and
Continental Automotive Systems.
Comment: Limited performance data provided.
Ricardo, Report on light-duty vehicle technology package optimization, 4 Dec 09, 32 p. This
is a progress report on Ricardo's modeling work for the EPA. A range of engine technologies,
hybrid technologies, transmission, and vehicle technologies are described.Comment: A
comprehensive list of near term technologies are included. The report is incomplete and
optimization apparent is not included here.
Ricardo, Response to questions regarding the generation of the diesel fuel maps for fuel
efficiency simulation, 16 Feb 10, 10 p. (proprietary) Paper answers a series of EPA questions
on how the diesel fuel maps were generated.
Comment: This is relevant information and provides a convincing description of the technical
basis for the diesel fuel maps.
                    43

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Completeness
Specific
Assumption/Topic









Comment
Excerpt
Mn
454
455
457
461
223
224
225
226
227
Review
Round
2
2
2
2
1
1
1
1
1
Reviewer
Sawyer
Sawyer
Sawyer
Sawyer
Wade
Wade
Wade
Wade
Wade
Comment
Ricardo, SCR as an Enabler for Low C02 Gasoline Applications, no date, 35 p. This
presentation describes technology and implementation for exhaust NOx reduction for lean
burn gasoline engines.
Comment: Comprehensive discussion of technology, but if and how inconcorporated in the
model not clear.
Ricardo, Simulation Input Data Review, 18 Mar 10, 17 p. (proprietary) This document reviews
the engine maps used in the model. Includes are examples of the baseline maps plus
modifications associated with a range of technologies. Data apply to all 7 vehicle classes.
Comment: This is the documentation that was missing in the earlier review material. Looks
reasonable and is reassuring.
Shimizu, R., et al., Analysis of a Lean Burn Combustion Concept for Hybrid Vehicles, 2009,
13 p. A technical paper, this document describes early (1984) and more recent Toyota lean
burn engines.
Comment: Interesting technical description but no clear if or how used in the Ricardo (201 1)
model.
Kapus, P., Potential of WA Systems for Improvement of C02 Pollutant Emission and
Performance of Combustion Engines, 30 Nov 2006, 9 p. This is a technical paper describing
variable valve actuation approaches and performance effects.
Comment: Useful general technical information.
Concern: This report has significant deficiencies in its description of the entire process used
in the modeling work. Many of these deficiencies have been previously discussed, but are
listed here for completeness.
An overall schematic and description of the powertrain and vehicle models and the
associated subsystem models/maps were not provided. Only vague descriptions were
included in the text of the report.
Technical descriptions of how the subsystems and vehicle models/maps for the baseline
vehicles were developed were not provided.
None of the overall or subsystem models/maps were provided for review so comments on
their adequacy are not possible.
Most importantly, only minimal descriptions were provided of how each of the advanced
technology subsystem models/maps was developed.
                    44

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Completeness
Completeness
Completeness
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Specific
Assumption/Topic



Accessory load
assumptions
Accessory load
assumptions
Accessory load
assumptions
Accessory load
assumptions
Additional
recommendations
shown in bold print
throughout other
sections of this
report are repeated
below for
completeness
Additional
recommendations
shown in bold print
throughout other
sections of this
report are repeated
below for
completeness
Comment
Excerpt
Mn
228
229
230
338
339
340
341
240
241
Review
Round
1
1
1
1
1
1
1
1
1
Reviewer
Wade
Wade
Wade
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Wade
Wade
Comment
Descriptions of the algorithms used for engine control, transmission control, hybrid system
control, and accessory control were not provided.
Descriptions of how synergistic effects were handled were not provided.
There are many engine technologies that have potential for reduced GHG emissions that
were not included in this study, such as:-Single stage turbocharged engines - Diesel hybrids-
Biofueled spark ignition and diesel engines-Natural gas fueled engines- Other alternative fuel
engines-Charge depleting PHEVand EV
Cite and/or validate the alternator efficiency values of 55% and 70%.
Account for charge/discharge losses in the advanced alternator control and/or describe the
12V battery model used for the simulation.
Describe, cite, and validate the accessory fan model used in the simulation.
Justify the use of a 200 Amp advanced alternator across all of the vehicle platforms.
Recommendation: Since the baseline vehicles modeled were 2010 production vehicles, the
models/maps for the subsystems used in these vehicle models should be included in the
report before it is released.
Recommendation: A baseline model of a hybrid vehicle should be developed and compared
to 2010 EPA fuel economy test data for production hybrid vehicles.
                    45

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Recommendations
Recommendations
Recommendations
Recommendations
Specific
Assumption/Topic
Additional
recommendations
shown in bold print
throughout other
sections of this
report are repeated
below for
completeness
Additional
recommendations
shown in bold print
throughout other
sections of this
report are repeated
below for
completeness
Additional
recommendations
shown in bold print
throughout other
sections of this
report are repeated
below for
completeness
Additional
recommendations
shown in bold print
throughout other
sections of this
report are repeated
below for
completeness
Comment
Excerpt
Mn
242
243
244
245
Review
Round
1
1
1
1
Reviewer
Wade
Wade
Wade
Wade
Comment
Recommendation: The detailed assumptions showing how the benefits of dry sump,
improved component efficiency, improved kinematic design, super finish, and advanced
driveline lubricants were added to the transmission maps should be added to the report
before it is released.
Recommendation: Subsystem models/map should be added to this report and another peer
review conducted to assess their adequacy before this report is released.
Recommendation: To establish the adequacy of the subsystem models/maps, derivation
details should be provided.
Recommendation: Both mechanically driven and electrically driven accessory power
requirements should be clearly provided in the report.
                    46

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Specific
Assumption/Topic
Additional
recommendations
shown in bold print
throughout other
sections of this
report are repeated
below for
completeness
Additional
recommendations
shown in bold print
throughout other
sections of this
report are repeated
below for
completeness
Advanced
Valvetrains
(Section 4. 1.1)
Advanced
Valvetrains
(Section 4. 1.1)
Advanced
Valvetrains
(Section 4. 1.1)
Aftertreatment/
Emissions
Solutions
Aftertreatment/
Emissions
Solutions
Comment
Excerpt
Mn
246
247
319
320
321
316
317
Review
Round
1
1
1
1
1
1
1
Reviewer
Wade
Wade
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Comment
Recommendation: A default weight increase/decrease should be added for each technology.
If weight reductions are to be studied, then the user should have to input a specific design
change, with the appropriate weight reduction built into the model, rather that having an
arbitrary slider for weight.
Recommendation: A closer examination of the reasons for the up to 1 1 % discrepancies
between the models and baseline vehicles' fuel economy test data should be undertaken so
that the models could be refined to provide better agreement.
Describe how variable valve timing technologies were applied to the base engine maps.
Describe the process of determining the extent of the efficiency improvement.
Describe how optimal valve timing was determined across the variety of engines simulated.
Provide better evidence that powertrain packages have credible paths to meet emissions
standards.
Provide evidence that fuel enrichment strategies are consistent with emissions regulations.
                    47

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Specific
Assumption/Topic
Boosting System
(4. 1.3 and 6.3)
Boosting System
(4. 1.3 and 6.3)
BSFC Map
Comparisons
Direct Injection
Fuel Systems
Direct Injection
Fuel Systems
Direct Injection
Fuel Systems
Electric Traction
Components
Electric Traction
Components
Electric Traction
Components
Engine Downsizing
Engine Downsizing
Engine Models
Engine Models
Comment
Excerpt
M«
327
328
396
323
324
325
353
354
355
330
331
310
311
Review
Round
1
1
2
1
1
1
1
1
1
1
1
1
1
Reviewer
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Comment
Describe the process of arriving at the boosted engine maps.
Describe how factors like knock are addressed in the creation of these maps.
I reviewed this but do not have any substantive comments. All of the figures compare
pseudo-virtual engines with other pseudo-virtual engines. A comparison back to a known,
experimentally validated engine current engine would have been more useful for me as it
would allow one to see the magnitude of improvements that were assumed for the 2020
engines and where on the map these improvements were made.
Cite sources of data used to predict Dl performance.
Describe how this data was used to develop the future engine performance maps.
Provide validation of modeling techniques used.
Describe the method used to model electric traction components.
Provide validation/basis for the process used to generate future technology versions of these
components.
Describe the technique used to scale these components.
Properly document the process of scaling engines.
Validate the process used to scale engines.
Provide fuel and efficiency map data for all engines used in simulation.
Describe what the "other inputs" are to the engine maps.
                    48

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Specific
Assumption/Topic
Engine Models
Engine Models
Engine Models
Engine technology
selection
Engine technology
selection
HEV Battery Model
HEV Battery Model
HEV Battery Model
Hybrid Controls
Presentations
Hybrid technology
selection
Hybrid technology
selection
Comment
Excerpt
M«
312
313
314
343
344
357
358
359
400
349
350
Review
Round
1
1
1
1
1
1
1
1
2
1
1
Reviewer
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Comment
Provide specific references of which published data was used to predict performance of the
future engines. Some references are given, however, it is not clear how exactly these
references are used.
Wherever possible, provide validation against data on similar technologies.
Describe in detail the approach used to "stack up" technologies for a given powertrain recipe.
Describe in greater detail the approach used to model technology stack-up on the advanced
vehicles.
Provide some form of validation that this approach is justified.
Describe the method used to model the HEV battery.
Provide validation/basis for the process used to generate future technology versions of the
battery.
Describe the technique used to scale the HEV battery .
Several hybrid controls presentations were provided, however, it was difficult to piece
together what information superseded the other since they were provided out of context.
There were several good slides showing dynamic programming results of different control
scenarios, however, it is assumed that this was not used for the mass simulation since it
would be computationally impractical. Thus, I expected to see some results comparing the
offline control results to the actual control used in the vehicle simulation, however, this was
not found. The major concern in this area is developing a control strategy that is near
optimal for a wide variety of hybrid architectures as well as architectures with varying
component types and sizes. Without further validation in this area it is not clear that the
hybrid results are valid since the control has such an important role in this.
Better describe the hybrid control strategy and validate against a current production baseline
vehicle.
Validate that the HEV control algorithm performs equally well on all vehicle classes.
                    49

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
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Recommendations
Recommendations
Recommendations
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Recommendations
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Recommendations
Recommendations
Recommendations
Recommendations
Specific
Assumption/Topic
Hybrid technology
selection
Overall
recommendations
Overall
recommendations
Specific
recommendations
for improvements
Specific
recommendations
for improvements
Specific
recommendations
for improvements
Specific
recommendations
for improvements
Specific
recommendations
for improvements
Specific
recommendations
for improvements
Transmissions
Comment
Excerpt
M«
351
232
233
234
235
236
237
238
239
361
Review
Round
1
1
1
1
1
1
1
1
1
1
Reviewer
Midlam-
Mohler
Wade
Wade
Wade
Wade
Wade
Wade
Wade
Wade
Midlam-
Mohler
Comment
Validate that other vehicle performance metrics, like emissions and acceleration, are not
adversely impacted by an algorithm that focuses solely on fuel economy. The emission side
of things will challenge to validate with this level of model, however, some kind of assurance
should be made to these factors which are currently not addressed at all.
Overall Recommendation: Provide all vehicle and powertrain models/maps and subsystem
models/maps used in the analysis in the report so that they can be critically reviewed.
Overall Recommendation: Expand the technology "package definitions" to enable evaluation
of the individual effects of a variety of technologies.
Provide an overall schematic and description of the powertrain and vehicle models.
a. Show all of the subsystem models/maps used in the overall model.
b. Show the format of the information in each of the subsystem models (including input,
subsystem model, output).
Provide technical descriptions of how the subsystems and vehicle models/maps for the
baseline vehicles were developed.
Provide overall system and subsystem models/maps in the report.
Provide detailed technical descriptions of how each of the advanced technology subsystem
models/maps was developed.
Provide descriptions of the algorithms used for engine control, transmission control, hybrid
system control, and accessory control.
Provide detailed descriptions of how synergistic effects were handled.
Cite data sources used in modeling.
                     50

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Specific
Assumption/Topic
Transmissions
Transmissions
Transmissions
Transmissions
Transmissions
Transmissions
Transmissions
Vehicle model
issues
Vehicle model
issues
Vehicle model
issues
Vehicle model
issues
Warm-Up
Methodology
Warm-Up
Methodology


Comment
Excerpt
M«
362
363
364
365
366
367
368
304
305
381
382
333
334
51
52
Review
Round
1
1
1
1
1
1
1
1
1
2
2
1
1
1
1
Reviewer
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Midlam-
Mohler
Assanis
Assanis
Comment
Validate models wherever possible.
Fully describe transmission models/maps and processes used to generate them.
Fully describe clutch/torque converter models/maps and processes used to generate them.
Fully describe the process used to generate shift maps and the operation of the shift
controller.
Fully describe the lockup controller (i.e. how soon can it enter lockup after shifting?).
Fully describe the process for modeling torque holes during shifting.
Fully describe the model used for the final drive (i.e. inputs/structure/outputs).
List the dynamic equation describing the longitudinal motion of the vehicle.
List all parameters used for each vehicle class for simulation.
List the dynamic equation describing the longitudinal motion of the vehicle
a. NOT ADDRESSED IN SUPPLEMNTAL MATERIAL REVIEWED
List all parameters used for each vehicle class for simulation
a. NOT ADDRESSED IN SUPPLEMNTAL MATERIAL REVIEWED
Cite sources of data for 10% and 20% factors applied to the cold bag fuel economy data.
Cite and/or validate the modeling approach used.
Various suggestions have already been included in the relevant sections.
The authors should expand the modeling sections. In particular, they should cite literature
references (where possible) and provide more detail when empirical data, modifiers, or
                     51

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                                          Verbatim Peer Reviewer Comments in Response to
                                                         Charge Questions
Charge Question
    Topic
    Specific
Assumption/Topic
Comment
 Excerpt
Review
Round
Reviewer
Comment
                                                              scaling laws are used.

Recommendations
Recommendations
Recommendations
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Recommendations
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53
54
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150
151
152
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154
155
156
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158

1
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Assanis
Assanis
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom
McBroom

Flexibility should be added to the models. Some engine technologies, such as variable cam
phasing, HCCI and alternative fuels should be considered.
A self-contained study should be presented as a test case for the results so that specific
conclusions can be drawn and the utility of the approach more easily understood.
Instead of using proprietary Ricardo (201 1) data/models/control algorithms citable data
should be used.
Without stating how this model is going to be used in the regulatory decision making process,
it is very difficult to assess its appropriateness.
Considerably more time in this effort is required up front in the report, to discuss the process
of building consensus on data and models. Because this is not really discussed, it gives the
impression that not much was done.
Guidelines for appropriate use should be given.
An uncertainty rating for each model/data set should be published to highlight the relative
differences in the assumptions/extrapolation of future technologies.
Should use coast down data for baseline vehicles to model parasitic losses.
In terms of acceptable use: rather that trying to use the model to assess the boundaries of
the envelope (or which technology is better), the tool could be used to find the areas of
maximum overlap. In other words, knowing that the same performance and fuel economy is
achievable using different technologies lends more confidence that the result is achievable.
Theoretically this number could be a calculated value generated from the RSM's.
Recommend allowing "real world" drive cycles to assess the robustness of the results. Could
be a user generated result from a composite of the data sets already generated.
Should define the process for data selection.... eventually you'll be asked by a manufacturer,
'how do we get 'x' technology included for consideration in the study.
Where lumped improvements are made, I recommend using historical results to publish
technology improvement curves. For example, the parasitic losses (Cd, Crr) should be
quantifiable. Vehicle mass reductions as well.
                                                                52

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Verbatim Peer Reviewer Comments in Response to
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Recommendations
Recommendations
Specific
Assumption/Topic








Comment
Excerpt
Mn
300
301
9
10
11
12
423
426
Review
Round
1
1
1
1
1
1
2
2
Reviewer
Midlam-
Mohler
Midlam-
Mohler
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Sawyer
Comment
Given the low level of detail given in the report, it does seem that the strategy used is
consistent with the goal of the work and what others in the field are doing. That being said,
the report is inadequate in nearly every respect at documenting model inputs, model
parameters, modeling methodology, and the sources and techniques used to develop the
technology performance data. Given the need for transparency in this effort, this reviewer
feels that the detail in the report is wholly inadequate to document the process used. The
organization responsible for the modeling has expertise in this area it is certainly possible
that the methodology is sound, however, given just the information in the report there is
simply no way for an external reviewer to make this conclusion.
Because of the lack of hard information to answer the charge questions, this peer review
evolved mainly into a suggested list of details that should be brought forward in order to allow
the charge questions to be answered properly. With this information, it is hoped that a
person with expertise in the appropriate areas will be able comment on the work more fully.
The failure to model the drivetrain-weight interactions is a major shortcoming. Appendix 2
should clearly state that vehicle weights are held constant (assuming that I am correct in that
assumption).
There should be a table describing the baseline vehicles.
Summarizing assumptions in tabular form would be a great assistance to the reader.
The design space should be expanded to include performance parameters, such as
power/weight or 0-60 times.
Ricardo, BSFC Map Commparisons, LBDI vs EGR Boost & DVAfor STDI, OBDI, & EGR
Boost, Light Duty Vehicle Complex Systems Simulation, EPA Contract No. EP-W=07=064,
work assignment 2-2, 24 Feb 10, 20 p. (proprietary) Comparison of engine technologies in
terms of maps of percent difference in bsfc in bmep vs rpm space allows visualization
Comment: Straightforward data analysis, presumably as requested by USEPA. Should aid in
understanding technology performance differences.
Ricardo, Response to EPA Questions on the Diesel Engine Fuel Maps, Supplemental
Graphs for Word Document, 16 Feb 10, 11 p. (proprietary) Document presents proposed
diesel engine maps for MY2020+ vehicles.
Comment: Anticipated technologies are listed but how the maps were generated is not
described. Maps seem reasonable.
                     53

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Quest on Specfc Comment R
%. . . .. „. . Excerpt 0 . Reviewer Comment

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Recommendations


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Recommendations


Executive
Summary



























431



444


445


460



231


295





2



2


2


2



1


1





Sawyer
Odvarka, E., etal., Electgric motor-generator for a hybrid electric vehicle, Engineering
Mechanics, 16, 131-139, 2009, 9 p. Describes electrical machine options of hybrid electric


Sawyer


Sawyer
vehicles. Includes efficiency maps for four technologies.
Comment: Data are of general interest, but date from 2003.
Ricardo, Lean/Stoichiometric switching load for 2020 Hybrid Boost Concept, (no date), 2 p.
Presents space velocity and fuel maps.
Comment: Relevance not clear.
Ricardo, Proposed Lean/Stoichiometric switching load for hybrid boost concept, 29 Apr 10, 1
p. Identifies proposed lean zone operating region on engine map.

Comment: relevance not clear.
Sawyer Ricardo, Transient Performance of Advanced Turbocharged Engines, 15 Sep 10, 19 p.
(proprietary) This report reviews expected advances in boosting technologies and anticipated


Wade
effects on vehicle performance.
Comment: Interesting information but how it impacts model is not clear.
This report needs major enhancements to reach the stated goal of being open and
transparent in the assumptions made and the methods of simulation. Recommendations to

Midlam-
rectify the deficiencies in these areas are provided in the previous four items.
For the purpose of describing the modeling approach used in the forecasting of the
Mohler performance of future technologies, the report reviewed is inadequate. In virtually every




area, the report lacks sufficient information to answer the charge questions provided for the
reviewer. It is entirely possible that the approach used is satisfactory for the intended
purpose. However, given the information provided for the review, it is not possible for this
reviewer to make any statement regarding the suitability of this approach.
                     54

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Verbatim Peer Reviewer Comments in Response to
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Topic
Executive
Summary
Executive
Summary
Other Comments
Other Comments
Other Comments
Specific
Assumption/Topic


Accessory Models
Accessory Models
Accessory Models
Comment
Excerpt
Mn
383
463
269
270
271
Review
Round
2
2
1
1
1
Reviewer
Midlam-
Mohler
Sawyer
Wade
Wade
Wade
Comment
The supplemental review material provided some answers to questions posed above, but in
general, did not provide the level of detail necessary to ensure a thorough review of the
process. The conclusion of this reviewer remains similar as on the original review, which is
that there were no serious flaws found in the work, however, there were enough omissions
that it is not possible to accurately judge if the predictions made are accurate. The biggest
concern in this work is the lack of validation and/or citation of where data and models are
coming from. There are numerous maps that are presented in the follow-up material,
however, these maps had to have originated from some process (which needs documented)
and should be compared against some kind of validation. Despite the lack of documentation
provided, the work is generally that of a project team that is competent in this field of study.
Ricardo (201 1) has provided material, which is stated to be the data incorporated in the
computer simulation. These data are consistent with the data expected to be the basis of the
simulation. It is impossible to establish a precise correspondence between the data and the
model. The performance data covered by the 44 separate documents seem reasonable and
provide additional assurance that the simulation is soundly based on measured performance.
There is no reason to doubt either the integrity or capability of Ricardo (201 1) in their
incorporation of appropriate data into their simulation model.
None of the accessory models were not provided for review, so their adequacy and suitability
cannot be assessed.
The accessory loads vs. engine speed for the conventional belt driven accessories were
apparently removed from the engine when electric accessories were applied. However, the
conventional accessory loads as well as the alternator loads/battery loads for the electric
accessories were not provided.
In contrast, as an example, PQA and Ricardo (2008) provided the following map of an
electric water pump and AC compressor drive efficiency. Similar maps for all accessory
models would be expected in this report. (See Exhibit 6)
                     55

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Verbatim Peer Reviewer Comments in Response to
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Topic
Other Comments
Other Comments
Other Comments
Other Comments
Other Comments
Specific
Assumption/Topic
Advanced
Valvetrains
(Section 4. 1.1)
Boosting System
(4. 1.3 and 6.3)
Boosting Systems
Boosting Systems
Boosting Systems
Comment
Excerpt
Mn
56
57
272
273
274
Review
Round
1
1
1
1
1
Reviewer
Assanis
Assanis
Wade
Wade
Wade
Comment
The report states that advanced valvetrain systems improve fuel consumption and GHG
emissions mainly by improving engine breathing. Other benefits cited are in supporting
engine downsizing and faster aftertreatment warm-up. Beyond improving volumetric
efficiency and reducing pumping losses, advanced valvetrains can enable compression ratio
variation to increase fuel economy and avoid knock, alter the combustion process by
modulating trapped residual, and enable cylinder deactivation to reduce pumping losses.
From the report, it is not clear which of the possible benefits of the advanced valvetrain
packages have been harnessed in each case. A more systematic analysis of technology
package combinations is warranted as several are synergistic but not additive.
A two-stage system is indeed promising for advanced turbocharging concepts. A distinction
should be made between series and sequential configurations. Air flow manipulation can
make it a series system (two-stage expansion and compression) or a sequential system
(turbos activated at different rpm). Variable geometry or twin-scroll turbines can be good
options for the low or high pressure stages, respectively. A two-stage turbocharging system
like this would take advantage of the lean SI exhaust enthalpy, reduce pumping work (or
even aid pumping), avoid mechanical work penalties, improve engine transient response,
enable high dilution levels (if desired) and probably help keep in-cylinder compression ratio
below 12:1, since significant compression would be done before the cylinder. EGRflow could
be driven through a low pressure loop (after the turbines) or an intermediate pressure loop
(between the turbines). The resulting turbo lag will depend on the details of the configuration
and the control logic used. Note that the assumption of a time constant of 1 .5 seconds (as
stated in the report) to represent the expected delay may not hold true in all cases.
The report states that "various boosting approaches are possible, such as superchargers,
turbochargers, and electric motor-driven compressors and turbines." (page 13). However,
elsewhere the report states "series-sequential turbochargers" will be used on the
Stoichiometric Dl Turbo engine (page 15).
It is not clear in the report how the series-sequential turbocharger was selected from the
variety of boosting devices that were introduced. Models for the turbochargers with
compressor and turbine efficiency maps were not provided, so the appropriateness of these
model cannot be assessed.
Comment: The model should include a single turbocharger system with less extreme
downsizing as advocated by the Sabre Engine (Coltman et al., 2008; Turner et al., 2009) as
a lower cost alternative to series-sequential turbochargers.
                     56

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Verbatim Peer Reviewer Comments in Response to
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Other Comments
Specific
Assumption/Topic
Cooled Exhaust
Manifold
Efficient
Components
(Section 4.4.9)
Engine Models
Engine Models
Comment
Excerpt
Mn
284
61
254
255
Review
Round
1
1
1
1
Reviewer
Wade
Assanis
Wade
Wade
Comment
The Ricardo (201 1) report states, "The future engine configuration was assumed to use a
cooled exhaust manifold to keep the turbine inlet temperature below 950C. . . No explanation
was provided of how the limit on turbine inlet temperature would affect boost pressure and
power.
Efficient components should also include gears since rotating gears are also a major source
of drag. Designing a better profile for gear teeth can reduce drag losses.
Engine models provided the torque curve, fueling map and other input parameters (which
were not specified in the report) (page 25). Since the report stated that "The fueling maps
and other engine model parameters used in the study were based on published data and
Ricardo (201 1) proprietary data (page 26), their adequacy and suitability could not be
assessed.
The report states that engines used in the model were developed using two main methods
(page 14). 1 . The first method assumed that "reported performance of current research
engines would closely resemble production engines of the 2020-2025 timeframe. 2. The
second method began with current production engines and then a "pathway of technology
improvements over the new 10-15 years that would lead to an appropriate engine
configuration for the 2020-2025 timeframe" was applied. Both of these approaches are
reasonable if: 1 . appropriate references are provided, 2. the reported performances for the
research engines used are documented in the report, 3. the technology improvements are
documented in the report, and 4. the methodology of incorporating the improvements is fully
documented.
                     57

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              Charge Questions
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Topic
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Other Comments
Specific
Assumption/Topic
Engine Models
Engine Models
Engine Models
Comment
Excerpt
Mn
256
257
258
Review
Round
1
1
1
Reviewer
Wade
Wade
Wade
Comment
The description of the derivation of the engine models in the report was, at best, vague, as
illustrated by the two examples below:
Example 1: Stoichiometric Dl Turbo
The current research engines of this configuration were reported to be the Sabre engine
developed by Lotus and the downsized concept engine developed by Mahle. Since the
engine modeled in the Ricardo (201 1) report had a peak BMEP of 25-30 bar and used
series-sequential turbochargers, the Sabre engine is not applicable since it only had a peak
BMEP of 20 bar and used a single stage turbocharger (Coltman et al., 2008; Turner et al.,
2009).
On the other hand, the Mahle engine appeared to be directly applicable, since it had a peak
BMEP of 30 bar and used series-sequential turbocharging (Lumsden et al., 2009). Since
Lumsden, et a. (2009) provided the BSFC map for this engine, shown below, it is not clear
why the Ricardo (201 1) report could not have shown this map, or a map derived from this
one, and then described how it was derived and/or combined with other maps to provide the
model used in the report. (See Exhibit 3)
The description of the derivation of the engine models in the report was, at best, vague, as
illustrated by the two examples below: Example 2: Advanced Diesel
For the advanced diesel, the report provided the following description: "...the LHDT engine
torque curve and fueling maps were generated by starting with a 6.6L diesel engine typical
for this class and applying the benefits of improvements in pumping losses or friction to the
fueling map". No description of the improvements in pumping losses or friction reduction was
provided and the variation of these improvements over the speed and load map were not
provided. In addition, the baseline 6.6L engine map was not provided, the 6.6L friction map
was not provided and the methodology for applying the improvements to the 6.6L engine
map was not provided.
The report should explain whether the engine model is only a map of BSFC vs. speed and
load, or if the engine model includes details of the turbocharger, valve timing, and control
algorithms for parameters such as air/fuel ratio, spark/injection timing, EGR rate, boost
pressure, and valve timing.
                     58

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Verbatim Peer Reviewer Comments in Response to
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Specific
Assumption/Topic
Engine Models
Engine Models
Engine Scaling
Engine Scaling
Comment
Excerpt
Mn
259
260
289
290
Review
Round
1
1
1
1
Reviewer
Wade
Wade
Wade
Wade
Comment
Advanced valvetrains were included in many of the advanced engines (page 12). However,
the method for applying these advanced valvetrains to the engine maps was not provided.
Also, no description of the control strategy for these valvetrains was provided. The report did
not provide a description of how the reduction of pumping losses with an advanced valvetrain
was applied to a downsized engine that already had reduced pumping losses. Therefore, no
assessment of how the model handled synergies could be made.
In summary, the Ricardo (201 1) report provided insufficient descriptions of the derivation of
the maps used for all of the engines in this study, which included:
- Baseline
- Stoichiometric Dl Turbo
- Lean-Stoichiometric Switching
- EGR Dl Turbo
- Atkinson Cycle
- Advanced Diesel
The report states, "The BSFC of the scaled engine map is . . .adjusted by a factor that
accounts for the change in heat loss that comes with decreasing the cylinder volume, and
thereby increasing the surface to volume ratio for the cylinder" (page 26). This is a
directionally correct correction. However, specific values for the correction should be
provided, together with references to the data and methodology used to derive the values
used.
Issue: The report states, "...downsizing the engine directly scales the delivered torque, ..."
(page 26). However, since there will be increased heat loss from the smaller displacement
cylinder, the torque would be expected to be less than the directly scaled values for the same
fueling rate.
                     59

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
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Other Comments
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Other Comments
Other Comments
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Specific
Assumption/Topic
Hybrid
Technologies
Models
Hybrid
Technologies
Models
Hybrid
Technologies
Models
Hybrid
Technologies
Models
Lean-
Stoichiometric
Switching (Section
4.2.2)
Lean-
Stoichiometric
Switching Engine
Comment
Excerpt
Mn
265
266
267
268
58
288
Review
Round
1
1
1
1
1
1
Reviewer
Wade
Wade
Wade
Wade
Assanis
Wade
Comment
Key elements of a hybrid system include: electric machines (motor-generator), power
electronics, and a high-voltage battery. Only the following vague description of the models
for these subsystems was provided: "For each of these systems, current state of the art
technologies were adapted to an advanced 2020-2025 version of the systems, such as by
lowering internal resistance in the battery pack to represent 2010 chemistries under
development and decreasing losses in the electric machine and power electronics to
represent continued improvements in technology and implementation" (page 29). This vague
description did not provide adequate details to assess the adequacy of these models. For
example, specific values for internal resistance with references should be provided together
with an illustration of how this was incorporated in the model of the battery.
In contrast, as an example, Staunton, et al. (2006) provided a detailed motor efficiency map,
shown below, as well as efficiency maps of other key components of the Prius hybrid vehicle.
Similar maps for all hybrid subsystems would be expected in this report. (See Exhibit 5)
In addition, "a Ricardo proprietary methodology was used to identify the best possible fuel
consumption for a given hybrid powertrain configuration over the drive cycles of interest."
(page 29), which precluded an assessment of its suitability.
No mention was provided of how the cooling system for the hybrid system was modeled.
The mixed-mode operation considered in the report seems to switch between stoichiometric
and lean SI direct injection operation. There are several multi-mode combustion efforts under
development that encompass several more combustion modes, including HCCI and
Sparkassisted compression ignition with amounts of EGR dilution.
The report states that this engine will use a lean NOx trap or a urea-based SCR system
(page 15). The use of fuel as a reducing agent was also suggested in the report (page 16).
However, the fuel economy penalty associated with regenerating the NOx trap or the
reducing agent for the SCR system was not provided.
                     60

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
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Other Comments
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Other Comments
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Specific
Assumption/Topic
P2 Parallel Hybrid
(Section 4.3.2)
Stoichiometric Dl
Turbo Engine
Stoichiometric Dl
Turbo Engine
Stoichiometric Dl
Turbo Engine
Stoichiometric Dl
Turbo Engine
Stoichiometric Dl
Turbo Engine
Comment
Excerpt
M«
59
275
276
277
278
279
Review
Round
1
1
1
1
1
1
Reviewer
Assanis
Wade
Wade
Wade
Wade
Wade
Comment
P2 refers to pre-transmission parallel hybrid, where an electric machine is placed in between
the engine and the transmission. While the report does not discuss details, there are two
possible configurations: (i) a single clutch, located in between the engine and the electric
machine, such as in the Hyundai Sonata, and (ii) two clutches, one in between the engine
and the motor, and the other one in between the motor and the transmission, such as in the
Infiniti M35 HEV. The P2 system looks promising to achieve good efficiency, but remaining
barriers include cost, drive quality, durability and to a lesser extend packaging. Careful
consideration of details is needed to properly assess benefits compared to a single mode
power split. Early reports have indicated that Nissan got 38% mpg increase out of their P2
and Hyundai got 42%, both with higher horsepower, as well. However, the P2 Touareg
doesn't seem to meet EPA 2012 CAFE standards.
The table below compares several attributes of the Ricardo Stoichiometric Dl Turbo Engine
with the Mahle Turbocharged, Dl Concept Engine. (See Exhibit 7)
Key content of the Mahle Turbocharged, Dl Concept Engine:
- Two turbochargers in series
- Charge air cooler
- Dual variable valve timing
- High energy ignition coils
- Fabricated, sodium cooled valves
- EGR cooler
Lumsden, et al. (2009) describing the Mahle concept engine stated that lowest fuel
consumption that usually occurs around 2000 rpm had moved out to 4000 rpm for the series-
sequential turbocharged engine.
Issue: The Ricardo (201 1) report did not discuss the concern that the lowest fuel
consumption in a series-sequential turbocharged engine had moved out to 4000 rpm, rather
than the usual 2000 rpm and did not discuss how this concern was handled.
The foregoing table indicates several significant issues: 1 . The turbine inlet temperature of
the Mahle engine is significantly higher than the limit assumed for the Ricardo engine (1025C
vs. 950C). Reducing the turbine inlet temperature is expected to result in lower BMEP levels
where the temperature is limited, (see Exhibit 7)
                     61

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Charge Question
      Topic
     Specific
Assumption/Topic
Comment
 Excerpt
Review
Round
Reviewer
Comment
Other Comments    Stoichiometric Dl
                   Turbo Engine
Other Comments
Other Comments
Stoichiometric Dl
Turbo Engine
Stoichiometric Dl
Turbo Engine
                         280        1 |  Wade        The foregoing table indicates several significant issues: 2.  The turbocharger response time
                                                      for the Mahle engine is 2.5 seconds, whereas Ricardo (2011) assumed a time constant of 1.5
                                                      seconds.  Such turbocharger delays are expected to result in significant driveability issues
                                                      for engines that are downsized approximately 50%. (see Exhibit 7)
      281
      282
Other Comments    Stoichiometric Dl
                   Turbo Engine
                         283
Other Comments
Transmission
Models
Other Comments    Transmission
                   Models
      261
                         262
         Wade
         Wade
                     Wade
            The table below compares several attributes of the Ricardo Stoichiometric Dl Turbo Engine
            with the Lotus Sabre Engine, (see Exhibit 8)
         Wade        The paper on the Sabre engine (Turner et al., 2009) indicates that operation at lower turbine
                      inlet temperatures results in a reduction in BMEP. However, the turbine inlet temperature for
                      the Sabre engine is still 40C above Ricardo's assumption.
                     Wade        Turner et al. (2009) indicates that the Sabre engine with a single stage turbocharger provides
                                  an attractive alternative to extreme downsizing with series-sequential turbochargers.
            Similar to engine models, the description of the derivation of transmission models was also
            vague. Using the automatic transmission model as an example, "For the 2020-2025
            timeframe, losses in automatic transmissions are expected to be about 20-33% lower than in
            current automatic transmissions from the specific technologies described below." The
            specific technologies that could provide these reductions appeared to include:
            - Shift clutch technology - to improve thermal capacity of the shifting clutch to reduce plate
            count and lower clutch losses during shifting.
            - Improved kinematic design - no description of these improvements was provided.
            -Dry sump - to reduce windage and churning losses.
            - Efficient components - improvements in seals, bearings and clutches to reduce drag.
            - Super finishing - improvements expected were not specified.
            -Lubrication- new developments in base oils and additive packages, but improvements were
            not specified.
            In addition to not specifying the improvements  expected from these technologies, no
            indication was provided of how these technologies were applied to the transmission models.
            For example,
            -The report stated that losses in automatic transmissions are expected  to be about 20-33%
            lower than in  current automatic transmissions (page 19). However, the baseline losses were
            not provided for reference and the means to achieve these reductions were not described.
            - The report stated that energy losses in DCTs are expected to be 40-50% lower than in
            current automatic transmissions (page 19). The details of this reduction were not provided
            and references describing these reductions were not provided.
                                                                           62

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic

Other Comments
Other Comments
Other Comments
Other Comments
Other Comments
Other Comments
Other Comments
Specific
Assumption/Topic

Transmission
Models
Transmission
Models
Transmission
Models (Section
6.4)
Transmission
Technologies
(Section 4.4)
Warm-Up
Methodology
Warm-Up
Methodology
Warm-Up
Methodology
Comment
Excerpt
Mn

263
264
62
60
285
286
287
Review
Round

1
1
1
1
1
1
1
Reviewer

Wade
Wade
Assanis
Assanis
Wade
Wade
Wade
Comment
- Bearing and seal losses have a greater effect on efficiency at light loads than at heavy
loads. The report did not describe how these losses were incorporated in the model. In
contrast to the lack of descriptions of details in the report, PQA and Ricardo (2008), as an
example, provided the following map of bearing losses in a transmission as a function of
shaft diameter and speed. Similar details for the relevant aspects of the transmission models
in this report would have been expected. (See Exhibit 4)
In summary, the Ricardo (201 1) report provided insufficient descriptions of the derivation of
the maps for the following transmissions:- Advanced automatic- Dry clutch DCT- Wet clutch
DCT- P2 Parallel hybrid transmission- PS Power Split hybrid transmission
In addition, the models for the automatic transmissions of the baseline vehicles were not
provided, so that their adequacy could not be assessed.
It is claimed that gear selection will be optimized for fuel economy for a given driver input and
road load. Can this also be adaptive? Engine performance degrades with age. This strategy
could also lead to more gear shifts; the latter would increase hydraulic loads and frictional
power losses in the clutch, thus eroding some of the possible fuel economy gains.
What about automatic transmissions with automated clutch replacing the torque convertor
and lock-up clutch? This is also a possibility.
"Ricardo used company proprietary data to develop an engine warm-up profile" which was
used to increase the fueling requirements during the cold start portion of the FTP75 drive
cycle (page 26). Since this data was proprietary, no assessment of its appropriateness can
be made.
Elsewhere the report states, "A bag 1 correction factor is applied to the simulated "hot" fuel
economy result of the vehicles to approximate warm-up conditions. . ." The correction factor
reduces the fuel economy results of the FTP75 bag 1 portion of the drive cycle by 20% on
the current baseline vehicles and 10% on 2020-2025 vehicles that take advantage of fast
warm-up technologies" (page 29). No references or data are cited to support this significant
reduction in correction factor.
Issue: No explanation was provided to clarify when the "engine warm-up profile" is used and
when the "correction factor" is used. Therefore, the appropriateness of the warm-up
methodology cannot be assessed.
                     63

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Other Comments
Other Comments
Specific
Assumption/Topic


Comment
Excerpt
Mn
15
16
Review
Round
1
1
Reviewer
Assanis
Assanis
Comment
The report is intended to provide administrators, product planners and legislators a practical
tool for assessing what is achievable, as well as insight into the complexity of the path
forward to reach those advances that will be useful for productive discussions between EPA
and the manufacturers. This path forward involves trade-offs among many design choices
involving available, and soon-to-be-available advances in engine technologies, hybridization,
transmissions and accessories. The current version of the simulation effort seems
reasonably balanced in the attention paid to each of these areas. The range of improvements
shown in the technologies considered and examples is encouraging.
Overall, the project attempts to undertake an analytical technology assessment study of
significant scope. It does a fairly competent job at analyzing a select number of technologies
and packages, mostly aimed at improving the gasoline 1C engine, and to a less extent the
diesel engine. It complements improvements on the engine side with synergistic
developments on the transmissions, hybrids and accessories. The main shortcoming of the
study is that the methodology relies extensively on proprietary and undisclosed data, as well
as empirical rules, correlations and modifiers without citing published reference sources.
eyond the perceived lack of transparency, keeping up with new technologies or approaches
will necessarily involve new versions of the program since the actual models of the
technologies used are proprietary and the choice and range of parameters available to users
is fixed and to some extent hidden. Due to these constraints, the simulation tool is limited in
its ability to provide fundamental insight; this will require a more basic thermodynamic
approach, perhaps best carried out by universities.
                     64

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question Specific Comment R .
Topic Assumption/Topic "^ Round Reviewer Comment
Other Comments
Other Comments


17
18
1
1
Assanis
Assanis
For the most part, the right technologies are being considered. However, certain promising
technologies and fuel options for 1C engine technologies (other than gasoline and diesel) that
can make a significant contribution to the improvement of mpg and reduction of C02
emissions have not been considered, or even mentioned at all. Primary examples are
advanced combustion technologies, such as high pressure, dilute burn, low temperature
combustion (e.g., Homogeneous Charge Compression Ignition, Partially Premixed
Compression Ignition, Spark-Assisted Compression Ignition), and closed-loop, in-cylinder
pressure feedback. Some of these combustion technologies have the potential to improve
fuel economy by up to 25%. Another significant assumption is that fuels used are equivalent
to either 87 octane pump gasoline or 40 cetane pump diesel. However, advanced biofuels,
particularly from cellulosic or lingo-cellulosic bio-refinery processes, which from the
standpoint of a life cycle analysis have strong potential for reduction of C02 emissions, can
have significantly different properties (including octane and cetane numbers) and combustion
characteristics than the current fuels. Note that over 13 billion gallons of renewables were
used in 2010, primarily from corn-ethanol and some biodiesel. According to the Renewable
Fuel Standard, 36 billion gallons of renewables need to be used by 2022. Also, a joint study
carried-out by Sandia and General Motors has shown that ninety billion gallons of ethanol
(the energy equivalent of approximately 60 billion gallons of gasoline) can be produced in the
US by year 2030 under an aggressive biofuels deployment schedule.
The report is lengthy at places, for instance in the description of technologies which users of
the simulation software are likely to be already familiar with, while too laconic at other places,
e.g. how the selected technologies were modeled in some detail. The draft can benefit from
better balancing of its sections. There should also be more words summarizing the illustrative
results (e.g., provide ranges of benefits), and assessing them critically (e.g., which
technologies seem to incrementally or additively contribute the most), rather than just stating
that the results are in Table 7.1 or in Appendix 3. A discussion of uncertainties present in the
analysis should be presented so as to enable the reader to place the findings into proper
perspective.
                     65

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                                         Verbatim Peer Reviewer Comments in Response to
                                                        Charge Questions
Charge Question
    Topic
    Specific
Assumption/Topic
Comment
 Excerpt
Review
Round
Reviewer
Comment
Other Comments
Other Comments
Other Comments
Other Comments
Other Comments
Other Comments
Other Comments







19
55
159
13
14
429
456
1
1
1
1
1
2
2
Assanis
Assanis
McBroom
Sawyer
Sawyer
Sawyer
Sawyer
The characterization of the modeling methodology as objective and "scientific" suggests that
the simulation is composed of rigorous, first-principle expressions for the various phenomena
without using "correlations", "empirical formulas", and "phenomenological models". Are these
conditions truly met? For instance, in many cases, steady-state dyno test data are the basis
of an engine map featuring a certain technology. In other cases, available data were scaled
based onempirical/proprietary factors and modifiers. The report should not characterize the
study as "scientific" unless data uncertainty is discussed and shown in appropriate situations.
For example, Table 7.1 presents comparisons between simulated and actual vehicle fuel
economy performance. Given the various subjective assumptions involved in the analysis,
the authors should comment whether the noticeable differences in certain cases are
significant.
It would be desirable to show the analysis used to convert fuel consumption savings to
vehicle greenhouse gas (GHG) emissions equivalent output. Ultimately, what matters is the
GHG savings resulting from the combined production and use cycle of alternative fuel
options for combustion engines.
Having conducted a similar effort for USCAR on the PNGV program, I understand that
considerable effort is required to develop such a model. I don't want to diminish all the hard
work that was done, by only offering criticism in the above sections. It appears that the intent
of the approach to this activity is in the right place, just better documentation is needed and
appropriate use guidelines.
The conclusions, Section 1 1, are a reasonable summary of the work conducted.
Including the membership of the advisory committee would be appropriate.
Ricardo, Hybrid Controls Follow-up, 10 Sep 11, 3 p. (proprietary) Report discussed
motor/general efficiency map used for 2020 technology. Projected efficiencies peak at 95%
but most P2 hybrid application if below 90% efficiency.
Comment: I am not qualified to assess if the projected motor/generator efficiencies are
appropriate for 2020-2025 as reported, but they seem low for 15 years in the future.
Ricardo, Assessment of Technology Options, 19 Nov 09, 22 p. (confidential) This document
reviews and rates a range of spark-ignition adaptable technologies to reduce C02 emissions.
Biofuels are included.
Comment: An interesting compendium but some previously reported.
                                                               66

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Verbatim Peer Reviewer Comments in Response to
              Charge Questions
Charge Question
Topic
Other Comments
Other Comments
Other Comments
Other Coments
Other Comments
Other Comments
Specific
Assumption/Topic






Comment
Excerpt
Mn
248
249
250
251
252
253
Review
Round
1
1
1
1
1
1
Reviewer
Wade
Wade
Wade
Wade
Wade
Wade
Comment
The vehicle model and powertrain model were developed and implemented by Ricardo
(201 1) in the MSC.Easy5 software package. The model reacts to driver input to provide the
torque levels and wheel speeds required to drive a specified vehicle over specified driving
cycles. The overall model consists of subsystem models that determine key component
outputs such as torque, speeds, heat rejection, and efficiencies. Subsystem models are
expected to be required for the engine, accessories, transmission, hybrid system (if
included), final drive, tires and vehicle, although the report did not clearly specify the
individual subsystem models used.
A design of experiments (DOE) matrix was constructed and the vehicle models were used to
generate selected performance, fuel economy and GHG emission results over the design
space of the DOE matrix. Response surface modeling (RSM) was generated in the form of
neural networks. The output from each model simulation run was used to develop the main
output factors used in the fit of the RSM. The resulting Complex Systems Model (CSM)
provides a useful tool for viewing the results from this analysis that included over 350,000
individual vehicle simulation cases.
The vehicle and powertrain models/maps and subsystem models/maps used in the analysis
were not provided in the report and could not be reviewed. In most cases, the report stated
that the models/maps were either proprietary to Ricardo (201 1) or at least elements were
proprietary so that they could not be provided for review. Without having these models/maps
and subsystem models/maps, their adequacy and suitability cannot be assessed.
Overall Recommendation: Provide all vehicle and powertrain models/maps and subsystem
models/maps used in the analysis in the report so that they can be critically reviewed.
The technology "package definitions" preclude an examination of the individual effects of a
variety of technologies. For example, for the Stoichiometric Dl Turbo engine, only the
version with a series-sequential turbocharger could be evaluated whereas a lower cost
alternative with a single turbocharger could not be evaluated. Likewise, only the AT8-2020
transmission could be evaluated with the Stoichiometric Dl Turbo engine, while the
substitution of the AT6-2010, as a lower cost alternative, could not be evaluated.
Overall Recommendation: Expand the technology "package definitions" to enable evaluation
of the individual effects of a variety of technologies.
                     67

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                                           Verbatim Peer Reviewer Comments in Response to
                                                           Charge Questions
Charge Question
     Topic
    Specific
Assumption/Topic
Comment
 Excerpt
Review
Round
Reviewer
Comment
Other Comments
                      291
               1
        Wade        Sample Output From Complex System Model (CSM)
                    5/4/2011
                    Relative Percentage Differences Were Added by W. R. Wade (see Exhibit 9)
                                                                  68

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                          Verbatim Peer Reviewer Comments in Response to

                                          Charge Questions
The peer reviewer Dr. Wade included the following ten exhibits in comments.  These are cited in the table
of verbatim comments.


Exhibit 1
Parameter
Engine Displacement
Final Drive Ratio
Rolling Resistance
Aerodynamic Drag
Mass
DoE Range (%)
50
75
70
70
60
125
125
100
100
120
Exhibit 2
Parameter
Engine Displacement
Final Drive Ratio
Rolling Resistance
Aerodynamic Drag
Mass
Electric Machine Size
DoE Ra
P2 Hybrid
50 150
75 125
70 100
70 100
60 120
50 300
nge (%)
Powersplit
50 125
75 125
70 100
70 100
60 120
50 150
Exhibit 3
                             BSFCJgMVh]
     0    1000  2000  3000  4000   6000  6000
               EnginoSyosd [n/min]


 Figure  19: BSFC over the engine operating envelope,
 CR 9.7:1.
                                                 69

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                         Verbatim Peer Reviewer Comments in Response to
                                        Charge Questions
Exhibit 4
                                   L9*C (*t 4Q»?rBIH|
       1
         ••c	
          [»: . :.,

                                                               •
                                                           ., ,
Figure 5-23:
in a
                                                     &wnng
                                              70

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                        Verbatim Peer Reviewer Comments in Response to
                                      Charge Questions
Exhibit 5
Exhibit 6

       533

       4.53
                              >;p»-»«l ; 141 MI

                  F;> 3 IS. 2M4 Pnnj macdr
                      W: A'«« PJ"^> Mac-, re a AC Drr< Eitrcy
    I
    i
       1:3



        i:>

         3
              '


                    *    *
                                        "
                            2C33
    Figure 34: Ei«clrlc Wrttr Ptjmp Machlry* & fij'r CondHtlonlng Drlw EfTOency
                                             71

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                       Verbatim Peer Reviewer Comments in Response to
                                     Charge Questions
Exhibit 7
Feature
Downsizing
BMEP
Turbo Response
Turbine Inlet
Temperature
NEDC fuel economy
Ricardo
Stoichiometric Dl
Turbo Engine
57% (for Std Car)
25-30 bar
1 .5 second time
constant
950C
Not available
Mahle
Turbocharged, Dl
Concept Engine
SAE 2009-01 -1503
50%
30 bar
2.5 second time
constant
(estimated from 4
second total response
time)
1025C
25 - 30% better that
NA baseline
Exhibit 8
Feature
Downsizing
BMEP
Turbine Inlet
Temperature
Fuel RON
Ricardo Stoichiometric
Dl Turbo Engine
57% (for Std Car)
25 - 30 bar
950C
87 PON
(Pump Octane Number)
Lotus Sabre Engine
SAE 2008-01 -01 38
32%
20.1 bar
980C
1050C (common) and
desired
95 RON
Est 91 PON
                                            72

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                       Verbatim Peer Reviewer Comments in Response to
                                     Charge Questions
Exhibit 9

FTP
HWFET
US06
Combined
0-60
mph
Displacement
FDR
Rolling
R.
Aero
Weight
Eng. Eff
Hybird
Class
Conventional SS
Base
(Baseline)
Stoich Dl Turbo
AT8-2020 to DCT
30.0
44.5
48.2%
46.3
4.21%
43.5
54.2
246%
55.3
1 .93%
29.1
32.5
11.7%
33.7
3.51%
34.9
48.4
38.7%
50.0
3.28%
8.3
8.5
8.6
1.04
1.04
1.04
3.23
3.23
3.23
0.00822
0.00822
0.00822
0.69
0.69
0.69
3625
3625
3625
1
1
1



Standard
Car
(Toyota
Camry)
Standard
Car
(Toyota
Camry)
Standard
Car
(Toyota
Camry)
HYBRIDS
P2w/StoichDI Turbo
(Rel to Conv SS SCT)
PS w/Stoich Dl Turbo
(Rel to Conv SS
DCT)
PS w/Akins on CPS
(Rel to Stoich Dl
Turbo)
PS w/Akins on DVA
(Rel to Stoich Dl
Turbo)
61.6
32.96%
57.5
24.00%
55.1
-4.08%
58.3
1 .5%
56.3
1 .80%
53.3%
-3.50%
53.2
-0.18%
54.8
2.7%
36.6
8.89%
36.4
8.24%
38.1
4.61%
38.7
6.1%
59.1
18.23%
55.5
11.11%
54.3
-2.29%
56.7
2.1%
8.6
9.2
8.5
8.5
0.83
0.83
2.4
2.4
3.23
3.23
3.23
3.23
0.00822
0.00822
0.00822
0.00822
0.69
0.69
0.69
0.69
3625
3625
3625
3625
1
1
1
1
24
80
80
80
Standard
Car
(Toyota
Camry)
Standard
Car
(Toyota
Camry)
Standard
Car
(Toyota
Camry)

Exhibit 10
Engines
Baseline
Stoich Dl Turbo
Lean Dl Turbo
EGR Dl Turbo
Atkinson CPS
Atkinson DVA
FTP
42.1
46.3
48.3
48.2
44.5
45.5
HWFET
62.6
55.3
56.4
57.6
59.0
57.1
US06
37.0
33.7
33.9
35.2
35.4
34.5
                                            73

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                                          References
 ..  •'."

Coltman, D., J.W.G. Turner, R. Curtis, D. Blake, B. Holland, RJ. Pearson, A. Arden, and H. Nuglisch,
       2008, Project Sabre: A close-spaced direct injection 3-cylinder engine with synergistic
       technologies to achieve low CO2 output. SAE Paper 2008-01-0138.

Hellenbroich, G., and V. Rosenburg, 2009, FEV's new parallel hybrid transmission with single dry clutch
       and electric torque support. Aachener Koolquium Fahrzeug- undMotorentechnik 2009 18:1209-
       1222.

Lumsden, G., D. OudeNijeweme, N. Eraser, and H. Blaxill, 2009, Development of a turbocharged direct
       injection downsizing demonstrator engine. SAE Paper 2009-01-1503.

PQA  and Ricardo,  2008,  A Study  of potential effectiveness  of carbon dioxide reducing vehicle
       technologies. Prepared for the U.S. Environmental Protection Agency,

Ricardo, Inc., 2011, Computer simulation of light-duty vehicle technologies for greenhouse gas emission
       reduction in the 2020-2025 timeframe. Prepared for the U.S. Environmental Protection Agency.
       April 6, 2011.

Staunton, R.H., C.W. Ayers, L.D. Marlino,  J.N. Chiasson, T.A., Burress,  2006, Evaluation of 2004
       Toyota Prius hybrid electric drive system. ORNL technical report TM-2006/423.

Turner, J.W.G., RJ. Pearson, R. Curtis, and B. Holland, 2009, Sabre: A cost-effective engine technology
       combination for high efficiency, high performance and low CO2 emissions. Low Carbon
       Vehicles 2009: Institution of Mechanical Engineers  (IMechE) conference proceedings.

U.S. Environmental Protection Agency (U.S. EPA), 2006, Peer Review Handbook, 3rd ed. Science Policy
       Council. EPA/100/B-06/002.
                                              74

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                             Appendix A. Charge to Peer Reviewers
    Charge to the Peer Reviewers of Ricardo's "Computer Simulation of Light-Duty Vehicle
  Technologies for Greenhouse Gas Emission Reduction in the 2020-2025 Timeframe" Report

Charge to Peer Reviewers of "COMPUTER SIMULATION OF LIGHT-DUTY VEHICLE
TECHNOLOGIES FOR GREENHOUSE GAS EMISSION REDUCTION IN THE 2020-2025
TIMEFRAME"

       As EPA and NHTSA develop programs to reduce greenhouse gas (GHG) emissions and increase
fuel economy of light-duty highway vehicles, there is a need to evaluate the effectiveness of technologies
necessary to bring about such improvements. Some potential technology paths that manufacturers might
pursue to meet future standards may include advanced engines, hybrid electric systems, mass reduction,
along with additional road load reductions and accessory improvements.

       Ricardo Inc. has developed simulation models including many of these technologies with the
inputs, modeling techniques, and results described in the Ricardo Inc. document "COMPUTER
SIMULATION OF LIGHT-DUTY VEHICLE TECHNOLOGIES FOR GREENHOUSE GAS
EMISSION REDUCTION IN THE 2020-2025 TIMEFRAME"

       EPA is seeking the reviewers' expert opinion on the inputs, methodologies, and results described
in this document and their applicability in the 2020-2025 timeframe.  The Ricardo Inc. report is provided
for review.  We ask that each reviewer comment on all aspects of the Ricardo Inc. report. Findings of this
peer review may be used toward validation and improvement of the report and to inform EPA and
NHTSA staff on potential use of the report for predicting the effectiveness of these technologies.  No
independent data analysis will be required for this review.

       Reviewers are asked to orient their comments toward the five (5) general areas listed below.
Reviewers are expected to identify additional topics or depart from these general areas as necessary to
best apply their particular set of expertise toward review of the report.

       (1) Inputs and Parameters. Please comment on the adequacy of numerical inputs to the model as
represented by default values, fixed values, and user-specifiable parameters.  Examples might include:
engine technology selection, battery SOC swing, accessory load assumptions, etc.)  Please comment on
any caveats or limitations that these inputs and parameters would affect the final results.

       (2) Simulation methodology. Please comment on the validity and applicability of the
methodologies used in simulating these technologies with respect to the entire vehicle. Please comment
on any apparent unstated or implicit assumptions and related caveats or limitations. Does the model
handle synergistic affects of applying various technologies together?

       (3) Results. Please  comment on the validity and applicability of the results to the light-duty
vehicle fleet in the 2020-2025 timeframe. Please comment on any apparent unstated or implicit
assumptions that may affect the results, and on any related caveats or limitations.
                                            A-l

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                              Appendix A. Charge to Peer Reviewers
       (4) Completeness.  Please comment on whether the report adequately describes the entire process
used in the modeling work from input selection to results.

       (5) Recommendations. Please comment on the overall adequacy of the report for predicting the
effectiveness of these technologies, and on any improvements that might reasonably be adopted by the
authors for improvement. Please note that the authors intend the report to be open to the community and
transparent in the assumptions made and the methods of simulation.  Therefore recommendations for
clearly defined improvements that would utilize publicly available information would be preferred over
those that would make use  of proprietary information.

       Comments should be sufficiently clear and detailed to allow readers familiar with the report to
thoroughly understand their relevance to the material provided for review. EPA requests that the
reviewers not release the peer review materials or their comments until Ricardo Inc. makes its report and
supporting documentation public. EPA will notify the reviewers when this occurs.

       If a reviewer has questions about what is required in order to complete this review or needs
additional background material, please contact Susan Elaine at ICE International (SBlaine@icfi.com or
703-225-2471). If a reviewer has any questions about the EPA peer review process itself, please contact
Ms. Ruth Schenk in EPA's Quality Office, National Vehicle and Fuel Emissions Laboratory by phone
(734-214-4017) or through e-mail (schenk.ruth @ epa. gov).
                                              A-2

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C-1

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                      DIONISSIOS (DENNIS) N. ASSANIS

PERSONAL

       Degrees

       Ph.D., Power and Propulsion, Massachusetts Institute of Technology (M.I.T.), 1985
       M.S.,  Management, Sloan School of Management, M.I.T., 1986
       M.S.,  Mechanical Engineering, M.I.T., 1982
       M.S.,  Naval Architecture and Marine Engineering, M.I.T., 1982
       B.Sc., Marine Engineering, Newcastle University, England, 1980

       Positions at University of Michigan

       Director, Michigan Memorial Phoenix Energy Institute, July 2009-date
       Jon R. and Beverly S. Holt Professor of Engineering
       Arthur F.  Thurnau Professor of the University of Michigan
       Chair, Mechanical Engineering, Jan. 2002- Aug. 2007
       Professor of Mechanical Engineering, Sept. 1994-date
       Professor of Applied Physics, 2003-date
       Founding Director for the United States, Clean Vehicle Consortium, U.S.-China
             Clean Energy Research Center, 2010-2015
       Director, Automotive Research Center, Sept. 2000- Oct.2009
       Director, W. E. Lay Automotive Laboratory, 1996-date
       Fellow, Michigan Memorial Phoenix Energy Institute, 2007-date
       Founding Co-Director,  General Motors Collaborative Research Laboratory on
             Engine Systems Research, 2002-2011
       Associate Director, General Motors Satellite Research Laboratory, 1998-2002
       Deputy Director, Automotive Research Center, Jan. 1996-Aug. 2000
       Acting Director, Automotive Research Center, Aug. 1995- Dec. 1995
       Interim Director, CoE Interdisciplinary Professional Programs, Fall 2001
       Founding Director, CoE Automotive Engineering Program, Sept. 1999-Apr. 2002
       Founding Director, MEAM Automotive Engineering Program, 1995-1999

       Positions at University of Illinois in Urbana-Champaign

       Associate Professor of Mechanical Engineering, Aug. 1990 - Aug. 1994
       Head, Thermal Sciences/Systems Division II, Aug. 1992 - Aug. 1994
       Research  Scientist, Office for Supercomputing Applications, Aug. 1991- 1994
       Assistant Professor of Mechanical Engineering, Sept. 1985 -Aug. 1990

       Positions at Other Institutions

       Honorary President, Zhejiang Automotive Engineering Institute, 2009-date
       Honorary Professor, Zhejiang Automotive Engineering Institute, 2009-date
       Advisory  Professor, Shanghai Jiao Tong University, Shanghai, China, 2009-date
       Guest Professor, Shanghai Jiao Tong University, Shanghai, China, 2003-2008
                                                                      Assanis, 1

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Adjunct Research Scientist, Argonne National Laboratory, Energy and
       Environmental Systems Division, May 1987-2002
Research Assistant, Sloan Automotive Laboratory, Massachusetts Institute of
       Technology, Sept. 1982- Aug. 1985
Teaching and Research Assistant, Department of Ocean Engineering, Massachusetts
       Institute of Technology, Sept. 1980-June 1982
Honors and Awards
       ASEE Mechanical Engineering Division Ralph Coats Roe Award,
           2011
       College of Engineering, Stephen S. Atwood Award, 2011
       University of Michigan Rackham Distinguished Faculty Achievement
           Award, 2009
       Member, National Academy of Engineering, 2008
       ASME, Internal Combustion Engine Award, 2008
       ASME Fellow, 2008
       Tau Beta Pi  Professor of the Year Award, 2006
       SAE Award for Research on Automotive Lubricants, 2002
       SAE Fellow, 2001
       Jon R. and Beverly S. Holt Professor of Engineering, 2000
       ASEE Annual Distinguisher Lecturer, College of Engineering, The
           University of Michigan, April 12,  2000
       Teaching Excellence Award, College of Engineering, The University
           of Michigan, 2000
       Arthur F. Thurnau Professor, The University of Michigan, 1999
       Excellence in Teaching Award, Mechanical Engineering and Applied
           Mechanics, The University of Michigan, 1998
       ASME Internal Combustion Engine Division  Meritorious Service
           Award, 1997
       ASME Internal Combustion Engine Division  Speaker Award, 1993,
       ASME Internal Combustion Engine Division  Speaker Award, 1994
       Listed in Who's Who in America, 1994-date
       Listed in Who's Who in Science and Engineering, 1993-date
       Listed m American Men and Women of Science, 1992-date
       University of Illinois Scholar, 1991 - 94
       SAE Russell Springer Award, 1991
       IBM Research Award, 1991

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          ASME/Pi Tau Sigma Gold Medal Award, 1990
          NSF Presidential Young Investigator Award, 1988-93
          Lilly Endowment Teaching Fellow Award, 1988
          NSF Engineering Initiation Award, 1987
          NASA Certificate of Recognition for Creative Development of a
               Technical  Innovation, 1987
          SAE Ralph Teetor Award to Outstanding Young Educators, 1987
          Excellent Teacher, listed every semester in student newspaper
               The Daily HIM, 1985-94
          Honors, B.Sc. Degree with Distinction, 1980


CONTRIBUTIONS TO ACADEMIC LEADERSHIP AND SERVICE

Contributions as Director, Michigan Memorial Phoenix Energy Institute

As the Director of the Michigan Memorial Phoenix Energy Institute (MMPEI),
Professor Assanis leads an  organization that manages the development, coordination
and promotion of multidisciplinary energy research and education programs across
the University of Michigan (UM).  MMPEI's mission is to chart pathways to a secure,
affordable and sustainable energy future.  His current priorities include the
following:

•  Develop the vision for integrated research thrusts on energy generation, storage,
   and utilization, and their interconnection with policy, economics, and social
   impact. Among major efforts, sustainable carbon-neutral transportation has
   emerged as a powerful research theme for UM that closely couples to the broad
   sustainability issues and integrated assessments. Electrification of transport,
   advanced  energy storage in  batteries and renewable fuels, as well as grid supply
   and distribution are of crucial importance to maintain UM's status of being a
   world-leader in automotive  and manufacturing engineering.  In the area of carbon-
   neutral electricity, MMPEI  is bringing into a common energy systems focus the
   campus-wide efforts  in  the areas of nuclear engineering, solar energy, wind, and
   wave energy.  MMPEI  is committed to fostering changes that would facilitate the
   permitting, leasing, construction, and monitoring of renewable energy projects
   while protecting natural resources.

•  Establish  new faculty appointments that combine strengths in science/technology
   with those in public policy,  business, economics and social sciences. Examples of
   multi-disciplinary cluster hires that MMPEI is leading  include energy economics,
   political science and  public  policy, energy storage, sustainable energy and climate
   change impacts. These new searches involve multiple  Departments from the
   College of Engineering, the College of Literature, Science and Arts, the Ford
   School of Public Policy, and the School of Natural Resources and Environment.


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•  Spearhead the development of innovative and transformative energy literacy
   across various media including curricular offerings, workshops, lecture series, and
   seminars. Catalyze cross-disciplinary educational programs in sustainable energy
   across the UM campus and in collaboration with global partners. Enhance the
   integration of energy education and research.

•  Develop partnerships with other academic institutions, national laboratories,
   industry, start-ups, venture capitalists, and economic development agencies  to
   promote scientific discovery and its translation to innovation andjob creation. As
   an exemplar, UM is proud to be among the founding members of the Oak Ridge
   National Lab-led partnership that has won the first, highly competitive DOE
   energy innovation hub for "Advanced Simulation of Light Water Nuclear
   Reactors" funded with $122M for five years. MMPEI played a significant role in
   institutionalizing this strategic partnership which positions UM to attack large-
   scale problems though the establishment of a discovery innovation network.

•  Develop strong international partnerships with first-class peer institutions with the
   strategic objective of tackling global energy and sustainability problems through
   education, research, industry transformation and innovative policies.  For
   instance, MMPEI has significantly contributed to the expansion of the UM-
   Shanghai Jiao Tong University educational collaboration to encompassjoint
   research in renewable energy.  With Tsinghua University and other Chinese and
   US partners in academia, industry and national labs,  we have recently won the
   competition for establishing the highly visible U.S.-China Clean Energy  Research
   Center on Clean Vehicles funded with over $50M for the next five years. With the
   Fraunhofer Institutes of Germany, we have initiated a landmark international
   collaboration aimed at the transformation of the transportation industry towards
   electrical mobility.  With the National University of Singapore, UM is proposing
   thejoint development of renewable energy technologies and policies for  high-
   density urban communities that will be demonstrated in Singapore, an ideal  test
   bed for sustainability.
•  Under Dr. Assanis' leadership, MMPEI is pursuing a two-pronged approach for
   the development of comprehensive building facilities for the Institute.  First, the
   UM Regents are funding  a $11M renovation and expansion of the Phoenix
   Memorial Laboratory to provide state-of-the-art space for energy research, as well
   as the home for MMPEI's administrative and collaborative functions.  In parallel,
   MMPEI  is developing a staged plan for the establishment of a multi-disciplinary
   hub for innovation and entrepreneurship in renewable energy, in partnership with
   other UM Centers, at the  UM North Campus Research Complex.

Contributions as Chair of Mechanical Engineering

As Chair of the Department of Mechanical  Engineering (ME) at the University of
Michigan (2002-2007), Professor Assanis led the administration and long-range
development of the ME Department's academic and research programs. The ME
Department  is a major academic unit that is educating more than 700 undergraduate
students and 500 graduate students (250 Master's and 250 PhDs), and employing 55
tenured and tenure track professorial faculty members, 18 primary research scientists

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and 70 support staff members in a physical plant of approx. 120,000 square feet spread
out over four buildings. Throughout his tenure as ME Chair, the Department's
undergraduate and graduate programs were consistently ranked within the top five
nationally by U.S. News and World Report.  Also, based on data from the 2005-06
academic year, the National Research Council rated the ME graduate program as #4 in
the country based on both regression and survey rankings.  His efforts have made
significant contributions in the following areas:

•   Planned strategically to establish and articulate a shared vision for the future that
    sustains and evolves the ME Department's core academic and research strengths in
    automotive and manufacturing engineering, while also developing a competitive
    position into the emerging areas of mechanical engineering, including bio-systems,
    energy/ eco-systems and micro/nano-systems. As the culmination of  these strategic
    planning efforts, a major addition and remodeling of the ME Building facilities, has
    emerged as the #2 all-campus building priority for UM's capital outlay plan over the
    next five years.

•   Successfully retained the ME Department's excellent body of faculty  and hired
    outstanding new faculty (11 new Professors and 15 Research Scientists). Promoted
    in rank 27 faculty members, including 5 women faculty who reached  the rank of
    Professor.   In addition to assessing and rewarding the performance of professorial
    faculty, implemented procedures for the annual review and merit raises of primary
    research faculty.  Mentoredjunior faculty members in their professional careers and
    made a deliberate effort to address issues that could compromise their success.
    Nominated a number of colleagues, students, alumni and staff who received
    prestigious professional awards, both outside and within the University, including
    four new endowed chairs.

•   Enhanced the ME  Department's efforts to create a multi-cultural and  diverse
    intellectual environment by retaining all women and underrepresented minority
    (URM) faculty; by hiring thee more women faculty members for a total  of 10 (18%
    of ME faculty); by strategically recruiting URM and women students  through K-12
    programs, the Detroit Area Pre-College Engineering Program, and the NSF Research
    Experience for Undergraduates Program; and by supporting mentorship groups
    including Unified Minority Mechanical Engineers and Society of Women Engineers.
    Improved communications among the students, alumni, faculty and staff.

•   Oversaw financial planning, budgets and expenditures for the ME  Department
    (annual budget of approx. $14M in general funds and more than $28M in research
    funds and gifts) and introduced "paperless" electronic tools in the areas of student
    services, financial  reporting, and faculty recruiting.  Participated in fundraising and
    pubic relations efforts for the  ME Department and College of Engineering in close
    coordination with the development staff.  Through these efforts, new  endowed
    professorships, a number of undergraduate student scholarships, and new graduate
    fellowships  from industry, and a prestigious named lectureship series  about the role
    of the Engineer in Society have been attracted to the M E Department.

•   Made significant progress towards a "paperless" administration through the
    development and implementation of electronic solutions in the areas of student

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   services (with web-based graduate application and admissions tracking systems),
   financial reporting (with accounting statements for contracts on line), faculty
   recruiting and faculty data center.

   Promoted the systematic exchange of faculty and students with strategically selected
   global partners, notably with the Shanghai Jiao long University, the Korean
   Advanced Institute for Science and Technology, Seoul National University and the
   Technical University of Berlin.

   Enhanced the strong tradition of an active and engaged External Advisory Board
   (EAB) which has served as a model for other CoE Departments and the University
   of Michigan's Transportation Research Institute (UMTRI).

   Promoted the development of K-12 programs intended to spark the interest of the
   brightest youngsters - including women and traditionally underrepresented groups in
   math, science and engineering.
Contributions as Director of Automotive Engineering Program

   As the Founding Director of the Master's of Engineering Program in Automotive
   Engineering (AUTO), I was responsible for designing the curriculum and launching
   the new degree Program, first in the Department of Mechanical Engineering and
   subsequently as a College-wide program in the College of Engineering.  My
   responsibilities have included recruiting prospective students, advising all M.  Eng.
   students, developing new courses, and pursuing international collaborations for
   joint degree offerings with global Universities, and especially Aachen (Germany)
   and Loughborough (UK) as part of the Ford Global Automotive Systems Master's
   degree. As part of our curriculum improvement activities, I  founded the College of
   Engineering AUTO Council and led its efforts to develop and evolve a strong
   academic curriculum that meets industry needs.  I also worked very effectively
   with the UM Center for Professional Development to offer to industry a  distance-
   learning version of our M.Eng. Program. Our visionary pursuit of distance learning
   teaching has set a standard for other programs to emulate.

   Overall, I strived to grow our  AUTO program, while simultaneously improving the
   quality of the entering students and courses offered. Our goals were met with great
   success, as evidenced by the enrollment in the AUTO program, which exceeded
   100 students within 5 years from the program's introduction, and the excellentjob
   placement and very positive feedback expressed by many of our continuing students
   and graduates.
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   Contributions as Interim Director of Interdisciplinary Professional Programs

      As the Interim  Director of the College of Engineering's Interdisciplinary
      Professional Programs (INTERPRO), I provided stability and leadership during a
      period of transition and growth to six interdisciplinary programs, automotive
      engineering, financial engineering, integrated micro-systems, manufacturing
      engineering, pharmaceutical engineering, and plastics engineering.  During my
      tenure as Director and working with the INTERPRO Directors' Council, I oversaw
      the management of the large growth in student enrollment which reached an all time
      high (320 enrolled students) in the history of the INTERPRO programs.  Most of
      this growth was accounted by part-time, distance learning professionals. I stepped
      down from my role as INTERPRO Director and AUTO Program Director to
      assume the position of Chair of Mechanical Engineering.
OTHER CONTRIBUTIONS TO SERVICE

       Major Committee Assignments at University of Michigan

       University of Michigan Committees:
       Vice President of Research Committee on Entrepreneurship, 2011
       Vice President of Research Director's Council, 2009-date
       North Campus Research Complex,  Director's Committee, 2009-2010
       Rackham Distinguished Faculty Achievement Award Committee, 2009-2011
       Panel on  Engagement/Institutes, Site Visit  of High  Learning  Commission on
          University Re-Accreditation, March 2010
       UM Energy Council, Founding Member, 2003-2007
             Charter member of the team that actively pursued the development of a
             UM research thrust on Energy working in partnership with other
             Colleges, articulated the vision statement for the thrust, and recommended
             to the  UM administration the development of a University-wide Energy
             Laboratory at the site of the decommissioned nuclear reactor.
       President's Committee on Intellectual Property Policy, 2001-02, Member
       University Senate, 1995-98,  Elected Senator

       College of Engineering Committees:
       College of Engineering (COE) Budget Task Team, 2005-07, Member
       COE Center of Professional Development Executive Committee, 2005-06,
             Member
       COE Faculty  Fellows Program, October 11-12, 2002, Panelist
       COE Interdisciplinary Professional  Program Directors Committee, 2001, Chair
       COE Nominating Committee, 2000-2001, Chair
       COE Automotive Council, 1999-date, Chair
       COE Curriculum Committee, 2000, Member
       COE Committee on Reshaping Graduate Education at the Master's Level,
             1998-99, Member
       COE Committee on M. Eng. Programs, 1998-99, Member
       COE UM-National University of Singapore Committee on Establishment of


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             Joint M.Eng. Program in Automotive Engineering, 1997-98, Chair
      COE Committee on Faculty Incentives for Continuing Education (ICE) and
             Distance Learning Instruction, 1997-98, Member

      Departmental Committees:
      ME Honors and Awards Committee, 2008-2011
      ME (formerly MEAM) Advisory Committee,
             Elected Member 1995-96,1997-98 and Fall 2001
             Chair, 2002-2008
      ME (formerly MEAM) Planning Committee
             Member, 1997-98
             Chair, 2002-2008
      MEAM Thermal Science Instructional Area Coordinator, 1997-2000
      MEAM Space Task Force Committee, 1996-98, Member
      W. E. Lay Automotive Laboratory Test Cell Committee, 1994-present, Chair
      W. E. Lay Automotive Laboratory Renovations Committee, 1994-95, Member
      MEAM Laboratory and Safety Committee, 1995-1998, Member
Service to Other Organizations

      1.  External Boards

      Member, Board of Directors, NextEnergy, a non-profit organization with a
           mission to be one of the nation's leading non-profit research catalysts
           and business accelerators for alternative and renewable energy, 2010-
           date.

      Member, Board of Directors, Consortium for Advanced Simulation of Nuclear
           Reactors,   an energy innovation hub  led  by Oak  Ridge National
           Laboratory (ORNL) and funded by DOE up to $122 million, 2010-2015.

      Member,  President's  Council  of Advisors  on  Science  and  Technology
           (PCAST) Working Group on Energy Technology Innovation System,
           2010.

      Co-Chair, National  Academy  of Engineering  Annual  German-American
           Frontiers of Engineering GAFOE Symposium, 2010-2012.

      Member, Science and Technology Council Advisory Board, Cummins Engine
           Company, Inc., Columbus, IN, 2010.

      Member, International Advisory Board, Center for Clean Combustion Energy,
           Tsinghua University, China, 2010-2013.

      Chair, Advisory Board, Tula Technology, Santa Clara, CA, 2009-date.

      Member, State of Michigan Great Lakes Wind Council, 2009-2010.
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Member,  Energy Council  of  the CTO  Forum,  a Silicon  Valley-based
     organization that  brings together Chief Technology Officers from  a
     cross-section of businesses and industries to discuss critical issues at the
     intersection of technology, energy and the environment, 2009-date.

Member, External Advisory Board, Center for Mobile Propulsion, RWTH
     Aachen University, 2009-date.

Member, National Academy of Sciences Committee on  Fuel  Economy of
     Medium- and Heavy-Duty Vehicles, appointed by the National Research
     Council's Board on Energy and Environmental Systems, 11/08-5/31/10.

Member, ASME  Internal Combustion Engine Division Executive Committee,
     2008-10.

Chair,  King Abdullah  University of Science  and Technology  (KAUST)
     Search for Director of Center for Clean Combustion Energy, 2008-09.

Member, External Validation Panel for Launching MSc degree in Automotive
     Engineering Design,  Hong Kong Polytechnic University, 2007.

Member,  Global  External  Advisory  Board,  Department  of Mechanical
     Engineering, Korean Advanced  Institute  for Science and Technology
     (KAIST), 2006-2008.

Member, External Advisory Board, Department of Mechanical  Engineering,
     Georgia Tech, 2004-date.

Member, External Advisory Panel, "Business  Briefing: Global Automotive
     and Manufacturing and Technology,"  World Market Research Centre,
     May 2002.
2.  Editorships

Editor, InternationalJournal of Automotive Technology, 2008-2011

Editorial Board, InternationalJournal of Powertrains, 2010-date

Editorial Board, InternationalJournal of Engine Research, 2003-2012

Editorial Board, InternationalJournal of Automotive Technology, 2005-2008

Associate Editor, ASME Journal for Gas Turbines and Power, 1996-2007

Scientific Board, Ingineria Automobilului, 2007-date

Guest Editor, International Journal of Heavy Vehicle Systems, 2004



                                                               Assanis, 9

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3.   Professional Society Memberships

American Society of Mechanical Engineers, Fellow
         Executive Committee Member, ICE Division, 2008-2013
         Journal Associate Editor, 1996-2008
         Past Chair of Student Activities, ICE Division
Society of Automotive Engineers, Fellow
         Member,  SAE  Research Executive Committee, 2000-date
         Faculty Advisor, University of Michigan, 1996-2004
         CoE Future Car, Faculty Co-Advisor, 1997-98
         Member,  Advanced Powerplant Committee
         Member,  Passenger Car Readers Committee
         Member,  Vehicular Heat Exchanger and Heat Transfer Committee
American Society for Engineering Education, Member
Sigma Xi, Member
New York Academy of Sciences, Member
The Combustion Institute, Member
Society of Naval Architects and Marine Engineers, Associate Member
4.  Organizing and Chairing Conferences, Sessions, Workshops, Lectures

Co-Chair and Co-Organizer,  Michigan  Memorial Phoenix Energy  Institute  and
     Fraunhofer Institutes of Germany Joint Conference, "Towards Carbon Neutral
     Vehicles," Plymouth, Ml, October 21, 2010.
Moderator,  Panel on "Fuel Economy and Clean  Transportation of the  Future,"
     Michigan Memorial Phoenix  Energy Institute  and Fraunhofer Institutes of
     Germany Joint Conference, "Towards Carbon Neutral Vehicles," Plymouth,
     Ml, October 21, 2010.
Chair, Plenary Session  on  "Future  Mobility - Energy,  Environment  &  Carbon
     Management," Emissions 2010, Michigan League,  University  of Michigan,
     Ann Arbor, June 15-16, 2010.
Co-Organizer  and Co-Chair, 11th International  Conference on Present and Future
     Engines for Automobiles, Shanghai, China, May 30-June 3, 2010.
Organizer, 3rd Annual   Michael E.  Korybalski  Endowed  Lecture in Mechanical
       Engineering:  "Engineering,   Innovation  and  the  Challenges of  the  21st
       Century," given  by  Charles Vest, President NAE and Emeritus President,
       M.I.T., May 12, 2010
Co-Chair, National Academy of Engineering Annual German-American Frontiers of
     Engineering GAFOE Symposium, Oak Ridge National Laboratory, Oak Ridge,
     TN, April 22-25, 2010.
Chair and Co-Organizer, ARC Annual  Conference, "Critical  Technologies for
       Modeling and Simulation of Ground Vehicles," May 12-13, 2009
Organizer, 2nd Annual  Michael E.  Korybalski Endowed  Lecture in Mechanical
       Engineering:  "Size  Matters," given  by Dr. Roger  McCarthy, Emeritus
       Chairman and CEO,  Exponent, Inc., May 4, 2009
Chair, Prime Power, National  Defense Industrial Association - Michigan  Chapter,
       Power and Energy Workshop, Troy, Ml,  November 18-19, 2008
Chair and Co-Organizer, ARC Annual  Conference, "Critical  Technologies for
       Modeling and Simulation of Ground Vehicles," May, 2008
                                                                 Assanis, 10

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Member  of  Scientific  Committee,  International  Workshop  on  Advances  in
       Combustion Science and Technology, India Institute of Technology, Kanpur,
       India, Dec. 31, 2007- Jan. 8, 2008
Organizer,  Inaugural   Michael  E.  Korybalski Endowed  Lecture  in  Mechanical
       Engineering:  "Driving  to a Sustainable  Future, a  New DNA for the
       Automobile,"  given by Dr. Lawrence Burns, VP Research, Development and
       Planning, General Motors
Chair and  Co-Organizer, ARC  Annual  Conference,  "Critical  Technologies for
       Modeling and Simulation of Ground Vehicles," May, 2007.
Member  of Scientific Committee,  2nd International  Symposium on  Clean and
       Efficient Combustion Engines, Tianjin, China, July 10-13, 2006.
Chair and  Co-Organizer, ARC  Annual  Conference,  "Critical  Technologies for
       Modeling and Simulation of Ground Vehicles," May, 2006.
Chair and  Co-Organizer, ARC  Annual  Conference,  "Critical  Technologies for
       Modeling and Simulation of Ground Vehicles," May, 2005.
Chair and  Co-Organizer, ARC  Annual  Conference,  "Critical  Technologies for
       Modeling and Simulation of Ground Vehicles," May, 2004.
Co-Organizer, "Premixed Charge  Compression Ignition Engines," 2003  JSAE/SAE
       International Spring Meeting, Yokohama, Japan, May 19-22, 2003.
Chair and  Co-Organizer, ARC  Annual  Conference,  "Critical  Technologies for
       Modeling and Simulation of Ground Vehicles," May, 2003.
Co-Organizer and Chair, "Homogeneous Charge Compression  Ignition Engines,"
       2003 SAE World Congress, Detroit, Ml, March 3-6, 2003.
Chair and  Co-Organizer, ARC  Annual  Conference,  "Critical  Technologies for
       Modeling and Simulation of Ground Vehicles," May, 2002.
Organizer,  "Homogeneous Charge  Compression  Ignition Engines,"   2002  SAE
       International Spring Fuels & Lubricants Meeting, Reno, Nevada, May  6 -  8,
       2002.
Co-Organizer,  "Advanced  Hybrid  Powertrain Systems," 2002  World  Congress,
       Detroit, Ml, March 4-7, 2002.
Co-Organizer, "Homogeneous Charge Compression  Ignition Engines," 2002 World
       Congress, Detroit, Ml, March 4-7, 2002.
Co-Organizer and Chair, "Homogeneous Charge Compression  Ignition Engines,"
       ASME Fall Technical Conference, Argonne, IL, Sep. 23-26, 2001.
Co-Organizer, "Homogeneous  Charge Compression  Ignition Engines,"  SAE  2001
        Fall  Fuels and  Lubricants International Conference, San  Antonio, TX,
        September 24-27, 2001.
Member, Advisory Committee,   COMODIA  2001,  International  Symposium on
        Diagnostics and Modeling of Combustion in Internal Combustion Engines,
        Nagoya, Japan, July 1-4, 2001.
Organizer and Chair,  "Homogeneous Charge Compression Ignition Engines," SAE
        2001  Spring  Fuels  and Lubricants International Conference, Orlando,
        Florida, May 7-9, 2001.
Chair and  Co-Organizer, ARC  Annual  Conference,  "Critical  Technologies for
       Modeling and Simulation of Ground Vehicles," May 15-16, 2001.
Co-Organizer and Co-Chair, "Hybrid Electric Vehicles," SAE International Congress
       and Exhibition, March 5-8, 2001.
Co-Organizer and Chair, "Novel  SI and Cl Combustion Systems," SAE  2000  Fuels
       and Lubricants International Conference, Paris, France, June 19-22, 2000.
Co-Organizer and Session Chair,  ARC  Annual Conference, "Critical Technologies
       for Modeling and Simulation of Ground Vehicles," May 2000.
Co-Organizer, "Direct Injection Engines and  Sprays," ASME-ICE Sprint Technical
       Conference, San Antonio, TX, April 9-12, 2000.


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Co-Organizer,  "Homogeneous  Charge  Compression  Ignition  Engines,"  SAE
       International Fuel and Lubricants  Meeting, Toronto, Canada, Oct.  25-28,
       1999.
Organizer, "Modeling and Simulation of Direct Injection Engine Processes," ASME-
       ICE Fall Technical Conference, Ann Arbor, Ml, Oct. 16-20, 1999.
Host, ASME-ICE Fall Technical Conference, Ann Arbor, Ml, Oct. 16-20, 1999.
Member of Technical Program Committee, Vehicle Thermal Management Systems
       VTMS-4  International Conference, London, UK, May 24-26, 1999.
Co-Organizer and Session Chair, ARC  Annual Conference, "Critical Technologies
       for Modeling and Simulation of Ground Vehicles," May 1999.
Organizer, "Modeling and Simulation of Engine Combustion Processes," ASME-ICE
       Spring Technical Conference, Columbus, IN, April 24-28, 1999.
Organizer, "Advanced Diesel Engine Powertrains," SAE  International Congress and
       Exposition, Detroit, Ml, Feb. 23-26, 1999.
Organizer, "Modeling and Simulation of Engine Combustion Processes," ASME-ICE
       Fall Technical Conference, Clymer, New York, September 27-30, 1998.
Moderator, "The Future  of Automotive Systems," SAE Automotive Systems Testing
       Topical Technical Symposium (TOPTEC), Novi, Ml, October 14-15, 1998.
Co-Organizer and Session Chair, ARC  Annual Conference, "Critical Technologies
       for Modeling and Simulation of Ground Vehicles," May 1998.
Chair, Panel on Surface  Engineering and Tribology, SAE International Congress and
       Exposition, Detroit, Ml, Feb. 23-26, 1998.
Organizer, "Adiabatic and Miller Cycle Engines,"  SAE International  Congress and
       Exposition, Detroit, Ml, Feb. 23-26, 1998.
Organizer, "New  Analytical  Methods in Engine Design," ASME-ICE Fall Technical
       Conference, Madison, Wl, Sept.  27 - Oct. 1, 1997.
Co-Organizer and Session Chair of ARC Annual Conference, "Critical Technologies
       in  Modeling and Simulation of Ground Vehicles," June 3-4,  1997.
Member of Technical Program Committee, Vehicle Thermal Management Systems
       VTMS-3  International Conference, Indianapolis, IN,  May 19-22, 1997.
Organizer,  "New  Analytical  Methods  in  Engine  Design,"  ASME-ICE Spring
       Technical Conference,  Fort Collins, Colorado, April 27-30, 1997.
Co-Organizer, "Adiabatic Engines",  SAE  International  Congress  and Exposition,
       Detroit, Ml, 1997.
Member, Program Review Subcommittee, Twenty-Sixth International Symposium on
       Combustion, Naples, Italy, July 28-Aug. 2, 1996.
Co-Organizer and Session Chair, ARC  Annual Conference, "Critical Technologies
       for Modeling and Simulation of Ground Vehicles," May 29-30, 1996.
Organizer, Student Paper  Competition, ASME  ICE Fall  Technical Conference,
       Fairborn,  OH, Oct. 20-23,1996.
Co-Organizer and  Chairman,  "Engine  Simulations," ASME ICE Fall  Technical
       Conference, Fairborn, OH, Oct. 20-23, 1996.
Co-Organizer, "Adiabatic Engines,"  SAE  International  Congress  and Exposition,
       Detroit, Ml, 1996.
Organizing  Committee,   Fraunhofer  Institute-University   of   Michigan   Joint
       Conference, "The  Best  of  German/American Automotive  Technology,"
       Southfield,  Ml, June 27-28,  1995
Co-Organizer and  Chairman,  "Engine  Simulations," ASME Engine Technology
       Spring Conference, Marietta, Ohio, April 23-26, 1995.
Co-Organizer and Session Chair of ARC Annual Conference, "Critical Technologies
       in  Modeling and Simulation of Ground Vehicles," April 19-20, 1995
Co-Organizer, "Adiabatic Engines,"  SAE  International  Congress  and Exposition,
       Detroit, Ml, 1995.
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Chairman and Co-Organizer,  "Modeling Engine Processes," ASME Fall  Technical
       Conference, Lafayette, IN, 1994.
Chairman and Co-Organizer,  "Adiabatic  Engines," SAE International Congress and
       Exposition, Detroit, Ml, 1994.
Chairman and  Organizer, "Engine Design," Energy Technology Conference and
       Exhibition, New Orleans, LA, 1994.
Chairman  and  Co-Organizer,  "Engine  Simulation  and  Controls,"  ASME  Fall
       Technical Conference, Morgantown, WV, 1993.
Co-Chairman, "Engine Sprays," I LASS, Worcester, MA, 1993.
Chairman, "Vehicle Cooling Systems," International Conference on Vehicle Thermal
       Management Systems, Columbus, OH, 1993.
Chairman and Co-Organizer,  "Adiabatic  Engines," SAE International Congress and
       Exposition, Detroit, Ml, 1993.
Vice-Chairman and Co-Organizer, "Intake Air Management,"  Energy Technology
       Conference and Exhibition, Houston, TX, 1993.
Chairman  and Co-Organizer, "Adiabatic  Engine Components," Vice-Chairman,
       "High Temperature Engine Heat Transfer," SAE International Congress and
       Exposition, Detroit, Ml, 1992.
Vice-Chairman  and  Co-Organizer,  "Engine  Simulation,"  Energy  Technology
       Conference and Exhibition, Houston, TX, 1992.
Co-Organizer,  "Panel  on  Post-95  Low  Emission  Engines,"  ASME  Energy
       Technology Conference and Exhibition, Houston, TX, 1991.
Moderator and Co-Organizer, "Panel on Post-95 Low Emission Engines," SAE
       International Congress and Exposition, Detroit, Ml, 1991.
Chairman  and Co-Organizer, "Adiabatic  Engine Components," Vice-Chairman,
       "High Temperature Engine Heat Transfer," SAE International Congress and
       Exposition, Detroit, Ml, 1991.
Chairman  and Co-Organizer, "Adiabatic  Engine Components," Vice-Chairman,
       "High Temperature  Engine Operation,"  SAE International  Congress and
       Exposition, Detroit, Ml, 1990.
Vice-Chairman,  "Basic  Engine  Processes,"  Energy Technology  Conference and
       Exhibition, Houston, TX, 1989.
Chairman  and Co-Organizer, "Adiabatic  Engine Components," Vice-Chairman,
       "High Temperature Tribology," SAE International  Congress and Exposition,
       Detroit, Ml, 1989.
Vice-Chairman  and  Co-Organizer,   "International  Symposium  on  Flows  in
       Reciprocating  Internal   Combustion  Engines,"  ASME  Winter  Annual
       Meeting, Chicago, IL, 1988.
 Vice-Chairman,  "Basic   Engine  Processes," American   Society of  Mechanical
       Engineers, Energy Technology Conference and Exhibition,  New Orleans,
       LA, 1988.
Assistant Chairperson, "High  Temperature Tribology," SAE International Congress
       and Exposition, Detroit, Ml, 1988.
Chairman, "Engine  Simulation  Studies,"  International  Association for Vehicle
       Design Fourth International Congress, Genera, Switzerland, 1987.
Assistant Chairperson,  "Adiabatic  Engines,"  SAE  International  Congress  and
       Exposition, Detroit, Ml, 1987.
5.  Service as Consultant to Government and Industry

Assanis and Associates, Inc., President, Ann Arbor, Ml (2000-date)
Optimetrics, Inc., Ann Arbor, Ml (1999)

                                                                   Assanis, 13

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       Textron Automotive, Southfield, Ml (1998)
       M.A.N.A.G.E., Inc., President, Ann Arbor, Ml (1995-1998)
       Automated Analysis Corporation, Ann Arbor, Ml (1996)
       Mobil Technology Company, New Jersey (1996-1997)
       GM Electromotive Division, La Grange,  IL (1988-1992)
       National Aeronautics and Space Administration, Cleveland, OH (1988)
       Adiabatics, Inc., Columbus, IN (1986-1991)
       Science Application International Corp., Seattle, WA (1986-1987)
CONTRIBUTIONS TO EDUCATION

       Sustained Commitment to Education

             I  have sustained my passionate commitment to education for over 20 years.
       As an Assistant and Associate Professor at the University of Illinois at Urbana-
       Champaign, I have taught a range of thermal science courses with student
       evaluations of my teaching consistently placing  me at the very top in a group of 50
       faculty members. Afterjoining the University of Michigan, my teaching
       evaluations (4.74/5.0 average for the quality of the courses I have taught and
       4.85/5.0  for the effectiveness of my teaching) have  continued to be among the
       highest in the Mechanical Engineering Department (55 tenured or tenure track
       faculty) and the College of Engineering (more than 320 faculty members).

             In 1987, I was honored with the Society  of Automotive Engineers Ralph
       Teetor Award, given to 20 outstanding engineering educators nationwide each year.
       In 1988,  I was one of six young UIUC faculty members selected in campus-wide
       competition to receive Lilly Teaching Fellow Awards. In 1990, I received the
       American Society of Mechanical  Engineers/Pi Tau  Sigma Gold Medal Award given
       annually in nationwide competition to the best mechanical engineer 10 years  after
       graduation.  In 1991-94, I was named University of Illinois Scholar for my
       contributions to research and teaching. I  am truly gratified to have been honored
       with the  1997-98 MEAM Excellence in Teaching Award, the 2000 College of
       Engineering Teaching Excellence Award, the distinguished Arthur F. Thurnau
       Chaired Professorship, and as the inaugural recipient of the Jon R. and Beverly S.
       Holt Chaired Professorship.
       Teaching Philosophy
             I  have always felt that a successful educator must love teaching and be able
       to convey excitement for learning to his/her students. Many of my activities as a
       teacher and mentor are governed by my strong belief that the key to effective
       teaching is to be enthusiastic about your teaching and to genuinely care about
       passing your knowledge to your students.  I personally strive to show my students
       my own  excitement about the material and to motivate them to make a sincere

                                                                      Assanis, 14

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effort to master the subject.  I have always emphasized the importance of an
engaging and interactive teaching-learning process, and created an open and
informal atmosphere in the class that encourages students to ask or answer
questions. I  have taken some bold steps to shift the paradigms of teaching
theoretical concepts to engineers, infused my own scholarly activities into the
classroom and shared my teaching techniques with my colleagues and future
educators. I  have stressed my belief that the only way to learn a subject is through
hard work and application of your knowledge to real projects, and repeatedly found
that students will work hard as long as they are motivated, encouraged when they
face adversity and rewarded for their intellectual accomplishments.
       Beyond the traditional classroom teaching, I have  adopted a holistic
approach to the teaching/learning process and utilized effectively the time outside
the classroom to advise, mentor, coach and teach the students.   I have advised
more than 50 doctoral, 100 Master's and M.Eng. students and hundreds of
undergraduate students.  I believe that sound advice and broadening of their
perspective can have a critical impact in the students' future careers. I am gratified
that several of my students have emulated me as a role model and havejoined
academia, including (within the past five years) Clemson  University, The Cooper
Union for the Advancement of Science and Art, Kansas University, Texas A&M
University, United States Merchant Marine Academy and the University of
Michigan. I  have also greatly enjoyed being the Faculty Advisor of the student
chapters of the Society of Automotive Engineers and the American Society of
Mechanical Engineers, working with the various student project teams, helping
them in their fundraising efforts, and addressing their technical and administrative
needs. Getting to know the undergraduate students better and contributing to their
education outside the classroom through special projects is time  consuming, but can
be extremely rewarding to both the students and the teacher.
Teaching Innovations

       I am particularly proud of the new perspective I  have brought to the student
teaching and learning process. The traditional way of teaching undergraduate
courses in thermo-sciences and their applications to energy conversion and internal
combustion engines has been through lectures and the use of highly idealized
models. These ideal models inherently make crude assumptions so that results are
often far from  reality.  Without compromising teaching of the fundamentals, I have
introduced  an innovative approach to further the education of my students through
the incorporation and coordinated use of a series of hands-on laboratories, computer
simulation tools, scientific movies, and real life case studies that are presented
within and  in parallel with the lectures.  Sophisticated laboratory experiments and
realistic simulation programs provide a more complete understanding of the
important physical processes.  Students can use the simulation models to compare
and analyze their experimental data under similar operating conditions, and suggest
ways to improve either the simulation models or the experimental techniques.
                                                                Assanis, 15

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       In my continuing efforts to enrich the class content, I  have also relied on the
use of the internet and distance learning.  With my graduate student instructors, we
have developed integrated learning environments that can be used asynchronously,
and at the student's learning pace, to bring together lecture notes, the blackboard,
assignments, solutions, clipboards, laboratory demos, simulation runs and engine
movies in digital media. We are now planning to run laboratory experiments live
from the classroom, or for that matter from any internet connection, to enable
students to appreciate lecture content and theory in the light of reality with live
demonstrations. Through these innovative approaches, I constantly strive to add
another dimension to the student learning.
Infusion of Scholarly Contributions into Teaching-Learning Process

       My teaching interests parallel and complement my research interests, as my
philosophy is that an excellent teacher must be at the same time a leader in his field
of research. Only this way I feel I  can give my students the best and most relevant
education to enable them become leaders in their fields. In the course of my
group's research activities, we have developed a large body of engine simulation
software that is extensively used by automotive manufacturers in engine
development.  With the ever-increasing capabilities of personal computers and
graphical programming languages  such as C++ and MATLAB-SIMULINK, it has
become possible to infuse user-friendly, student versions of these computer
simulations to the classroom, thus  greatly contributing to my effective teaching.
My research activities have also enabled me to rejuvenate the Walter Lay
Automotive Laboratory, thus contributing advanced engine experiments to our
classes and exposing our students to state-of-the-art laboratory set-ups
(http://me.engin.umich.edu/autolab/). These activities have contributed to
reaffirming U of M's leadership in automotive engineering.
Contributions to New Course Development
       Although the University of Michigan has had a long tradition of excellence
in the instruction of internal combustion engines, when I started my career as a
Professor at Michigan I realized that our engine-related courses and research
facilities were not adequate to meet the current demands of the industrial and
research communities for automotive engineers.  In order to give our students the
best possible education in the field, I have taken a series of steps. First, I
completely revised the lectures of our undergraduate/beginner graduate course (ME
438) in internal combustion engines. In addition,  I developed and incorporated a
series of laboratories as part of the course, which was thus converted from three to
four credit hours.  This course enrollment has almost doubled in size following my
revisions, and has been offered simultaneously via distance learning to industry.
Second, based on  my scholarly activities, I developed a graduate level course
(originally ME 534 and now renumbered as ME538) that deals with the application
of thermal sciences to the simulation and design of modern combustion engines.
Third, I have developed with my  undergraduate and graduate students a single-

                                                                 Assanis, 16

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cylinder engine laboratory experiment that has been used as part of our thermal
science laboratory class.

      As part of my activities as the Director of the Automotive Program, I
oversaw the development of the curriculum for the new degree program and
contributed a number of the new modules that were essential to achieving the goals
M.Eng. program.  In order to broaden the horizons of automotive engineers, I
introduced a two semester sequence of automotive seminars (ME 591 and ME 592,
now renumbered as ME 501), delivered by industry leaders, that exposed the
students to the wide spectrum of interdisciplinary engineering activities involved in
the process of development, design, and manufacturing of complex automotive
systems.  In one of its offerings, the UM automotive seminar class was focused on
Vehicle Energy, in global collaboration with Aachen University, Germany, and
Ford Motor Company. Furthermore, to provide our automotive engineering
students with practical experience in team building, carrying out projects in
interdisciplinary teams, and in developing and managing projects, I introduced the
capstone M.Eng. Automotive project (ME 593, now renumbered as ME 502). The
Automotive Seminars and Project experiences we provide our students have been a
model for similar "practimum" programs introduced by several Departments in the
College of Engineering.

      As part of my activities as the Director of the Michigan Memorial Phoenix
Energy Institute,  I have co-developed and moderated a graduate level
interdisciplinary seminar on "The Power of And'. Energy Systems and Policy
Opportunities for the  U.S." The objective of the seminar series is to introduce the
audience to the power of integrated energy systems and the promise it holds to craft
an energy policy  for the United States  that ensures plentiful  and low-cost energy,
national security  and sustainable economic growth. The seminar series draws on
the collective knowledge and experience of U-M faculty, staff and students.
                                                               Assanis, 17

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       Courses Taught at University of Michigan
Date
Winter
95
Fall 95
Winter
96
Winter
96
Fall 96
Fall 96
Winter
97
Winter
97
Fall 97
Fall 97
Winter
98
Winter
98
Fall 98
Fall 98
Winter
99
Fall 99
Fall 99
Winter
00
Winter
00
Fall 00
Fall 01
Fall 01
Fall 02
Fall 03
Fall 04
Fall 05
Fall 06
Winter
08
Fall 08
Wint09
Course
ME 534

ME 438
ME 534

ME 592

ME 438
ME 591
ME 534

ME 592

ME 438
ME 591
ME 534

ME 592

ME 438
ME 591
ME 592

ME 438
ME 591
ME 534

ME 592

ME 591
ME 438
ME 591
ME 438
ME 438
ME 438
ME 438
ME 438
ME 599

ME 438
ME 538
                            Course Title
                    Advanced Internal Combustion
                                Eng.
                     Internal Combustion Engines
                    Advanced Internal Combustion
                                Eng.
                     Automotive Eng. Seminar II

                     Internal Combustion Engines
                      Automotive Eng. Seminar I
                    Advanced Internal Combustion
                                Eng.
                     Automotive Eng. Seminar II

                     Internal Combustion Engines
                      Automotive Eng. Seminar I
                    Advanced Internal Combustion
                                Eng.
                     Automotive Eng. Seminar II

                     Internal Combustion Engines
                      Automotive Eng. Seminar I
                     Automotive Eng. Seminar II

                     Internal Combustion Engines
                      Automotive Eng. Seminar I
                    Advanced Internal Combustion
                                Eng.
                     Automotive Eng. Seminar II
                       (Vehicle Energy Seminar)
                      Automotive Eng. Seminar I
                     Internal Combustion Engines
                      Automotive Eng. Seminar I
                     Internal Combustion Engines
                     Internal Combustion Engines
                     Internal Combustion Engines
                     Internal Combustion Engines
                     Internal Combustion Engines
                       Analysis and Control of
                       Alternative Powertrains
                     Internal Combustion Engines
                           Advanced ICEs
Enroll
23
42
21
8
69 (43+26)"
18
18

68 (37+31)
12
32
40(15+25)
50


88 (53+35)
33 (18+15)
23
38(23+15)
33 (18+15)
66(41+25)
40(15+25)
53
72 (32+40)
54
70 (50+20)
50
26 (20+6)
40
32
Crs Eval
4.45
4.85
4.87
n/a1
4.83
n/a
4.86
n/a
4.80
n/a
4.17
n/a
4.86
n/a
n/a
4.83
n/a
4.71
n/a
n/a
4.85
n/a
4.85
4.97
4.91
4.88
4.92
4.42
4.94
4.54
Instr Eval
4.54
4.85
4.97
n/a
4.85
N/A
4.94
n/a
4.88
n/a
4.72
n/a
4.94
n/a
n/a
4.95
n/a
4.85
n/a
n/a
4.90
n/a
4.85
4.97
4.93
4.88
4.91
4.22
4.94
4.80
1  Organizer and host of Automotive Engineering Seminar Series I and II.
  Standard course evaluation forms not applicable (n/a).
2  Distribution designates student enrollment for on-campus and distance learning students.
                                                                    Assanis, 18

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Offerings of Short Courses and Workshops

I am a proponent of life-long learning and have frequently taught short
courses and workshops to practicing engineers in industry.  Examples are:

"Modeling and Computer Simulation of Internal Combustion Engines," Chair,
      Continuing   Engineering   Education,   University  of  Michigan,
      September 9-13, 1996; July 7-11, 1997; June 29-July 3, 1998; July 5-
      9,1999; July 10-14, 2000.

"Basic  Engines  and   Their  Controls,"  Chair,  Continuing  Engineering
      Education, Motorola, Deerfield, IL, two-day offerings, 1996-2005.
One-on-One Student Instruction and Mentorship

Post-Doctoral Fellows Mentored

     1.  George Papageorgakis (now with ExxonMobil)
     2.  Dohoy Jung (now Assistant Professor at UM-Dearborn)
     3.  George Delagrammatikas (now Assistant Professor at Cooper Union)
     4.  Sang-Jin Hong (now with Ford Motor)
     5.  Chris Depcik (now Assistant Professor at University of Kansas)
     6.  Timothy Jacobs (now Assistant Professor at Texas A&M)
     7.  Christos Chryssakis (now Research Scientist at NTU, Athens)
     8.  Vassilis Hamosfakidis (now with Risk Metrics)
     9.  Andreas Malikopoulos (now at ORNL)
    10.  Robert Prucka (now Assistant Professor at Clemson University)
    11.  Chaitanya Sampara (now at NanoStellar)
    12.  Andrew Ickes (now at Argonne National Laboratories)
    13.  Hee Jun Park (now at Samsung Heavy Industries, Korea)
    14.  Seung Hwan Keum (continuing in my group)
    15.  Byungchan Lee (now at UM- Dearborn)
    16.  Will Northrop (now at GM R&D)
    17.  Michael Smith (now at University of Michigan)

Ph. D. Committees Chaired at University of Michigan

     1.  XiaoboSun, 1996, Chair
     2.  George Papageorgakis, 1997, Chair
     3.  Apoorva Agarwal, 1998, Chair
     4.  Dohoy Jung, 2000, Chair
     5.  George Delagrammatikas, 2001, Co-Chair (with P. Papalambros)
     6.  Sang-Jin Hong, 2001, Co-Chair (with M. Wooldridge)
     7.  Scott Fiveland, 2001, Chair
     8.  Stani Bohac, 2002, Chair
     9.  Kukwon Cho, 2003, Co-Chair (with Z. Filipi)

                                                             Assanis, 19

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10.  Guntram Lechner, 2003, Chair
11.  Christopher Depcik, 2003, Chair
12.  Bruno Vanzieleghem, 2004, Co-Chair (with H. Im)
13.  Pin Zeng, 2004, Chair
14.  Wooheum Cho, 2004, Chair
15.  Junseok Chung, 2004, Co-Chair (with Z. Filipi)
16.  Tim Jacobs, 2005, Chair
17.  Aris Babajimopoulos, 2005, Chair
18.  Ron Grover, 2005, Chair
19.  Christos Chryssakis, 2005, Chair
20.  Bin Wu, 2005, Co-Chair (with Z. Filipi)
21.  Sangseok Yu, 2006, Co-Chair (with D. Jung)
22.  Vassilis Hamosfakidis, 2006 (Chair)
23.  Kyoung Joon Chang, 2007, Chair
24.  Alex Knafl, 2007, Chair
25.  Manbae Han, 2007, Co-Chair (with S. Bohac)
26.  Melody Papke, 2007, Co-Chair with Jun Ni
27.  Andreas Malikopoulos, 2007, Co-Chair (with P. Papalambros)
28.  Jonathan Hagena, 2007, Co-Chair (with Z. Filipi)
29.  Robert Prucka, 2007, Co-Chair (with Z. Filipi)
30.  Orgun Guralp, 2008, Co-Chair (with Z.  Filipi)
31.  Chaitanya Sampara, 2008, Co-Chair (with E. Bissett, GM)
32.  Yanbin Mo, 2008, Chair
33.  Shawn Grannell, 2008, Co-Chair (with S. Bohac)
34.  Andrew Ickes, 2009, Co-Chair (with S. Bohac)
35.  Hee Jun Park, 2009, Co-Chair (with D. Jung)
36.  Seung Hwan Keum, 2009, Co-Chair (with H. Im)
37.  Byungchan Lee, 2009, Co-Chair (with D. Jung)
38.  Will Northrop, 2009, Co-Chair (with S.  Bohac)
39.  Michael Smith, 2010, Co-Chair (with S. Bohac)
40.  Jason Martz, 2010, Chair
41.  Sung Jin Park, candidate, 2011 (expected), Co-Chair (with D. Jung)
42.  Mehdi Abarham, candidate, 2011 (expected), Co-Chair (with J. Hoard)
43.  Matt Spears, candidate, 2011 (expected), Chair
44.  Jerry Fuschetto, candidate, 2011 (expected), Chair
45.  Russel Truemner, pre-candidate, 2011 (expected),  Co-Chair (with R. Beck)
46.  Stefan Klinkert, pre-candidate, 2011 (expected), Co-Chair (with S. Bohac)
47.  Sotiris Mamalis, pre-candidate, 2012 (expected), Co-Chair (with A.
    Babajimopoulos)
48.  Robert Middleton, pre-candidate, 2013 (expected), Chair
49.  Kevin Zaseck, pre-candidate, 2013 (expected), Co-Chair (with Z. Filipi)
50.  Janardhan Kodavasal, pre-candidate,  2013 (expected), Co-Chair (with A.
    Babajimopoulos)
51.  Prasad Shigne, candidate, 2013 (expected), Co-Chair (with A.
    Babajimopoulos)
52.  Ashwin Salvi, pre-candidate, 2013  (expected), Co-Chair (with Z. Filipi)
53.  Elliott Alexander Ortiz Soto, pre-candidate,  2013  (expected), Chair
54.  Vjjai Manikandan, candidate, 2013 (expected), Chair
55.  Luke Hagen, pre-candidate, 2013 (expected), Chair

                                                          Assanis, 20

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    56.  Brandon Lee, pre-candidate, 2013 (expected), Co-Chair (with A.
        Babajimopoulos)
Ph. D. Committees Chaired at University of Illinois in Urbana-Champaign

    1.  Qiong Li, 1991, Chair
    2.  Leonard Shih, 1992, Chair
    3.  Panos Tamamidis, 1992, Chair
    4.  Constantine Varnavas,  1994, Chair
    5.  Douglas Baker, 1995, Chair
    6.  Michalis Syrimis, 1996, Chair

M. S. Committees Chaired at University of Michigan

   1.  James Wallace, 1997, Chair
   2.  Michael Mshar, 1998, Chair
   3.  Scott Fiveland, 1999, Chair
   4.  George Seaward, 2000, Chair
   5.  Chris Depcik, 2000, Chair
   6.  Salih Mahameed, 2001, Chair
   7.  Ron Grover, 2001, Chair
   8.  Selim Buyuktur, 2001,  Co-Chair (with M. Wooldridge)
   9.  Cheol Su Lee, 2001, Chair
   10.  Brian Baldwin, 2001, Chair
   11.  Tim Jacobs, 2002, Chair
   12.  John Matsushima, 2002, Co-Chair (with Z. Filipi)
   13.  Aris Babajimopoulos, 2002, Chair
   14.  Christos Chryssakis, 2002, Chair
   15.  Berrin Daran, 2002, Co-Chair (with Z. Filipi)
   16.  Scott Thompson, 2003, Chair
   17.  Chad Jagmin, 2003, Co-Chair (with Z. Filipi)
   18.  Andrew Ickes, 2003, Chair
   19.  Matthew Leustek, 2003, Chair
   20.  Wesley Williamson, 2004, Co-Chair (with Z. Filipi)
   21.  Robert Prucka, 2004, Chair
   22.  Jonathan Hagena, 2004, Chair
   23.  Chaitanya Sampara, 2004, Chair
   24.  Orgun Guralp, 2004, Co-Chair (with Z. Filipi)
   25.  Gerald Fernandes, 2006, Co-Chair (with Z. Filipi)
   26.  Chandra Sandrasekaran, 2006, Co-Chair (with S. Bohac)
   27.  Steve Busch, 2007, Co-Chair (with S. Bohac)
   28.  Vjjayaraghavan Shriram, 2007, Co-Chair (with Z. Filipi)
   29.  Alberto Lopez, 2008, Co-Chair (with S. Bohac)
   30.  Challa Prasad, 2008, Co-Chair (with A. Babajimopoulos)
   31.  Mark Hoffman, 2008, Co-Chair (with Z. Filipi)
   32.  Michael Smith, 2009, Chair
   33.  Anastasios Amoratis, 2009, Co-Chair (with A. Babajimopoulos)
   34.  SotirisMamalis, 2009,  Chair

                                                             Assanis, 21

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   35. Ashwin Salvi, 2009, Co-Chair (with Z. Filipi)
   36. Robert Middleton, 2009, Chair
   37. Samuel Olesky, 2009, Chair
   38. Elliott Alexander Ortiz Soto, 2010, Chair
   39. Janardhan Kodavasal, 2010, Co-Chair (with A. Babajimopoulos)
   40. Prasad Shigne, 2010, Co-Chair (with A. Babajimopoulos)
   41. Jeremy Spater, 2010, Chair
   42. Laura Manofsky, 2011 (expected), Chair
   43. Ann Marie Lewis, 2011 (expected), Chair
   44. Luke Hagen, 2011 (expected), Chair
   45. Srinath Gopinath, 2011 (expected), Chair
   46. Kyoung Hyun Kwak,  2011  (excepted), Co-Chair (with D. Jung)
   47. Tejas Chafekar, 2011  (expected), Co-Chair (with J. Hoard)

M. S. Degrees Chaired at University of Illinois in Urbana-Champaign

   1.  Edward Badillo, 1989, Chair
   2.  Matthew Polishak, 1989, Chair
   3.  Michael Bonne, 1989, Chair
   4.  James McLeskey, 1989, Chair
   5.  Riadh Namouchi, 1990, Chair
   6.  TarunMathur,  1990, Chair
   7.  Constantine Varnavas, 1990, Chair
   8.  Francis Friedmann, 1990, Chair
   9.  Andrew Phillips, 1990, Chair
   10. Kevin Wiese, 1990, Chair
   11. Brian Bolton, 1990, Chair
   12. Panos Tamamidis, 1990, Chair
   13. Thomas Leone, 1990, Chair
   14. Timothy  Burt, 1990, Chair
   15. Douglas Baker, 1991, Chair
   16. Gregory Clampitt, 1991, Co-Chair (with White)
   17. Daniel Clark, 1991, Chair
   18. Evangelos Karvounis, 1991, Chair
   19. Matthew Lipinski, 1992, Co-Chair (with White)
   20. Michalis  Syrimis, 1992, Chair
   21. Matthew Schroder, 1993, Co-Chair (with White)
   22. Donald Nakic,  1994, Co-Chair (with  White)
   23. George Papageorgakis, 1994, Chair
   24. Scott Butzin, 1994, Chair
   25. Cristopher Bare, 1995, Chair
   26. Thomas Brunner, 1995, Chair
   27. Paul Herring, 1995, Chair
   28. Stani Bohac, 1995, Chair
   29. Timothy  Frazier, 1995, Chair
                                                             Assanis, 22

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M. Eng. Automotive Projects Directed at University of Michigan
      (ME 593/503, 4 credit hours)
   1.   Winter 1996;
   2.   Winter 1996;
   3.   Spring 1996;
   4.   Spring 1996;
   5.   Fall 1996;
   6.   Fall 1997,
   7.   Winter 1997;
   8.   Winter 1997;
   9.   Winter 1997;
   10. Spring 1997;
   11. Winter 1998;
   12. Winter 1998;
   13. Winter 1998;
   14. Winter 1998;
   15. Summer 1998;
   16. Fall 1998;
   17. Fall 1998;
   18. Fall 1998;
   19. Fall 1998;
   20. Winter 1999;
   21. Winter 1999;
   22. Winter 1999;
   23. Winter 1999;
   24. Winter 1999;
   25. Winter 1999;
   26. Summer 1999;
   27. Summer 1999;
   28. Summer 1999;
   29. Fall 1999;
   30. Fall 1999;
   31. Fall 1999;
   32. Fall 1999;
   33. Winter 2000;
   34. Winter 2000;
   35. Winter 2000;
   36. Winter 2000;
   37. Winter 2000;
   38. Winter 2000;
   39. Winter 2000;
   40. Winter 2000;
   41. Spring 2000;
   42. Summer 2000;
   43. Summer 2000;
   44. Winter 2001;
   45. Winter 2001;
   46. Summer 2002;
Fadi Kanafani
Richard Sellschop
Philip Glazatov
David Silberstein
Caleo Tsai
Marc Allain
Osvaldo Corona
Fabien Redon
Steven Siegal
Eric Mokrenski
Lee Choon Hyong
Yu-Min Lin
Faisal Mahroogi
Bruno Vanzieleghem
Yuri Rodrigues
Claude Bailey
John Emley
Ghosh Ranajay
Islam Kazi
Stephanie Lacrosse
Russell Thompson
Carlos Armesto, Greg Christensen, Eugene Cox, John Dent
John Joyce
Marcus Branner
Michael McGuire
Steven Hoffman
Alejandro Sales
David Wheatley
Todd Petersen
John Matsushima
Michelle Chaka and Mary Wroten
Julie D'Annunzio, Timothy Veenstra, and Todd Glance
Bhargav SriParakash
Douglas Iduciani and Ronald Kruger
Timothy Gernant, Allen Lehmen and Jeffrey Kaiser
Brian Young, Mark Dipko and Andrew Slankard
Stephen White
Tomoyuki Takada,  Mami Takada and Milton Wong
Cristian Arnou and Soon Low
Elaine Kelley
Joseph Fedullo, Colin Roberts and John Celmins
Frank Voorburg and Marie Mann
Ping (Pete) Yu
Jason Martz;
Kwang Yong Kang
Jonathan Jackson
                                                             Assanis, 23

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   47. Summer 2002;   David Swain and Dan Yerrace
   48. Winter 2009;    Peter Andruskiewicz
   49. Winter 2009;    Dan Murray
   50. Winter 2009;    AmitGoje
AUTO 503 Capstone Special Project

   1.   Fall 2008, Peter Andruskiewicz, 3 credit hours
   2.   Winter 2009, Amit Goje, 3 credit hours
Ph.D. at Korea Advanced Institute of Science and Technology (KAIST), Korea
       (carried-out in part at W. Lay Automotive Laboratory under my direction)
       Tong Won Lee, 2003

Diplomarbeit at Technical University of Graz, Austria
       (carried-out at W. E. Lay Automotive Laboratory under my direction)
       Guntram Lechner, 1999
       Alex Knafl, 2001

Studenarbeit at Rheinisch-Westfalische Technische Hochschule Aachen
       (carried-out at W. E. Lay Automotive Laboratory under my direction)

       Michalis Panagiotidis, 1999
       Christof Schultze, 1999
Graduate Special Projects (ME 590) Directed at University of Michigan

    1.  Winter 1995; Teresa Schulke; 3 credit hours
    2.  Winter 1995, Fadi Kanafani; 3 credit hours
    3.  Winter 1995, Karl Ondersma; 3 credit hours
    4.  Spring/Summer1995; M. Mubbashir Abbas; 2 credit hours
    5.  Winter 1996-98; Paul L. Powell III; 6 credit hours
    6.  Fall 1997; Erik Koehler; 3 credit hours
    7.  Winter 1998; Kukwon Cho; 3 credit hours
    8.  Winter 1998; Scott Fiveland; 3 credit hours
    9.  Winter 1999; Russell Thompson, 3 credit hours
    10. Winter 1999; Stephanie LaCrosse, 3 credit hours
    11. Summer 1999; Thomas Veling, 3 credit hours
    12. Fall 1999, John Matsushima, 3 credit hours
    13. Winter 2000, Carlos Armesto, 3 credit hours
    14. Winter 2000, Lee Byungchan, 3 credit hours
    15. Winter 2000 and Winter 2001, Cheol Su Lee, 6 credit hours
    16. Winter 2000, Jeff Sanko, 3 credit hours
    17. Winter 2000, Ryan Nelson, 3 credit hours
    18. Winter 2000, Selim Buyuktur,  3 credit hours
    19. Winter 2000, George Seaward, 3 credit hours

                                                              Assanis, 24

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20. Winter 2000, Ping Yu, 3 credit hours
21. Fall 2000, Marie Mann, 3 credit hours
22. Fall 2000, Matthew Schwab, 3 credit hours
23. Winter 2001, Cheol Su Lee, 3 credit hours
24. Winter 2002, Josh Richards, 3 credit hours
25. Winter 2002 and Fall 2002, Brett Thompson, 6 credit hours
26. Fall 2002, Mengkai Zhang, 3 credit hours
27. Fall 2003, Krishna  Kumar, 3 credit hours
28. Fall 2003 and Winter 2004, Andreas Malikopoulos, 6 credit hours
29. Fall 2003 and Winter 2004, Christopher Morgan, 6 credit hours
30. Winter 2004, Mark Hoffman, 3 credit hours
31. Winter 2004, Weibin Zhu, 3 credit hours
32. Fall 2004, Seung Hwan Keum, 3 credit hours
33. Fall 2004, John Zeilstra, 3 credit hours
34. Fall 2004 and Winter 2005, Kwangsoon Choi, 6 credit hours
35. Fall 2004 and Winter 2005, Qi Wang, 6 credit hours
36. Fall 2004 and Winter 2005, Qingan Zhang, 6 credit hours
37. Fall 2005, Jarrod Robertson, 3 credit hours
38. Fall 2005, Gudiseva Satya Varun, 3 credit hours
39. Winter 2005, Stephen Busch, 3 credit hours
40. Winter 2005, Abigail Mechtenberg, 3 credit hours
41. Winter 2005, Richard Niedzwiecki, 3 credit hours
42. Winter 2005, Choi  Kwangsoon, 3 credit hours
43. Winter 2006, Nikolas Anderson, 3 credit hours
44. Winter 2007, David Ault; 3 credit hours
45. Winter 2007, Michael Christiansen, 3 credit hours
46. Winter 2007, Matthew Freddo, 3 credit hours (with S. Bohac)
47. Winter 2007, Dong Han, 3 credit hours
48. Winter 2007, Stefan Klinkert, 3 credit hours (with S. Bohac)
49. Winter 2007, Mahesh Kumar Madurai.  3 credit hours
50. Winter 2007, Robert  Middleton, 3 credit hours
51. Winter 2007, Challa Prasad, 3 credit hours (with A. Babajimopoulos)
52. Winter 2007, Ashutosh Sajwan, 3 credit hours (with S. Bohac)
53. Winter 2007, Jaskirat Singh, 3 credit hours (with D. Jung)
54. Winter 2007, Ashwin Salvi, 3 credit hours (with Z. Filipi)
55. Winter 2007, Vishnu Nair, 3 credit hours
56. Fall 2007; Vivek Srinivasan Narayanan; 3 credit hours
57. Winter 2008, Ramamurthy Vaidyanathan; 3 credit hours
58. Spring 2008, Alphonso  King, 6 credit hours
59. Fall 2008, Amit Goje, 3 credit hours (with J. Hoard)
60. Fall 2008, Doohyun Kim, 3 credit hours
61. Fall 2008, Kyoung-Hyun Kwak, 3 credit hours
62. Fall 2008, Saktish Sathasivam, 3 credit hours
63. Fall 2008, Prasad Shingne, 3 credit hours
64. Winter 2009, Sourabh Goel, 3 credit hours
65. Winter 2009, Chang-Ping Lee, 3 credit  hours
66. Winter 2009, Kevin Zaseck, 3 credit hours
67. Winter 2009, Elliott Ortiz-Sotto, 3 credit hours
68. Fall 2009, Vishnu Vitala, 3 credit hours

                                                           Assanis, 25

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    69. Winter 2010, Tejas Chafekar, 3 credit hours (with J. Hoard)
    70. Fall 2010, Saradhi Rengarajan, 3 credit hours (with J. Hoard)
Undergraduate Special Projects (ME 490) Directed at University of Michigan

   1.   Winter 1995, Maurice Moulton; 3 credit hours
   2.   Winter 1995; George Papageorgakis; 3 credit hours
   3.   Winter 1996; David Messih; 3 credit hours
   4.   Winter 1996; Eric Morenski; 3 credit hours
   5.   Winter 1996; Benedict J. Baladad; 3 credit hours
   6.   Winter 1996; Kevin Ferraro; 3 credit hours
   7.   Spring 1997, Andreas Athanassopoulos, 3 credit hours
   8.   Fall 1998, Ryan Nelson, 3 credit hours
   9.   Winter 1999; Nicholas Bellovary and Daniel Kulick, 3 credit hours
   10.  Winter 1999; Daniel Herrera and Joel Hartter, 3 credit hours
   11.  Winter 1999; Larry Mercier and Reza Sharifi, 3 credit hours
   12.  Winter 2000; Nicolas Wetzler, 3 credit hours
   13.  Winter 2001; Andrew Ickes, 3 credit hours
   14.  Winter 2002; Keith DeMaggio, 3 credit hours
   15.  Fall 2003; Marvin (Bob) Riley
   16.  Fall 2004; Katherine Chia-Chun Ho, 3 credit hours
   17.  Fall 2004, Liang Xue, 3 credit hours
   18.  Winter 2005, Levi Roodvoets, 3 credit hours
   19.  Fall 2005; Erin Robbins, 3 credit hours
   20.  Winter 2006; David Ault, 3 credit hours
   21.  Winter 2006; Tommaso Gomez, 3 credit hours
   22.  Winter 2007; Daniel Murray, 3 credit hours
   23.  Spring 2007, Dimitri  Karatsinides, 2 credit hours
   24.  Winter 2009; Anthony Mansoor, 3 credit hours
   25.  Winter 2009, Lucas Vanderpool, 3 credit hours
ME 450 Senior Design Project

   1.  Winter 2006, Dan Murray, Chris Marchese, Dave Ault, Randy Jones,
      "Design of a Hydraulic Dynamometer," 3 credit hours
   2.  Winter 2007, Qioghui Fung, Chun Yang Ong, Chee Chian Seah, Joann
      Tung, "Heated Catalyst Test-Rig for Single Cylinder Engine"
Undergraduate Research Opportunity Program (UROP)

   1.   Fall 2006, Christine Siew, "Determination of Operational Limits and
       Stability Analysis of HCCI Engine Using 1-D Simulation"
   2.   Fall 2006, Nathan Shoemaker, "Challenge X- Crossover to Sustainable
       Mobility"

                                                              Assanis, 26

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CONTIBUTIONS TO RESEARCH

       Major Research Accomplishments

       Dr. Assanis' research interests lie in the thermal sciences and their
       applications to energy conversion, power and propulsion, and automotive
       systems design.  His research focuses on analytical and experimental studies
       of the thermal, fluid and chemical phenomena that occur in internal
       combustion engines, after-treatment systems, and fuel processors.  His efforts
       to gain new understanding of the basic energy conversion processes have
       made significant impact in the development of energy and power systems with
       significantly improved fuel economy and dramatically reduced emissions.  His
       group's research accomplishments have been published in over 250 articles in
      journals and international conference proceedings. More specifically:

   •   Over the past 25 years, he has made major contributions in modeling and computer
       simulation of internal combustion engine processes and systems, under steady-state
       and transient operation, and in carrying-out sophisticated in-situ experimental
       techniques, applicable to operating engine combustion chambers, to validate their
       fidelity.  His innovative work has shed light into complex fuel-air mixing,
       combustion, pollutant formation and transient heat transfer phenomena in metal and
       ceramic-insulated engine combustion chambers.  His simulation models and
       experimental insights are used by engine researchers and developers (e.g., General
       Motors, Caterpillar, Argonne, Lawrence Livermore and Sandia National
       Laboratories) to improve vehicle fuel economy while at the same time satisfying
       ultra-stringent emissions standards.

   •   His group has pioneered the integration of high fidelity engine models with driveline
       and vehicle models and used these comprehensive tools for realistic assessment and
       design optimization of conventional and hybrid powertrain systems.  His engine-in-
       vehicle simulation methodologies have contributed significantly to the dual need-dual
       use heavy-duty industry/U.S.  Army ground mobility mission through the
       development and optimization of advanced propulsion systems with 2-3 times higher
       fuel efficiency and ultra low smoke and particulate emissions.

   •   He has made lasting contributions to the fundamental understanding of the chemical
       and physical processes that govern the operation of Homogeneous Charge
       Compression Ignition (HCCI) engines and their exhaust aftertreatment systems. His
       revolutionary insights make possible to operate engines in ultra clean, low
       temperature combustion, fuel economical regimes that constitute a paradigm shift
       from  the traditional, high temperature, pollutant forming engine combustion.  His
       HCCI combustion strategies and patents have assisted industry to improve fuel
       economy of clean gasoline and diesel cars by 15%-20%, while virtually eliminating
       NOx  and particulate emissions.

   •   Over the past 15 years, Dr. Assanis has led the efforts to revitalize the University of
       Michigan's automotive engineering activities and transformed the Walter E. Lay
       Automotive Laboratory into a beehive of research activity (see the URL link:

                                                                      Assanis, 27

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 http://me.engin.umich.edu/autolab/). He has initiated large-scale projects involving
 partnerships among academia, government and industry, led the fundraising efforts
 through writing major proposals, and directed the research activities. He has
 collaborated extensively with faculty members, research scientists and post-doctoral
 scholars from various Universities and disciplines.  He has directed the research of
 more than 50 Ph.D. and more than 100 MS and M.Eng. graduate students.  His
 group's research accomplishments have been published in over 250 articles in
journals and international conference proceedings.  His group's engine and
 powertrain system simulations are used in industry, academia and government.

 Grants and Contracts

 Dr. Assanis has been the project director, principal or co-principal investigator for
 more than $100M in grants and contracts funded by automotive industry (General
 Motors, Ford Motor Co., Chrysler LLC and DaimlerChrysler Corporation,
 Mitsubishi Motors Co., Honda Motor Co., Borg Warner, Ricardo), the heavy-duty
 truck industry (Detroit Diesel Corporation, Caterpillar, Inc., International,
 Cummins, Caterpillar, Yanmar Diesel Engine Co, Komatsu), the oil industry
 (ExxonMobil Corporation, Lubrizol, Amoco Oil, Chevron, Ethyl Corporation),
 the U.S. government (Department of Defense, Department of Energy, NASA,
 EPA, National Science Foundation) and National Laboratories (Sandia, Argonne).
 Major collaborative research partnerships he has led or co-led include:

    •  Department of Energy, Office of Policy and International Affairs, "U.S.-
       China Clean Energy Research Center - Clean Vehicle Consortium CERC-
       CVC," Sept. 2010-Sept. 2015. The strategic intent of the CERC-CVC is to
       forge a strong partnership between the U.S. and China, the largest
       greenhouse gas emitters and the largest existing and emerging vehicle
       markets, for breakthrough research and development. The CERC-CVC is
       led by the University of Michigan in partnership with Ohio State University,
       M.I.T., national labs (Sandia National Laboratories, Oak Ridge National
       Laboratory, Argonne National Laboratory, Joint BioEnergy Institute,
       Fraunhofer Institutes, Germany), and industry (Ford  Motor Company,
       General Motors, Cummins Engine Co., Toyota Motor Co., Chrysler,
       Cummins, MAGNET, A123, American Electric Power, First Energy and the
       Transportation Research Center). The total value of the U.S. effort is nearly
       $30M, of which the US DOE will contribute $12.5M over a five-year
       period, and industry and academia will contribute $17M. The Chinese
       government will match the US effort with a $25M of funding to a
       consortium of Chinese academic partners, led by Tsinghua University, and
       industry.

    •  General Motors-University of Michigan  Engine Systems Research
       Collaborative Research Laboratory (GM/UM ESR CRL).  This successful
       research partnership between the two institutions, initiated in 1998 and
       currently in its third, five-year phase ($15M in total funding, 1998-2013)
       uses the special expertise  of UM to conduct fundamental research into core
       competitive areas for GM in order to significantly improve fuel economy

                                                                Assanis, 28

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       and dramatically reduce emissions of next generation engines. The CRL has
       also motivated the growth and strengthening of additional areas of
       excellence of importance to GM and commensurate with the scholarly
       expertise and intellectual pursuits of the University faculty. As of December
       2010, Professor Assanis has stepped down as GM-UM ESR CRL Founding
       Co-Director to become the Founding Director for the United States Clean
       Vehicle Consortium, U.S.-China Clean Energy Research Center, 2010-2015.

       UM-led Multi-University Consortium on Homogeneous Charge
       Compression Ignition (HCCI)/ Low temperature Combustion (LTC)
       Engine Research, funded since 2001 by the Department of Energy
       (approx. $10M of funding to 12/31/09}.  This innovative research
       holds the promise of delivering high fuel economy with dramatically
       reduced emissions through a paradigm-shift approach compared to the
       traditional, high temperature,  pollutant forming engine combustion in
       today's engines. University of Michigan partners include Stanford, MIT,
       and UC Berkeley.  In 2011, our consortium has won a third-phase DOE
       award  (3 years, $3.75M) to explore high-pressure, lean burn (HPLB)
       combustion, with the potential to improve engine efficiency by 20-40%.

       Automotive Research Center, (ARC), a UM-led, eight-university, U.S.
       Army Center of Excellence founded in 1994 to advance the state-of-the-art
       modeling and simulation of military and civilian ground vehicles.  The
       current third phase ($40M in funding, July 2004 - July 2010) emphasizes
       research into the design of vehicles propelled by next-generation
       powertrain systems for a variety of energy supply sources.  The ARC is
       the most advanced university-based automotive research center in the
       country and has provided both educational opportunities and a unique
       cooperative partnership among the military, academia and the automotive
       industry.  Current University partners include Clemson University,
       Oakland  University, University of Alaska-Fairbanks, University of Iowa,
       Virginia Tech University, and Wayne State University.  As of October
       2009, Professor Assanis has stepped down as ARC Director to become the
       Director of the Michigan Memorial Phoenix Energy Institute.
Other Current Grants at The University of Michigan

Department of Energy, Office for Energy Efficiency and Renewable Energy,
Robert  Bosch  LLC,  AVL  Powertrain  Engineering Inc.,  University  of
Michigan  and  Stanford  University,  "Advanced  Combustion Controls -
Enabling Systems and Solutions (ACCESS) for High Efficiency Light Duty
Vehicles, $24,000,000, Project Director:  Hakan Yilmaz (Bosch); Co-Pi  and
Lead for Combustion Modeling:   Dennis Assanis; my group's  portion of the
budget $4,000,000 ($2,000,000 from DOE, $680,360  from Bosch, $480,000
from AVL and $839,640 from UM), 4/1/2010- 6/30/2014.

Department of Energy, Office for Energy Efficiency and Renewable Energy,
"A University Consortium for Efficient and Clean High Pressure Lean Burn

                                                              Assanis, 29

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Engines," The  University of  Michigan in partnership with  Massachusetts
Institute  of Technology and  University  of  California-Berkeley,  10/1/09-
8/31/12, $3,750,000, Principal Investigator and Consortium Director.

Collaborative Development of Clean Diesel Exhaust Aftertreatment System
Through   Modeling   and   Testing,  Michigan  Economic   Development
Corporation, 21st Century Jobs Fund, $1,650,000,  1/1/07-6/30/10,  Principal
Investigator (proposal selection process conducted by American Association
for the Advancement of Science; 61 awards from 505 submitted proposals).

General Motors R&D Center, "Modeling and Experimental Study of Boosted
HCCI Engine," 7/1/07-6/30/2011, $1,400,000, Principal Investigator.

Ford  Motor Company,  "EGR Cooler  Fouling  Research,"  4/1/10-12/31/11,
$281,000, Principal Investigator.

U.S. Environmental Protection Agency, "Center for Engineering Excellence
through  Hybrid  Technology,"  11/1/09-10/31/12,  $1,560,000, Co-Principal
Investigator; PI: Z. Filipi.

University of  Tennessee-Battelle, LLC.,  "Simulation  of  High Efficiency
Stoichiometric  GDI  Combustion,"   5/1/10-4/30/11,  $100,000,   Principal
Investigator.

ConocoPhillips, Inc., "Fuel Effects on HCCI Combustion Limits," 6/30/2011,
$100,000, Principal Investigator.

Michigan Public Service Commission, "Integrated Assessment of Feasibility
and Deployment of Offshore Wind Technologies in the Great Lakes," 1/1/11-
12/31/12, $800,000, Principal Investigator.
Competed/or

National Science  Foundation,  "A  Proposal  for  the Establishment of an
Engineering Research Center for Carbon Neutral Vehicles (ERC-CNV)", The
University  of  Michigan  in  partnership  with Massachusetts  Institute of
Technology,  University  of California-Berkeley,  University  of Illinois  at
Urbana-Champaign,  Michigan State  University, North  Carolina A&T State
University,  9/1/08-8/31/13,  $18,500,000,  Principal  Investigator and ERC
Director; invited among 34/143 pre-proposals to submit a full proposal, and
reached site visit round of 8 finalists.
Past Grants

Automotive  Research  Center  (ARC)  of  Excellence  in  Modeling  and
Simulation of Ground Vehicles, Department of Defense:  Phase I: 9/94-7/98,

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$9,000,000, Co-Principal Investigator and Deputy Director (1/96-7/98); Phase
II:  7/98-6/04,   $25,000,000,  Co-Principal  Investigator  (7/98-9/02)  and
Principal  Investigator  (9/02-6/04); Deputy Director  (7/98 to 9/00)  and
Director (9/00-6/04).

Experimental Investigation of  Heat Rejection Characteristics of 1-4  and V-6
Engine   Designs,  Ford  Motor  Co.,  1/95 to  6/96,  $142,000,  Principal
Investigator.

Prediction  of  Engine Heat Rejection, Ford  University  Research  Program,
1995, $50,000 (unrestricted grant), Principal Investigator.

Direct Injection of Natural Gas: In Cylinder CFD Computations, DOE/NASA,
1/95 to 12/96, $214,506, Principal Investigator

Engine  Heat Transfer and  Engine/Fuels Interaction  Technology,  Chevron
Oronite Technology Group, 5/95  to 4/99, $8,000, Principal Investigator

Engine  Friction  Studies with Boundary-Friction Reducing Additives, Mobil
Technology Group and  ExxonMobil  Research and  Engineering  Company,
1/96-8/15/00, Total Funding $919,362, ($183,540,  1/96-6/96; $135,822, 6/96-
5/97; $250,000, 1/97-12/97;  $200,000,  1/98-12/98; $100,000,  1/99-6/99;
$50,000, 1/00-8/00),  Principal  Investigator.

Experimental Investigation of Heat Rejection Characteristics of Diesel Engine
Designs, Ford Motor Co., 6/96-6/97, $20,000, Principal Investigator.

Study  of Unburned  Hydrocaron  Emissions  Mechanisms,  Ricardo, 1997,
$90,000 (gift), Principal Investigator.

Direct Injection  of Natural Gas: In Cylinder  CFD Computations, SANDIA,
3/97-2/98, $25,000, Principal Investigator.

Fuel Economy and Power Benefits of Cetane-Improved Fuels in Heavy-Duty
Diesel Engines, Ethyl, 1997, $20,000 (gift), Principal Investigator.

Investigation of  Thermal  and  Strength Characteristics  of Metal  Matrix
Composite Pistons for Heavy-Duty Diesel Engines, Focus  Hope, 1997-98,
$60,000, Principal  Investigator.

Effect of Metal Matrix Composite  Liners on Engine Friction and Wear,  Inco
Limited, 1997-99, $50,000 (gift), Principal Investigator.

Optimizing  the  Performance  and Emissions  of  a Direct-Injection Spark-
Ignition  Engine  Using Multi-Dimensional Modeling, Honda Initiative Grant
Program, 8/1/97-7/31/98, $25,000, Principal Investigator.
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General Motors/UM  Collaborative  Research  Laboratory  (formerly Satellite
Research  Laboratory),  5/98-12/31/02,  $5,000,000,  GMCRL  Co-Principal
Investigator and Director, Advanced Powertrain Systems Division.

Effect of Exhaust Valve Opening on Cold Start Hydrocarbon Emissions, Ford
Motor  Company,  6/98 to 12/01,  Total  Funding $380,000 ($230,000,  6/98-
12/99; $150,000, 1/00-12/00), Principal Investigator.

Ricardo Single Cylinder  Research Engines,  Mobil  Technology Company,
9/1/98, $230,000 (gift), Principal Investigator.

Optimizing the Performance and Emissions of Direct-Injection Compression-
Ignition Engines Using Multi-Dimensional Modeling, EPA,  9/1/98-8/31/99,
$40,000, Principal Investigator.

Diesel Spray Combustion Modeling, Yanmar Diesel Engine Company, Japan,
9/1/98, $27,000 (gift), Principal Investigator.

Using Chemical Kinetics to Simulate Engine Performance  and Emissions,
Caterpillar, Inc., 1/1/99-12/31/99, $40,000 (gift), Principal Investigator.

Mixture Preparation and Nitric Oxide  Formation in a GDI Engine Studied by
Combined Laser Diagnostics and  Numerical Modeling DOE/Sandia National
Laboratory, 4/1/1999-3/31/2002, $383,505, Co-Principal Investigator.

Development  of   Pressure  Reactive  Piston  Technology  for  Improved
Efficiency and Low NOx  Emissions in Spark-Ignition (SI) and Compression
Ignition (Cl) Engines, Ford Motor Company/DOE  PNGV Program, 10/12/99-
5/31/2003, $436,825, Principal Investigator.

In Cylinder Pressure Sensors Using Thin Film Shape Memory Alloys, Orbital
Research, 6/00-8/31/02, $120,000, Principal Investigator.

Systems  Approach for Demonstrating  Very Low Nox  Emissions  from a
Direct-Injection Compression-Ignition (CIDI) Engine  with a NOx Catalyst,
EPA, 1/01-6/30/02, $100,000, Principal Investigator.

Concurrent Design of Next Generation Powertrains, Manufacturing Processes
and Materials: A Simulation-Based Approach, US ARMY/TACOM under the
Dual Use Science and  Technology  program  DUST 2000,  4/3/01-4/2/03,
$3,000,000, Co-Principal Investigator.

Simulation-Based  Design  and Demonstration  of Next Generation Advanced
Diesel  Technology, Ford  Motor  Company/US  ARMY TACOM under  the
Dual Use Science and Technology program DUST 2001,  $2,420,000, 9/1/01
to 12/31/03, Principal  Investigator.

A University Consortium on Homogeneous Charge Compression  Ignition,
Low Temperature Combustion  for  High  Efficiency, Ultra-Low Emission

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Engines,  The  University  of  Michigan  in  partnership  with Massachusetts
Institute of Technology, Stanford University, and University of California-
Berkeley,  Department  of Energy,  Phase  I: 10/1/01-3/31/06, $4,800,000,
Principal  Investigator and Consortium Director.

General Motors/UM  Collaborative  Research Laboratory on  Engine Systems
Research,   "Advanced   Diesel  Combustion  System  Optimization  Tools
Implementation,"   6/1/04-8/31/04,   $17,160,  Principal   Investigator  and
GMCRL Co-Director.

General Motors/UM  Collaborative  Research Laboratory on  Engine Systems
Research,   "Advanced   Diesel   Combustion  System   Development  and
Measurement  of  Hydrocarbon  Species and  Unregulated  Emissions  from
Diesel  Engines Operating in Advanced Combustion Modes," 9/1/03-8/31/04,
$116,206, Principal Investigator and GMCRL Co-Director.

General Motors/UM  Collaborative  Research Laboratory on  Engine Systems
Research, "Experimental Assessment of Design Concepts  for Robust Spray-
Guided Stratified-Charge Combustion,"  8/1/04-7/31/05, $135,168, Principal
Investigator and GMCRL Co-Director.

Precision Heat Management in SI Engines, DaimlerChrysler Challenge Fund
Project, $180,000, 9/1/01 to 12/31/04.

Detailed  Exhaust  Hydrocarbon  Measurements  in  a  Multi-Cylinder Engine,
Ford Motor Company, 9/1/03 to 8/31/05, $98,000, Principal Investigator.

Engine-In-Vehicle  Modeling,  Navistar,  1/1/99-12/06, $300,000, unrestricted
grant, Co-Principal Investigator.

General Motors/UM  Collaborative  Research Laboratory on  Engine Systems
Research, "PCCI  Diesel Engine Combustion and Aftertreatment Systems,"
9/19/2006, $85,000, unrestricted grant, Principal Investigator.

Fuel Processors for  PEM Fuel  Cells,  Department  of  Energy,  10/01-9/06,
$4,545,471, Co-Principal Investigator.

Eaton  Corporation Innovation Center,  "Assessment of the NOx  Reducing
Potential  of NOx  Adsorber-NH3  SCR Exhaust  Aftertreatment Systems,"
Phase  I:  7/1/04 to 6/30/05,  $114,876;  Phase II:  7/1/05-12/31/06, $60,000,
Principal  Investigator.

General Motors/UM  Collaborative  Research Laboratory on  Engine Systems
Research, "Discovery Project: Free Piston Linear Alternator," 6/1/05-8/31/07,
$528,245, Principal Investigator.

Investigation of VVT Fuel Economy and Emissions Benefits under Cold-
Start,  Idle  and Low Load  Conditions,  DaimlerChrysler Challenge  Fund
Project, 1/1/05 to 6/30/08, $300,000, Principal Investigator.

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U.S.  Environmental  Protection  Agency,  "Integrated  Hydraulic   Hybrid
Propulsion  System  and  Advanced  Components  for  Maximizing  Fuel
Efficiency and Emissions Benefits,"  4/2006-10/2009, $226,000, Co-Principal
Investigator; PI: Z. Filipi.

Advanced Powertrain Modeling, Borg Warner, 1/06-6/10, $300,000, Principal
Investigator.

Ford Motor Company, "Development of Diesel EGR Cooler Fouling Model,"
Ford-UM Alliance, 9/1/07-12/31/09, $200,000, Principal Investigator.
Grants and Contracts at University of I Ilinois in Urbana-Champaign

Effect  of Combustion Chamber Insulation on  Turbocharged Diesel  Engine
Performance,  UlUC-Research  Board,  3/20/86 - 6/30/87,  $20,000 (grant),
Principal Investigator

Intake Valve Event Optimization for Specified Engine Operating Conditions,
General Motors  Pontiac Group, 8/21/86 to 6/30/88,  $31,000,  Co-Principal
Investigators: J. E. Peters and D.N. Assanis, Project Director: D.N. Assanis

Development of a  Modern Engine  Test  Cell for  Studies of Low-Heat-
Rejection   Engine  Performance,  UlUC-Research Board,   $6,000  (grant),
1/15/87 to 1/15/88, Principal Investigator

NSF, An Experimental and Analytical  Study  of Unsteady  Heat Transfer in
Low-Heat-Rejection  Engine  Combustion  Chambers, $69,983,  7/1/87  to
11/30/89, Principal Investigator

Development of an  Integrated  Rankine Bottoming Cycle for Diesel  Engine
Exhaust Heat Recovery, UlUC-Research Board,  $7,624 (grant), 8/21/87 to
5/21/88, Principal Investigator

Adiabatics, Inc., Development  and Use of  a Computer Simulation Code for
LHR  Vehicle  Fuel  Economy, $30,926,   9/1/87 to  7/31/88,  Co-Principal
Investigators: D. N. Assanis, R. A.  White, Project Director: D.N. Assanis

Analysis and Testing of Ceramic-Coated  Engine Components, Adiabatics,
Inc., $14,466, 9/1/87 to 12/31/88, Principal Investigator

Fluidized  Bed  Heat  Recovery from  Diesel  Engines,  U.S. Army  CERL,
$13,692, 9/15/87 - 5/31/88, Principal Investigator

Engineering Research Equipment  Grant: A Modern Single-Cylinder  Engine
Test Facility for Diesel  Engine Research,  NSF, $51,400 (equipment grant),
from 5/1/88 to 10/31/89, Principal Investigator
                                                               Assanis, 34

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Presidential Young Investigator Award: Engine Combustion and Emissions
Studies, NSF, $312,500, 6/88 to 12/93, Principal Investigator

A  Modern Single Cylinder Diesel  Research Engine, Caterpillar,  $27,000
(gift), 7/7/88,  Principal Investigator

Development of Multi-Dimensional  Heat Transfer Models for LHR Engine
Studies, National Center for Supercomputing Applications, 35 CPU  hours on
CRAY X/MP, 3/88 to 12/89, Principal Investigator

Combustion and Emissions of Low-Heat-Rejection Diesel  Engines, $129,223,
U.S. Army TACOM, 8/88 to 8/90, Principal  Investigator

The   Effect  of  Light  Weight  Reciprocating  Components  on  Engine
Combustion,  Frictional Losses, and Heat  Transfer,  Chrysler, 8/88 -  8/90,
$115,992, Principal Investigator

An Optical Table for Laser Velocimetry, $6,311 (gift), Newport Corp., from
4/89, Principal Investigator

Support  for  Women,  Minorities,  and  Disabled  Engineering   Research
Assistants, NSF, 2/89 - 2/90, $4,958, Principal Investigator

Development of  an  Improved Combustion Model   for Use in  a  Multi-
dimensional  Engine  Simulation,  National   Center  for  Supercomputing
Applications,  90 CPU hours on CRAY X/MP and CRAY 2, 12/89 - 12/90,
Principal Investigator

An Experimental and  Analytical Study of  Unsteady  Heat Transfer in LHR
Engines  -  REU  Supplement,  NSF,  2/1/90  to  7/31/90, $8,973,  Principal
Investigator

Investigation  of a Fluidized Bed Heat Exchanger,  U.S. Army CERL, 8/90 to
5/91, $16,935, Principal Investigator

Development of  a Hydrocarbon Emissions  Model  for  Multi-Dimensional
Engine  Simulation, National Center for Supercomputing Applications, 80
CPU hours on CRAY X/MP and CRAY 2, 4/90 - 4/91, Principal Investigator

Effect of  Reed Valves in the  Intake Ports  on SI  Engine Performance and
Knock,  Ford  Motor  Company, 8/21/90 to 12/93, $169,377, Co-Principal
Investigators:  D.N. Assanis, J. E. Peters, R. A. White, Director: D. N. Assanis

A  Study of Fuel-Air Distribution in the Intake  System  of a Spark-Ignited
Natural  Gas  Engine,  Cummins, 8/21/90  -  5/31/94, $140,000  (gift),  Co-
Principal Investigators: D. N. Assanis, R. A.  White
                                                              Assanis, 35

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Lignin-Augmented Bituminous  Coal  Depolymerization:  A Route  to  Clean
Fuels, Center for Research on Sulfur in Coal, $105,036, Co-Pi, 8/21/90 to
8/31/91, Co-Principal Investigators: D. N. Assanis, C. Kruse, PD: C.  Kruse

Prediction of 3-D Turbulent Flows Using a BFC Computer Code, National
Center for  Supercomputing Applications,  $24,000 and  50 CPU  hours on
CRAY 2, 9/90 - 8/92, Principal Investigator

Joint Research Program between Mitsubishi Motors Corp. and University of
Illinois, Mitsubishi Motors Corp., $340,000 6/1/91  to 5/31/93,  Co-Principal
Investigators: D. N. Assanis,  R. A.  White, H. Sehitoglu, D. Socie, Project
Director: D. N. Assanis

Octane  Requirement  Increase  and  its  Relation to Combustion  Chamber
Deposits, Amoco  Oil  Company, $130,798,  9/1/91to 12/93,  Co-Principal
Investigators: D. N. Assanis, R. A. White, Project Director: R. A. White

Integrated Production/Use of  Ultra Low Ash  Coal, Center for  Research on
Sulfur in Coal, $148,959,  Co-Pi, 8/91- 8/92, Co-Principal  Investigators: D. N.
Assanis, C.  Kruse, Project Director: C. Kruse

Development,  Optimization,  and Testing of a  3-D Computational  Fluid
Dynamics Code, National Center for Supercomputing Applications, 96 hours
on CRAY Y-MP, 11/91 to 12/92, Principal Investigator

A  Modern  Set  of  Emissions Analyzers for Internal Combustion Engine
Pollution Studies, UIUC Research Board, $42,000 (grant),  10/91, PI

Development of a Comprehensive Evaporation  Model for Use in a Multi-
Dimensional  Engine  Simulation, National  Center for Supercomputing
Applications, 85 CPU hours on CRAY X/MP and CRAY 2,  11/92 - 12/93,
Principal Investigator

Effects of Combustion Characteristics on Heat Loss under  Knocking  and Non-
Knocking Conditions, Mitsubishi Motor  Company, 6/93 - 5/95, $200,085,  Co-
Principal Investigator: D. N. Assanis

An Improved Model for Droplet Evaporation in High Pressure Diesel Sprays,
UIUC Research Board, $6,728 (grant), 6/93 to 12/93, Principal  Investigator

Design of Low Distortion Insulated Piston/Liner System, Inco Ltd., $25,000
(gift), from  8/93 - 8/95, Principal Investigator

RISC-6000 Workstations  for Computation and  Visualization  of  Reactive
Engine Flows, IBM, $39,888 (gift), from 12/93, Co-Principal Investigators: D.
N. Assanis, R. A. White
                                                               Assanis, 36

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Direct Injection of Natural Gas: In Cylinder CFD Computations, DOE/NASA,
1/94 to 12/94, $231,174, Co-Principal Investigators: D.  N. Assanis, J.  E.
Peters, R. L. Lucht, Project Director: D.N. Assanis

Direct Injection of Natural Gas: In Cylinder Laser Measurements, GRI, 1/94
to 12/96, $488,178, Co-Principal Investigators: D. N. Assanis, J. E. Peters, R.
L. Lucht, Project Director: R.L. Lucht

Prediction of Engine Heat Rejection, Ford University Research Program, from
1/94, $50,000 (grant), Principal Investigator

Evaluation of Hydrated Ethanol for Dl Compression Ignition Engines,  Illinois
Department of Energy and Natural  Resources, 1/94 to 6/96, $60,000 per year,
Co-Principal Investigators: D. N. Assanis, C. Goering.

Publications

Articles in Refereed Journals, Transactions or Archives

1.   D. N. Assanis, and J. B. Heywood, "Development and  Use  of a Computer
     Simulation of the Turbocompound Diesel System for Engine Performance and
     Component Heat Transfer Studies," selected for SAE 1986 Transactions, 95:2^
     2.451-2.476, 1987.   (Presented  as SAE Paper 860329,  SAE International
     Congress and Exposition, Detroit, Ml, Feb. 24-28, 1986; and included in The
     Adiabatic Diesel Engine: Global Developments, SAE Special Publication 650,
     95-120,1986.)

2.   Assanis, D. N., and Heywood, J. B., "Simulation Studies of the Effects of Low-
     Heat-Rejection on Turbocompound Diesel Engine Performance," International
     Journal of Vehicle Design, 8:3,  282-299, 1987. (Based  on Presentation at 3rd
     International Conference  on Turbocharging and  Turbochargers,  Institute of
     Mechanical Engineers, London, United Kingdom, May 6-8, 1986.)

3.   Assanis,  D.  N.,  and E.  Badillo,  "Transient  Heat Conduction in Low-Heat
     Rejection Engine Combustion Chambers," selected for SAE 1987 Transactions,
     96:4, 4.82-4.92, 1988.  (Presented as SAE Paper 870156, SAE International
     Congress  and  Exposition,  Detroit,  Ml,  Feb.  23-27, 1987; and  included in
     Adiabatic Engines and Systems, SAE Special Publication 700, 153-163, 1987.)

4.   Assanis,  D.  N.,  and  E.  Badillo,  "Transient Analysis  of Piston-Liner Heat
     Transfer  in  Low-Heat-Rejection  Diesel  Engines," selected  for SAE 1988
     Transactions: Journal of Engines, 97:6, 6.295-6.305, 1989. (Presented as SAE
     Paper 880189, SAE International Congress and Exposition, Detroit, Ml, Feb.
     29-March 4,  1988;  and  included in Recent Developments in the Adiabatic
     Engine, SAE Special Publication 738, 97-107, 1988.)

5.   Assanis, D. N., "Effect of Combustion Chamber Insulation on the Performance
     of a Low-Heat-Reject!on  Diesel  Engine with Exhaust Heat Recovery," Journal
     of Heat Recovery Systems & Combined Heat and Power,  9:5,  475-484, 1989.
     (Based on Paper 869486,  presented  at 21st Intersociety  Energy Conversion
     Engineering Conference, San Diego, CA,  Aug. 25-29, 1986.)
                                                                   Assanis, 37

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6.    Assanis,  D.  N., and E. Badillo, "On  Heat Transfer Measurements in Diesel
     Engines using Co-Axial Fast-Response Thermocouples," ASME Transactions:
     Journal of Engineering for Gas Turbines and Power, 111:3, 458-465, 1989.
     (Presented at ASME-ETCE Technical Conference, Houston, TX, Jan. 22-25,
     1989; and included in Basic Processes in Internal Combustion Engines,  ICE-
     6,25-32,1989.)

7.    Assanis,  D.  N., "Thin Thermal  Barrier  Coatings for Internal Combustion
     Engine  Components,"  International Journal of Materials  and  Product
     Technology,  4:3,  232-243, 1989. (Presented with  R. Kamo and W. Bryzik as
     SAE Paper 890143, SAE  International Congress and Exposition, Detroit, Ml,
     Feb. 27 - March 3, 1989 and selected for SAE 1989 Transactions:  Journal of
     Engines, 98:3,131-136,1990.)

8.    Phillips, A., and D. N. Assanis, "A PC-Based  Vehicle Powertrain  Simulation
     for Fuel Economy and Performance Studies," International Journal of Vehicle
     Design, 10:6^ 639-658, 1989. (An improved version of the simulation was
     presented  with A. Phillips  and  P. Badgley  in  SAE Paper  900619,  SAE
     International  Congress and  Exposition,  Detroit, Ml, Feb. 26-March  2, 1990;
     and selected  for SAE  1990 Transactions: Journal of Passenger Cars,  99:6,
     1991.)

9.    Assanis, D. N. and M. Polishak, "Valve Event Optimization in a Spark-Ignition
     Engine," International Journal of Vehicle Design,  10:6, 625-638,  1989.
     (Presented at ASME-ICED Technical Conference, Dearborn, Ml, Oct. 15-18,
     1989; and selected for ASME Transactions: Journal of Engineering for Gas
     Turbines and Power, 112:3, 341-347, 1990.)

10.   Assanis,  D.  N., and E.  Badillo,  "Evaluation of Alternative  Thermocouple
     Designs for  Transient  Heat Transfer Measurements in  Metal  and  Ceramic
     Engines," selected for SAE 1989 Transactions: Journal of Engines, 98:3, 1036-
     1051, 1990.  (Presented as SAE Paper 890571, SAE International Congress and
     Exposition, Detroit, Ml, Feb. 27 - March 3, 1989; and included in  Worldwide
     Progress on Adiabatic Engines, SAE Special Publication 785, 169-184, 1990.)

11.   Tamamidis,  P., and D.  N.  Assanis,  "Generation of Orthogonal Grids with
     Control of Spacing," Journal of Computational Physics, 94:2, 437-453, 1991.

12.   Sekar, R. R., W. W. Marr, D. N. Assanis, R. L.  Cole, T. J. Marciniak, and J. E.
     Schaus, "Oxygen   Enriched  Diesel Engine  Performance: A Comparison of
     Analytical  and  Experimental Results,"  ASME  Transactions: Journal  of
     Engineering for Gas Turbines and Power, 113:3, 365-369,  1991.  (Presented at
     ASME-ICED Technical Conference, Rockford, IL, Oct. 1990; and included in
     New Technology in Large Bore Engines,  ICE-13, 57-62, 1990.)

13.   Filipi, Z., and D. N. Assanis, "Quasi-Dimensional Computer Simulation of the
     Turbocharged Spark-Ignition  Engine  and its Use for Two and Four  Valve
     Engine  Matching  Studies,"  selected for SAE 1991 Transactions:  Journal of
     Engines, 100:3, 52-68,  1992.   (Presented  as SAE Paper  910075,  SAE
     International Congress and Exposition, Detroit, Ml, Feb. 25-March 1, 1991.)

14.   Assanis,  D.  N., Wiese, K., Schwarz, E.,  and W.  Bryzik, "The  Effects of
     Ceramic Coatings  on  Diesel  Engine Performance and Exhaust Emissions,"
     selected for SAE 1991 Transactions: Journal of Engines, 100:3, 657-665, 1992.

                                                                    Assanis, 38

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     (Presented as SAE Paper 910460, SAE  International Congress and Exposition,
     Detroit, Ml, Feb. 25-March 1, 1991.)

15.   Varnavas, C., and  D.  N.  Assanis,  "The Effects  of Spray,  Mixing, and
     Combustion  Model  Parameters  on KIVA-II  Predictions," selected for SAE
     1991 Transactions: Journal of Engines, 1488-1497, 100:3, 1992.  (Presented as
     SAE Paper 911785, SAE International Off-Highway and Powerplant Congress,
     Milwaukee, Wl, Sept. 9-12,1991.)

16.   Shih,  L, and  D. N. Assanis, "Implementation of a Fuel Spray Wall Interaction
     Model in KIVA-II,"  selected for SAE 1991 Transactions: Journal of Engines,
     100:3, 1498-1512, 1992. (Presented as SAE Paper 911787, SAE International
     Off-Highway and Powerplant Congress, Milwaukee, Wl, Sept. 9-12, 1991.)

17.   Yerramareddy, S., Tcheng, D. T., Lu, S. C-Y., and D.N. Assanis,  "Creating and
     Using Models for Engineering Design: A Machine Learning Approach," IEEE
     Expert, Special Track on Machine Learning, 52-59, June 1992.

18.   Assanis,  D.N.,  "The  Effect of  Thin  Ceramic Coatings on  Petrol  Engine
     Performance  and Emissions," International Journal  of Vehicle  Design, 13:4,
     378-388, 1992.   (Based on  SAE  Paper 900903, presented with T. Mathur at
     SAE  41st Annual Earthmoving  Industry Conference, Peoria,  IL, April 3-5,
     1990; and selected  for  SAE 1990 Transactions:  Journal of Materials and
     Manufacturing, 99:5, 1991.)

19.   Assanis,  D.   N., and  F. A. Friedmann,  "A  Thin-Film  Thermocouple for
     Transient Heat  Transfer  Measurements in  Ceramic-Coated  Combustion
     Chambers," International Communications in  Heat and Mass  Transfer,  20,
     459-468,1993.

20.   Karvounis, E., and D. N. Assanis, "The Effect of Inlet Flow Distribution on
     Catalytic Conversion  Efficiency", International Journal of Heat and Mass
     Transfer, 36:6, 1495-1504, 1993.

21.   Tamamidis,  P.,  and D. N. Assanis,  "Evaluation  of  Various  High  Order
     Schemes  With  and  Without  Flux  Limiters," International   Journal for
     Numerical Methods in Fluids, 16, 931-948, 1993.

22.   Tamamidis, P., and  D.  N. Assanis, "Three Dimensional Incompressible Flow
     Calculations  with  Alternative  Discretization  Schemes," Numerical Heat
     Transfer, PartB, 24, 57-76, 1993.

23.   Tamamidis, P., and  D. N. Assanis, "Prediction of Three-Dimensional  Steady
     Incompressible Flows using Body-Fitted Coordinates," ASME  Transactions:
     Journal of Fluids Engineering, 115, 457-462, 1993. (Based on paper  presented
     at  ASME-WAM   Symposium   on   Multidisciplinary   Applications   of
     Computational Fluid Mechanics, Atlanta, GA, Dec. 1-6, 1991.)

24.   Assanis,  D. N., Karvounis, E., Sekar, R., and W. Marr, "Heat Release Analysis
     of Oxygen-Enriched Diesel Combustion," ASME Transactions: Journal  of
     Engineering for Gas Turbines and Power, 115, 761-768, 1993.  (Presented as
     ASME Paper 93-ICE-8, ASME-ETCE Technical  Conference, Houston, TX,
     Jan. 31-Feb. 3, 1993.)
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25.   Karvounis, E. and D. N. Assanis, "A Novel  Methodology for  Engine Design
     and Optimization," International Journal of Vehicle  Design,  14:3,  261-277,
     1993.

26.   Karvounis, E. and D. N. Assanis, "FIND: A Framework for Intelligent Design,"
     SAE  1993  Transactions:  Journal  of Engines,  102:3,  1605-1620,  1994.
     (Presented  as SAE  Paper 931180, SAE Earthmoving  Conference, Peoria, IL,
     April  20-21, 1993.)

27.   Baker, D.,  and  D.  N. Assanis, "Multi-Dimensional Finite Element Code for
     Transient Heat Transfer Calculations," Numerical Heat Transfer, Part B, 25:4,
     395-414,1994.

28.   Baker, D.,  and D. N. Assanis, "A Methodology for Coupled Thermodynamic
     and  Heat  Transfer  Analysis  of a  Diesel  Engine,"  Applied Mathematical
     Modeling, 18, 590-601,1994.

29.   Tamamidis, P.,  and D.  N.  Assanis,  "Optimization of Inlet Port Design in  a
     Uniflow-Scavenged  Engine Using a 3-D Turbulent Flow Code," SAE 1993
     Transactions: Journal of Engines, 102:3, 1621-1633, 1994. (Presented as SAE
     Paper 931181, SAE Earthmoving Conference, Peoria, IL, April 20-21, 1993.)

30.   Shih,  L., and D.  N. Assanis, "Effect of Ring  Dynamics and Crevice Flows on
     Unburned  Hydrocarbon   Emissions,"  ASME  Transactions:  Journal   of
     Engineering for Gas Turbines and Power, 116:4, 784-792, 1994. (Presented at
     ASME-ICED Fall Technical Conference, Morgantown, WV, September 26-29,
     1993; and  included  in Alternate Fuels, Engine Performance and Emissions,
     ICE-20,195-206, 1993.)

31.   Mavinahally, N.,  Assanis,  D.  N.,  Govinda  Mallan,  K.R.,  and K.  V.
     Gopalakrishnan,  "Torch Ignition:  Ideal for  Lean   Burn Premixed-Charge
     Engines," ASME Transactions: Journal of Engineering for Gas Turbines and
     Power, 116:4, 793-798, 1994.  (Presented as ASME  Paper 94-ICE-6, ASME
     ETCE Conference,  New Orleans, LA, January 23-26, 1994.)

32.   Nakic, D., Assanis, D.  N.,  and R.  A.  White, "Effect of Elevated Piston
     Temperature  on  Combustion  Chamber   Deposit  Growth,"  SAE  1994
     Transactions, 103:3, 1454-1466, 1995.  (Presented as SAE Paper 940948, SAE
     International Congress and  Exposition, Detroit, Ml, March 1-5, 1994.)

33.   Papageorgakis,  G., and  Assanis, D.N., "A  Spray  Breakup Model  for Low
     Injection  Pressures," International   Communications  in  Heat  and  Mass
     Transfer , 23 (1), 1-10, 1996. (Based on ATA  Paper 94A1097, New Design
     Frontiers for More Efficient, Reliable, and Ecological Vehicles, Vol. 2,  pp.
     793-  802,  presented  at  4th  International  Conference  Florence ATA  1994,
     March 16-18, 1994.)

34.   Tamamidis, P., Zhang, G.,  and D. N. Assanis, "Comparison of Pressure-Based
     and Artificial Compressibility Methods for Solving 3-D Steady  Incompressible
     Flows," Journal of Computational Physics, 124, 1-13, 1996.

35.   Zhang, G.,  Assanis, D. N.,  and Tamamidis, P., "Segregated Prediction of 3-D
     Compressible Subsonic Fluid Flows Using Collocated  Grids," Numerical Heat
     Transfer, Part A, 29:757-775, 1996.

                                                                   Assanis, 40

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36.   Bohac, S., Baker, D., and D. N. Assanis, "A Global Model for Steady-State and
     Transient S.I. Engine Heat Transfer Studies," SAE 1996 Transactions: Journal
     of Engines.   (Presented  as  SAE  Paper  960073,  1996  SAE  International
     Congress, Detroit, Ml, February 26-29, 1996.)

37.   Syrimis,  M., Shigahara, K., and D. N. Assanis,  "Correlation between  Knock
     Intensity and Heat Transfer under Light and Heavy Knocking Conditions in a
     Spark  Ignition  Engine,"  SAE  1996  Transactions:  Journal  of Engines.
     (Presented  as SAE Paper 960495, 1996 SAE International Congress, Detroit,
     Ml, February 26-29, 1996.)

38.   Sun, X., Assanis, D. N., and G. Brereton, "Assessment of Alternative Strategies
     for Reducing Hydrocarbon and Carbon Monoxide Emissions from  Small Two-
     Stroke Engines," SAE 1996 Transactions: Journal of Engines.  (Presented as
     SAE Paper 960743, 1996  SAE International Congress, Detroit, Ml, February
     26-29, 1996.)

39.   Badillo,  E., Assanis,  D.  N.,  and  H. Servati, "One-Dimensional  Transient
     Dynamics of Fuel Evaporation and Diffusion in Induction Systems," SAE 1997
     Transactions: Journal of Engines.  (Presented as SAE Paper  970058, 1997
     SAE  International  Congress  and  Exposition,  Detroit, Ml, February  24-27,
     1997.)

40.   Alsterfalk,  M., Filipi, Z. S., and D.  N. Assanis, "The Potential of the Variable
     Stroke Spark-Ignition  Engine," SAE 1997  Transactions: Journal of Engines.
     (Presented  as  SAE Paper 970067, 1997  SAE  International  Congress and
     Exposition, Detroit, Ml, February 24-27, 1997.)

41.   Syrimis,  M., and D. N. Assanis, "Piston Heat Transfer Measurements  Under
     Varying Knock Intensity in A Spark-Ignition Engine," SAE 1997 Transactions:
     Journal of Engines.  (Presented as SAE Paper 971667,  1997 SAE International
     Fuels and Lubricants Meeting, Dearborn, Ml, May 5-8, 1997).

42.   Murrell,  J. D.,  Lewis, G.  M.,  Baker,  D. M., and D. N. Assanis, "An  Early-
     Design Methodology for Predicting Transient Fuel Economy and Catalyst-Out
     Exhaust Emissions," SAE 1997 Transactions: Journal of Engines.  (Presented
     as SAE  Paper 971838,  Vehicle  Thermal Management  Systems VTMS-3
     International Conference, Indianapolis, IN, May 19-22, 1997.)

43.   Green, G. J., Henly, T. J., Starr,  M.  E., Assanis, D. N., Syrimis,  M.,  and F.
     Kanafani, "Fuel  Economy and Power Benefits of Cetane-Improved Fuels in
     Heavy-Duty Diesel  Engines," SAE 1997 Transactions: Journal of Fuels and
     Lubricants. (Presented as SAE Paper 972900, SP-1302, SAE International Fall
     Fuels and Lubricants Meeting, Tulsa, Oklahoma, October 13-16,  1997.)

44.   Syrimis,  M., and  D.  N.  Assanis,  "The  Effect of the Location of  Knock
     Initiation  on  Heat Flux  into  an SI  Combustion  Chamber,"  SAE  1997
     Transactions: Journal of Engines.  (Presented as SAE Paper 972935, SP-1300,
     SAE  International   Fall Fuels and  Lubricants  Meeting,  Tulsa,  Oklahoma,
     October 13-16, 1997.)
                                                                    Assanis, 41

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45.  Zhang,  G.,  Filipi, Z. S.,  and D. N.  Assanis, "A Flexible,  Reconfigurable,
     Transient Multi-Cylinder  Diesel  Engine  Simulation  for  System  Dynamic
     Studies," Mechanics of Structures and Machines, 25(3), 357-378, 1997.

46.  Agarwal, A., Filipi, Z. Assanis, D. N., and D. Baker, "Assessment of Single-
     and  Two-ZoneTurbulence Formulations  for Quasi-Dimensional  Modeling of
     Spark  Ignition Engine Combustion,"  Combustion Science and Technology,
     136: 13-39,1998.

47.  Anderson,  M., Assanis,  D.N., and  Filipi, Z.  S., "First  and Second Law
     Analyses of a Naturally-Aspirated, Miller Cycle, SI Engine with Late Intake
     Valve Closure," SAE 1998 Transactions: Journal of Engines.  (Presented as
     SAE Paper 980889, SAE International Congress and Exposition, Detroit, Ml,
     Feb. 23-26, 1998.)

48.  Papageorgakis, G., and Assanis, D.N., "Optimizing Gaseous Fuel-Air Mixing
     in Direct Injection Engines  Using  an RNG-Based k-e Model," SAE 1998
     Transactions:  Journal of Engines.  (Presented as SAE Paper 980135, SAE
     International Congress and Exposition,  Detroit, Ml, Feb. 23-26, 1998.)

49.  Papageorgakis, G., and Assanis, D.N.,  "Comparison of Linear and Non-Linear
     RNG-Based k-e models for Incompressible Turbulent Flows," Numerical Heat
     Transfer, PartB, 35:  1-22, 1999.

50.  Assanis, D. N., Delagrammatikas, G., Fellini, R., Filipi, Z. S.,  Liedtke, J.,
     Michelena, N., Papalambros, P., Reyes, D., Rosenbaum, D., Sales, A., Sasena,
     M., "Optimization Approach  to Hybrid  Electric Propulsion System  Design,"
     Mechanics of Structures and Machines, 27(4), 393-421, 1999.

51.  Assanis, D. N., Bryzik, W.,  Castanier,  M. P.,  Darnell, I. M., Filipi, Z.  S.,
     Hulbert, G.  M., Jung, D.,  Ma, Z., Perkins, N. C., Pierre, C., Scholar, C. M.,
     Wang, Y., Zhang, G., "Modeling and Simulation of an  M1 Abrams Tank with
     Advanced Track Dynamics and Integrated Virtual  Diesel Engine," Mechanics
     of Structures and Machines, 27(4), 453-505, 1999.

52.  Assanis, D. N., Bryzik, W., Chalhoub,  N., Filipi, Z., Henein, N., Jung, D., Liu,
     X., Louca, L., Moskwa, J., Munns, S.,  Overholt, J., Papalambros,  P., Riley, S.,
     Rubin, Z., Sendur, P., Stein, J., and  G. Zhang, "Integration  and Use of Diesel
     Engine,  Driveline and Vehicle  Dynamics Models for Heavy  Duty Truck
     Simulation,"   selected for  1999  SAE  Transactions: Journal  of  Engines.
     (Presented as SAE  Paper  1999-01-0970, SAE  International Congress and
     Exposition, Detroit, Ml, March 1-4, 1999.)

53.  Lee, K. S., Assanis,  D. N., Lee,  J. H., and  K. M. Chun, "Measurements and
     Predictions  of Steady-State and Transient Stress  Distributions  in  a  Diesel
     Engine  Cylinder  Head," selected  for 1999  SAE  Transactions: Journal of
     Engines.  (Presented  as SAE Paper 1999-01-0973, SAE International Congress
     and Exposition, Detroit, Ml, March 1-4, 1999.)

54.  Assanis, D.  N.,  Hong, S.  J., Nishimura, A.,  Papageorgakis,  G.,  and  B.
     VanZieleghem, "Studies  of Spray Breakup  and Mixture Stratification in a
     Gasoline  Direct  Injection  Engine Using  KIVA-3V," ASME Transactions:
     Journal of Gas Turbines  and Power, 122:3, 485-492, 2000.  (Presented at
     ASME-ICE Spring Technical Conference, Columbus, IN, April 24-28, 1999.)

                                                                     Assanis, 42

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55.    Filipi,  Z. S.,  and D.  N. Assanis, "The Effect of the Stroke-to-Bore Ratio on
      Combustion,  Heat Transfer and  Performance  of  a  Homogeneous Charge SI
      Engine of  Given Displacement," International Journal of Engine Research,
      1:2,191-208,2000.

56.    Assanis, D.N.,  Filipi, Z. S., Gravante, S., Grohnke, D., Gui, X., Louca, L,
      Rideout, G.,  Stein, J.,  and Wang., Y., "Validation and Use of SIMULINK
      Integrated,  High  Fidelity, Engine-ln-Vehicle Simulation of the  International
      Class VI Truck," selected for 2000 SAE Transactions: Journal of Engines.
      (Presented  as SAE  Paper  2000-01-0288, included in Vehicle  and Engine
      Systems Models, SP-1527, SAE 2000 World Congress, Detroit, Ml, March 6-9,
      2000.)

57.    Fiveland,  S.B.,  and  D. N. Assanis,  "A  Four-Stroke  Homogeneous Charge
      Compression Ignition  Engine  Simulation for Combustion and  Performance
      Studies," selected for 2000 SAE Transactions: Journal of Engines. (Presented
      as SAE Paper 2000-01-0332, included in Compression Ignition Combustion
      Processes,  SP-1530,  SAE  2000 World  Congress,  Detroit, Ml, March 6-9,
      2000.)

58.    Panagiotidis,  M., Delagrammatikas, G., and D. N. Assanis, "Development and
      Use of a Regenerative  Braking Model for a Parallel  Hybrid Electric Vehicle,"
      selected for 2000 SAE  Transactions: Journal of Engines.  (Presented as SAE
      Paper  2000-01-0995, SAE  2000 World Congress,  Detroit, Ml, March 6-9,
      2000.)

59.    Assanis, D.N., Filipi, Z.S., Fiveland, S.B., and Syrimis, M., "A Methodology
      for Cycle-by-Cycle Transient Heat Release Analysis in a Turbocharged Direct
      Injection Diesel  Engine," selected for 2000 SAE  Transactions: Journal  of
      Engines.    (Presented  as  SAE  Paper  2000-01-1185,   and   included  in
      Compression Ignition  Combustion Processes, SP-1530,  SAE  2000  World
      Congress, Detroit, Ml, March 6-9, 2000.

60.    Noorman, M.T., Assanis, D. N.,  Patterson, D., Tung,  S. C., and  Tseregounis,
      S., "Overview of Techniques  for Measuring Friction  Using Bench Tests and
      Fired Engines,"  selected for 2000  SAE Transactions: Journal  of Fuels and
      Lubricants.  (Presented  as SAE Paper 2000-01-1780, and included in Advances
      in  Powertrain  Tribology,  SP-1548,  SAE  2000  Fuels  and  Lubricants
      International Conference, Paris, France, June 19-22, 2000.)

61.    Agarwal, A.  and Assanis, D. N., "Multi-Dimensional Modeling of Ignition,
      Combustion  and Nitric Oxide  Formation in Direct  Injection  Natural Gas
      Engines,"  selected  for  2000  SAE  Transactions:  Journal of Fuels and
      Lubricants.  (Presented as SAE Paper 2000-01-1839 and included in Novel SI
      and CI  Combustion Systems,  SP-1549,  SAE 2000  Fuels and Lubricants
      International Conference, Paris, France, June 19-22, 2000.)

62.    Lee, K.S.,  and  D. N.  Assanis,  "Thermo-Mechanical  Analysis  of Optically
      Accessible Quartz Cylinder Under Fired Engine  Operation,"  International
      Journal of Automotive Technology, Vol. 1, No. 2, 79  -87, 2000.

63.    Assanis, D. N., Poola, R., Sekar,  R., and  G. R. Cataldi, "Study of  Using
      Oxygen-Enriched Combustion Air for Locomotive  Diesel  Engines,"  ASME

                                                                    Assanis, 43

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     Transactions:  Journal  of Gas Turbines and Power,  123:1,  157-166,  2001.
     (Presented  in Diamond Anniversary Conference of the ASME-ICE Division,
     Fairborn, OH, October 20-23, 1996.)

64.   Filipi,  Z. S., and D. N. Assanis, "A Non-Linear,  Transient,  Single-Cylinder
     Diesel  Engine Simulation for Predictions of Instantaneous Engine Speed and
     Torque," ASME Transactions: Journal of Gas Turbines and Power, 123:4,
     951-959,2001.

65.   Agarwal, A., and D. N. Assanis, "Multi-Dimensional Modeling of Natural Gas
     Autoignition using  Detailed  Chemical Kinetics,"  Combustion Science and
     Technology, 163: 177-210, 2001.

66.   Fiveland,  S. B. and D.  N. Assanis,  "Development  of  a  Two-Zone  HCCI
     Combustion Model Accounting for Boundary Layer Effects," selected for 2001
     SAE Transactions: Journal of Engines.  (Presented as SAE  Paper 2001-01-
     1028, SAE World Congress, Detroit, Ml, March  5-8, 2001.)

67.   Delagrammatikas, G. J., and  D. N. Assanis,  "The  Reverse Engineering of a
     Turbocharged  Diesel Engine through a Unified Systems  Approach," selected
     for 2001 SAE Transactions: Journal of Engines.   (Presented as SAE  Paper
     2001-01-1244, SAE World Congress, Detroit, Ml, March 5-8, 2001.)

68.   Jung, D. and D. N. Assanis, "Multi-Zone Dl Diesel  Spray Combustion Model
     for Cycle Simulation Studies of Engine Performance and  Emissions," selected
     for 2001 SAE Transactions: Journal of Engines.   (Presented as SAE  Paper
     2001-01-1246, SAE World Congress, Detroit, Ml, March 5-8, 2001.)

69.   Michelena,  N.  Louca,  L., Kokkolaras, M., Lin, C. C., Jung, D.,  Filipi, Z.,
     Assanis, D. N., Papalambros, P., Peng, H,  Stein, J. and M. Feury,  "Design of
     an  Advanced   Heavy  Tactical  Truck: A  Target  Cascading Case  Study,"
     selected  for 2001  SAE Transactions,  Journal  of  Commercial Vehicles.
     (Presented  as  SAE  Paper 2001-01-2793,  SAE International  Truck and Bus
     Exposition, Chicago, IL, November  12-14, 2001).

70.   Kim, H.M., Kokkolaras, M., Louca, L.S., Delagrammatikas, G.J., Michelena,
     N.  F.,  Filipi, Z. S., Papalambros, P. Y., Stein, J.L.  and D.N. Assanis, "Target
     Cascading  in Vehicle Redesign: A  Class VI Truck Study," Int. J. of Vehicle
     Design, Vol.29, No.3, 2002.

71.   Hong,  S. J., M. Wooldridge and D. N. Assanis, "Modeling of Chemical and
     Mixing Effects on Autoignition  Under Direct Injection  Stratified  Charge
     Conditions," Proceedings  of 29th International Symposium on Combustion,
     Sapporo, Japan, July 21-26, 2002.

72.   Fiveland, S., Agama, R., Christensen, M., Johansson, B., Hiltner, J., Mauss, F.,
     and D. N. Assanis,  "Experimental   and  Simulated  Results Detailing  the
     Sensitivity of Natural Gas HCCI Engines to Fuel Composition," selected for
     2001 SAE  Transactions: Journal of Fuels and Lubricants, 110:4, 2123-2134.
     (Presented  as SAE Paper 2001-01-3609, 2002 SAE World Congress,  Detroit,
     Ml, March 4-7, 2002.)

73.   Olsson, J. 0, Tunestal, P., Johansson,  B., Fiveland, S., Agama, R., Willi, M.
     and D. N.  Assanis, "Compression  Ratio Influence on Maximum Load of a

                                                                    Assanis, 44

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     Natural Gas  Fueled HCCI  Engine," selected  for 2002 SAE Transactions:
     Journal Engine, 111:3, pp. 442-458. (Presented as SAE  Paper 2002-01-0111,
     Session on Homogeneous Charge Compression Ignition Engines, 2002 SAE
     World Congress, Detroit, Ml, March 4-7, 2002.)

74.   Depcik, C. and D.  N. Assanis, "A Universal Heat Transfer  Correlation  for
     Intake/Exhaust Flow in a Spark-Ignition Internal  Combustion Engine", selected
     for 2002 SAE  Transactions:  Journal  of  Engines,  111:3,  pp.  734-740.
     (Presented as SAE  Paper 2002-01-0372, Session  on  Engine Modeling, 2002
     SAE World Congress, Detroit, Ml, March 4-7, 2002.)

75.   Lee, T., Bae, C., Bohac, S.V. and D. N. Assanis, "Estimation of Air Fuel Ratio
     of an  SI Engine  from Exhaust Gas Temperature at Cold  Start Condition,"
     selected for 2002 SAE Transactions: Journal of Fuels and Lubricants,  111:4,
     pp. 592-600.  (Presented as SAE Paper 2002-01-1667, 2002 SAE Spring Fuels
     and Lubricants Meeting and Exhibition, Reno, NV, May 6-9, 2002.)

76.   Fiveland, S. B.  and  D. N. Assanis, "Development and Validation of a  Quasi-
     Dimensional  Model  for  HCCI  Engine  Performance and Emissions Studies
     under Turbocharged Conditions," selected for 2002 SAE Transactions: Journal
     of Fuels and Lubricants, 111:4, pp. 842-860.  (Presented as SAE  Paper 2002-
     01-1757, 2002  SAE Spring Fuels and Lubricants Meeting and Exhibition,
     Reno, NV, May 6-9, 2002.)

77.   Lechner, G.,  Knafl, A., Assanis, D. N.,  Tseregounis, S.I.,  McMillan, M.L.,
     Tung, S.C., Mulawa, P.A., Bardasz, E. and S. Cowling, "Engine Oil Effects on
     the Friction and  Emissions of  a  Light-Duty,  2.2L  Diesel  CIDI Engine,"
     selected for 2002 SAE Transactions: Journal of Fuels and Lubricants,  111:4,
     pp. 1165-1181.  (Presented as SAE Paper 2002-01-2681, SAE Powertrain &
     Fluid Systems Conference & Exhibition, San Diego, CA, October 21-24, 2002;
     selected for 2002 Award for Research on Automotive Lubricants.)

78.   Babajimopoulos, A. Assanis, D. N. and S. Fiveland, "Modeling the Effects of
     Gas Exchange Processes on HCCI Combustion and an Evaluation of Potential
     Control  Through   Variable  Valve  Actuation,"   selected  for  2002 SAE
     Transactions:  Journal  of Fuels and  Lubricants,  111:4,  pp.  1794-1809.
     (Presented as SAE  Paper 2002-01-2829,  SAE  Powertrain & Fluid  Systems
     Conference & Exhibition, San Diego, CA, October 21-24, 2002.)

79.   Assanis,  D.N.,  Filipi, Z.S.,  Fiveland, S.B., and Syrimis, M.,  "A Predictive
     Ignition Delay Correlation Under Steady-State  and Transient  Operation of a
     Direct-Injection Diesel Engine," ASME Transactions: Journal of Engineering
     for Gas Turbines and Power, 125:2, 450-457, 2003.

80.   Syrimis,  M.,  and  D.  N.  Assanis,  "Knocking Cylinder  Pressure  Data
     Characteristics in a  Spark-Ignition  Engine," ASME Transactions: Journal of
     Engineering for Gas Turbines and Power, 125:2^, 494-499, 2003.

81.   Zhang, G., and  D.  N. Assanis,  "Manifold  Gas Dynamic Modeling and  its
     Coupling with  Single  Cylinder  Engine  Models using SIMULINK,"  ASME
     Transactions: Journal of Engineering for  Gas Turbines and Power,  125:2_,
     563-571, 2003.
                                                                    Assanis, 45

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82.    Nelson  II, S. A., Filipi, Z.,  and  D. N. Assanis, "The Use of Neural Networks
      for Matching Compressors with  Diesel Engines," ASME Transactions: Journal
      of Engineering for Gas Turbines and Power, 125:2^ 572-579, 2003.

83.    Bohac, S., Assanis, D. N., and H. Holmes, "Speciated Hydrocarbon Emissions
      and the Associated Local Ozone Production from an Automotive Gasoline
      Engine," InternationalJournal of Engine Research, 5:1, 53-70, 2004.

84.    Delagrammatikas, G.J., and  D. N. Assanis, "Development of a Neural Network
      Model of an Advanced, Turbocharged Diesel Engine for Use in Vehicle-Level
      Optimization Studies,"/. Mech. E. Proceedings, Part D, Journal of Automobile
      Engineering, 218:5, 521-533(13), 2004.

85.    Li, Z, Kokkolaras, M. Jung, D., Papalambros, P. Y., and D. N. Assanis, "An
      Optimization Study of  Manufacturing  Variation  Effects on Diesel  Injector
      Design  with Emphasis  on  Emissions," selected for  inclusion  in  2004 SAE
      Transactions: Journal of Materials and Manufacturing (Presented  as  SAE
      Paper 2004-01-1560,  2004  SAE World Congress,  Detroit, Ml,  March 8-11,
      2004.)

86.    Filipi, Z., Wang, Y., and  D. N. Assanis "Effect of Variable Geometry Turbine
      Control (VGT) on Vehicle System Transient Response," International Journal
      of Heavy Vehicle Systems, 11:3/4, 303-326, 2004.

87.    Lin, C.C., Filipi, Z., Wang,  Y., Louca, L.,  Peng,  H., Assanis, D., and J.  Stein,
      "Integrated, Feed-Forward Hybrid Electric  Vehicle Simulation in SIMULINK
      and its Use for Power Management Studies," International Journal of Heavy
      Vehicle Systems, 11:3/4, 349-371, 2004.

88.    Filipi, Z., Louca, L., Kokkolaras, M.,  Daran, B.,  Lin, C.C., Yildir, U., Wu, B.,
      Assanis, D., Peng,  H., Papalambros, P., Stein, J., Szkubiel, D., and R. Chapp,
      "Combined  Optimization of Design and Power Management of the Hydraulic
      Hybrid Propulsion  System for the 6x6 Medium Truck," International Journal
      of Heavy Vehicle Systems, 11:3/4, 372-402, 2004.

89.    Kokkolaras, M., Louca, L.S., Delagrammatikas,  G.J., Michelena, N.F., Filipi,
      S.V., Papalambros, P.Y., Stein, J.L.  and  D.N.  Assanis, "Simulation-Based
      Optimal  Design  of   Heavy Trucks  by  Model-Based   Decomposition:  An
      Extensive Analytical  Target Cascading Case Study," International Journal of
      Heavy Vehicle Systems, 11:3/4, 403-433, 2004.

90.    Jung, D., and D. N. Assanis, "Modeling of a Direct-Injection Diesel Engine
      Emissions for a Quasi-Dimensional Multi-Zone  Spray Model," International
      Journal of Automotive Technology, 5:3, 165-172,  2004.

91.    Jung. D., and D. N. Assanis, "Reduced Quasi-Dimensional Combustion Model
      of  the  Direct  Injection  Diesel  Engine  for  Performance  and  Emissions
      Predictions," KSMEInternational Journal, Vol. 18, No. 5, pp.865-876, 2004.

92.    Wu, B., Lin, C.-C., Filipi, Z., Peng, H., and D.  N. Assanis, "Optimal Power
      Management for  a   Hydraulic  Hybrid  Delivery  Truck",   Vehicle  System
      Dynamics, 42:1-2, 23-40, 2004.
                                                                    Assanis, 46

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93.   Snyder, J., R., Grover, R.  0., Sick, V., and D. N. Assanis, "Transient Spray
     Cone Angles  in  Pressure-Swirl Injector  Sprays," selected  for  2004 SAE
     Transactions: Journal of Fuels and Lubricants.   (Presented as SAE Paper
     2004-01-2939, SAE Powertrain &  Fluid Systems Conference &  Exhibition,
     Tampa, Florida, October 25-28, 2004.)

94.   Sjoberg, M., Dec, J.E., Babajimopoulos, A., and  D. N. Assanis, "Comparing
     Enhanced Natural Thermal Stratification against Retarded Combustion Phasing
     for  Smoothing of  HCCI  Heat Release  Rates,"  selected  for  2004 SAE
     Transactions: Journal of Fuels and Lubricants.   (Presented as SAE Paper
     2004-01-2994, SAE Powertrain &  Fluid Systems Conference &  Exhibition,
     Tampa, Florida, October 25-28, 2004.)

95.   Chang,  J., Gurap, 0.,  Filipi, Z,  Assanis, D. N., Kuo, T. W., Najt, P., and R.
     Rask, "New Heat Transfer Correlation for the HCCI  Engine Derived from
     Measurements of Instantaneous Surface Heat Flux," selected for 2004 SAE
     Transactions: Journal of Fuels and Lubricants.   (Presented as SAE Paper
     2004-01-2996, SAE Powertrain &  Fluid Systems Conference &  Exhibition,
     Tampa, Florida, October 25-28, 2004.)

96.   Wu, B., Filipi, Z.S., Assanis, D. N., Kramer, D. M., Ohl, G. L, Prucka, M. J.,
     and E. DiValentin, "Using Artificial Neural  Networks for Representing the Air
     Flow through a 2.4  Liter VVT engine," selected for 2004 SAE Transactions:
     Journal of Fuels  and Lubricants.  (Presented as SAE Paper 2004-01-3054,
     SAE  Powertrain & Fluid Systems Conference &  Exhibition, Tampa, Florida,
     October 25-28, 2004.)

97.   Bohac,  S. and D. N. Assanis, "Effect of Exhaust Valve Timing on Gasoline
     Engine  Performance and  Hydrocarbon Emissions,"  selected for  2004 SAE
     Transactions: Journal of Fuels and Lubricants.   (Presented as SAE Paper
     2004-01-3058, SAE Powertrain &  Fluid Systems Conference &  Exhibition,
     Tampa, Florida, October 25-28, 2004.)

98.   Depcik, C., van Leer, B., and D. N. Assanis,  "The Numerical Simulation of
     Variable-Property Reacting Gas Dynamics:  New Insights and Validation,"
     Numerical Heat Transfer-Part A: Applications, 47:1, 27-56, 2005.

99.   Depcik, C. and D. N. Assanis, "Graphical  User Interfaces in an Engineering
     Educational Environment," Computer Applications in Engineering Education,
     13:1,48-59,2005.

100. Cho,  H., Jung,  D, and D.  N. Assanis, "Control Strategy of Electric Coolant
     Pumps for Fuel Economy Improvement," International Journal of Automotive
     Technology, 6:3, 269-275, 2005.
101. Chang,  J., Filipi, Z.,  Assanis, D.,   Kuo, T-W.,  Najt,  P.  and  R.  Rask,
     "Characterizing the Thermal  Sensitivity of a  Gasoline  HCCI  Engine with
     Measurements of Instantaneous Wall  Temperature and Heat Flux,"  Special
     HCCI issue, International Journal of'Engine Research, 289-310, 6:4, 2005.

102. Babajimopoulos, A., Assanis, D.N.,  Flowers, D., Aceves, S., and R.  Hessel,
     "A Fully Coupled Computational Fluid Dynamics and Multi-Zone Model with
     Detailed  Chemical  Kinetics  for  the  Simulation  of  Premixed  Charge

                                                                   Assanis, 47

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     Compression Ignition Engines," Special HCCI issue of International Journal
     of Engine Research, 497-512, 6:5, 2005.

103. Depcik,  C.  and  D.  N.  Assanis, "One Dimensional  Automotive  Catalyst
     Modeling," Progress in Energy and Combustion Science, 308-369, 31:4, 2005.

104. Kokkolaras,  M., Mourelatos, Z.P., Louca, L.S., Filipi, Z.S., Delagrammatikas,
     G.J.,  Stefanopoulou,  A.G., Papalambros,  P.Y., and  D.N. Assanis,  "Design
     under Uncertainty and Assessment of Performance Reliability for a Dual-Use
     Medium  Truck with Hydraulic-Hybrid  Powertrain and Fuel Cell  Auxiliary
     Power Unit," selected  for  2005 SAE Transactions:  Journal of Engines.
     (Presented as SAE Paper 2005-01-1396,  SP-1956, 2005 SAE World Congress,
     Detroit, Ml, April  11-14, 2005.)

105. Jacobs, T. J.,  Bohac, S. V., Assanis, D. N., Szymkowicz, P. G., "Lean and Rich
     Premixed Compression Ignition  Combustion in a Light-Duty Diesel Engine,"
     selected for 2005  SAE Transactions: Journal of Engines.  (Presented as SAE
     Paper 2005-01-0166, SP-1963, 2005  SAE World Congress, Detroit, Ml, April
     11-14,2005.)

106. Lechner,  G., Jacobs,  T.,  Chryssakis,  C.,  D. N. Assanis,  and R.  Siewert,
     "Evaluation   of Narrow  Spray  Cone  Angle,  Advanced  Injection  Timing
     Strategy to Achieve Partially Premixed Compression Ignition  Combustion in a
     Diesel Engine,"  selected for 2005 SAE Transactions: Journal of Engines.
     (Presented as SAE Paper 2005-01-0167,  SP-1963, 2005 SAE World Congress,
     Detroit, Ml, April  11-14, 2005.)

107. Aceves, S., Flowers, D.L., Espinosa-Loza,  F., Babajimopoulos, A., and  D.N.
     Assanis,  "Analysis of Premixed Charge Compression Ignition Combustion
     with  a Sequential Fluid Mechanics-Multizone Chemical  Kinetics  Model,"
     selected for 2005  SAE Transactions: Journal of Engines.  (Presented as SAE
     Paper 2005-01-0115, SP-1963, 2005  SAE World Congress, Detroit, Ml, April
     11-14,2005.)

108. Hong, S.J.,  Wooldridge, M.  S., Im, H.G.,  Assanis,  D.N.,  and Pitsch, H.,
     "Development and Application of a Comprehensive Soot Model for 3D  CFD
     Reacting  Flow Studies in a Diesel Engine," Combustion and Flame,  143:1-2,
     11-26,2005.

109. Jung, D.  and  D. N. Assanis, "Quasi-Dimensional Modeling of Direct Injection
     Diesel Engine Nitric Oxide,  Soot and  Unburned  Hydrocarbon Emissions",
     ASME Transactions:  Journal of Engineering for Gas  Turbines and Power,
     128:2,388-396,2006.

110. Chryssakis, C.A., Hagena, J.R.,  Knafl,  A., Hamosfakidis, V.D., Filipi,  Z.S.,
     and  D.N. Assanis, "In-Cylinder Reduction  of PM and  NOx Emissions  from
     Diesel Combustion with Advanced Injection Strategies," special issue on "New
     Strategies in Automotive  Diesel Engines  for Meeting  Upcoming Pollutant
     Emissions Restrictions,"  International  Journal of Vehicle  Design, 83-102,
     41:1-4,2006.
                                                                   Assanis, 48

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111. Bohac,  S.V., Han, M., Jacobs, T.J., Lopez, A.J., Assanis,  D.N.,  and  P.G.
     Szymkowicz, "Speciated Hydrocarbon Emissions from an Automotive Diesel
     Engine  and  DOC Utilizing Conventional and PCI Combustion," 2006 SAE
     Transactions: Journal of Fuels and Lubricants, 115, 41-52, 2007. (Presented as
     SAE Paper 2006-01-0201, SP-2005, 2006 SAE Congress, Detroit, Ml, April 3-
     6, 2006.)

112. Knafl, A., Busch, S.  B., Han, M., Bohac, S.V., Assanis,  D.N., Szymkowicz,
     P.G.,  and  R.D.  Blint,  "Characterizing Light-Off Behavior  and  Species-
     Resolved  Conversion Efficiency during In-Situ  Diesel  Oxidation  Catalyst
     Degreening," 2006 SAE Transactions: Journal of Fuels and Lubricants, 115,
     53-62, 2007. (Presented at 2006 SAE Congress, SP-2022, Detroit, Ml, April 3-
     6, 2006.)

113. Chang,  K.J., Babajimopoulos, A., Lavoie, G.A., Filipi, Z.S., and D.N. Assanis,
     "Analysis of Load and Speed Transitions in an HCCI Engine Using 1-D Cycle
     Simulation and  Thermal  Networks," 2006  SAE  Transactions:  Journal of
     Engines, 115,  621-633, 2007.  (Presented as SAE  Paper 2006-01-1087,  SP-
     2005, 2006 SAE Congress, Detroit, Ml, April 3-6, 2006.)

114. Guralp,  O.A., Hoffman, M.A., Assanis,  D.N., Filipi, Z.S., Kuo, T.W., Najt, P.,
     and R. Rask, "Characterizing the Effect of Combustion Chamber Deposits on a
     Gasoline HCCI Engine," 2006 SAE Transactions,  Journal of Engines,  115,
     824-835, 2007.  (Presented  as SAE Paper 2006-01-3277, Powertrain and Fluid
     Systems Conference and Exhibition," October 2006, Toronto, ON, Canada).

115. Filipi, Z., Fathy,  H., Hagena, J., Knafl, A., Ahlawat,  R., Liu, J., Jung, D.,
     Assanis, D.N.,  Peng,  H.,  and J.  Stein, "Engine-in-the-Loop Testing for
     Evaluating Hybrid Propulsion Concepts  and  Transient Emissions - HMMWV
     Case Study," 2006 SAE Transactions: Journal of Commercial Vehicles,  115,
     23-41,   2007.  (SAE  Paper 2006-01-0443,  SP-2008,  2006  SAE  Congress,
     Detroit,  Ml, April 3-6, 2006.)

116. Jacobs,  T. J. and  D.  N. Assanis, "The Attainment  of Premixed Compression
     Ignition  Low-Temperature Combustion  in  a Compression  Ignition Direct
     Injection Engine," Proceedings of Combustion Institute, vol. 31,  2913-2920,
     2007. (Presented at 31st International Symposium on Combustion,  Heidelberg,
     Germany, August 6-11, 2006).

117. Cho, H., Jung, D., Filipi, Z.S., Assanis,  D.N., Vanderslice, J., and W. Bryzik,
     "Application of Controllable Electric Cooling Pumps for Fuel Economy and
     Cooling   Performance  Improvement,"   ASME  Transactions:  Journal  of
     Engineering for Gas Turbines and Power, 127:1, 239-244, 2007.

118. Babajimopoulos, A.,  Lavoie, G.A., and  D.N. Assanis "On the Role of Top
     Dead Center Conditions in the Combustion Phasing of Homogeneous Charge
     Compression Ignition Engines," Combustion Science and Technology, 179:9,
     2039-2063, 2007.

119. Depcik,  C. and D.N. Assanis, "Merging Undergraduate and Graduate Fluid
     Mechanics Through the Use of the SIMPLE Method for the  Incompressible
                                                                   Assanis, 49

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     Navier-Stokes Equations," International Journal of Engineering Education,
     23:4,816-833,2007.

120. Jacobs, T.  Depcik, C, Hagena, J.  and D.  N. Assanis, "Instructional Use of a
     Single  Zone,   Pre-Mixed  Spark   Ignition  Heat   Release   Simulation,"
     International Journal of Mechanical Engineering Education, 35:1, 1-31, 2007.

121. Fernandes, G., Fuschetto, J.,  Filipi, Z., Assanis, D.N., and H. McKee, "Impact
     of  Military JP-8  Fuel  on  Heavy   Duty  Diesel  Engine  Performance  and
     Emissions," Journal of Automobile Engineering, Proceedings of the Institution
     of Mechanical Engineers, PartD, 221:8, 957-970, 2007.

122. Northrop, W., Jacobs, T., Assanis, D., and Bohac, S., "Deactivation of a Diesel
     Oxidation Catalyst due to Exhaust Species from Rich Premixed Compression
     Ignition in a Light-Duty Diesel  Engine," Int. J. Engine Res., 8:6, 487-498,
     2007.

123. Sampara,  C.S.,  Bissett,  E.J., Chmielewski,  M., and  D.N. Assanis, "Global
     Kinetics for Platinum Diesel  Oxidation Catalysts," Industrial and Engineering
     Chemistry Research, 46:24, 7993-8003, 2008.

124. Sampara,   C.S.,  Bissett, E.J.,  and  D.N.  Assanis,  "Hydrocarbon Storage
     Modeling for  Platinum  Diesel  Oxidation  Catalysts," Chemical  Engineering
     Science, 63, 5279-5192, 2008.

125. Hong, S.  J., Wooldridge,  M.S., Im, H.G.,  Assanis,  D.N., and   E. Kurtz,
     "Modeling of Diesel Combustion,   Soot  and  NO  Emissions  Based  on  a
     Modified  Eddy  Dissipation  Concept," Combustion Science and Technology,
     180:8,1421-1488,2008.

126. Chryssakis, C.  and D.  N. Assanis,  "A  Unified Spray Break-up  Model for
     Internal Combustion Engine Applications," Atomization and Sprays, 18:5, 375-
     426, 2008.

127. Jung, D., and D.  N. Assanis,  "A Reduced Quasi-Dimensional Model  to Predict
     the Effect of Nozzle Geometry on Diesel  Engine Performance and Emissions,"
     submitted  to Journal of Automobile Engineering  (IMechE Proc.  Part D),
     222:01,131-141,2008.

128. Jung, D.,  Wang, W.L.,  Knafl, A., Jacobs, T.J., Hu, S.J., and D.N. Assanis,
     "Experimental Investigation of  the  Abrasive Flow  Machining  Effects  on
     Injector Nozzle Geometries, Engine Performance and Emissions in a Dl Diesel
     Engine," International Journal of Automotive Technology, 9:1, 9-15, 2008.

129. Depcik, C., Assanis, D.N., and K. Sevan, "A One-Dimensional Lean NOX Trap
     Model with a Global Kinetic Mechanism that includes NH3 and N20," Int. J.
     Engine Res., 9:1, 57-77, 2008.

130. Skjoedt, M., Butts, R., Assanis,  D. N., and S.V., Bohac, "Effects of Base  Oil,
     Friction  Modifier  and  Viscosity Grade  on  Firing  Engine Friction  in  an
     Automotive Engine," TribologyInternational, 41:6, 556-563, 2008.
                                                                    Assanis, 50

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131. Granell, S. M., Assanis, D.  N., Bohac, S. V., and D. E. Gillespie", "The Fuel
     Mix Limits and Efficiency of a Stoichiometric, Ammonia and Gasoline Dual
     Fueled  Spark Ignition  Engine,"  ASME  Journal of Engineering for Gas
     Turbines and Power, 130:4,  042802:1-8, 2008.

132. Han, M., Jacobs, T. J., Assanis, D. N. and S. V. Bohac, "Method and Detailed
     Analysis of Individual  Hydrocarbon Species from Diesel Combustion Modes
     and  Diesel  Oxidation  Catalyst,"  ASME  Journal of Engineering for Gas
     Turbines and Power, 130:4,  042803:1-10, 2008. (Presented at ASME ICE Fall
     Technical Conference, Charleston, SC, October 14-17, 2007.)

133. Jacobs,  T.J.,  and  D.N. Assanis, "Characteristic  Response of a  Production
     Diesel Oxidation  Catalyst Exposed to Lean and  Rich PCI Exhaust," ASME
     Transactions: Journal  of Engineering for  Gas Turbines  and Power, 130:4,
     042805:1-9, 2008.  (Presented at ASME  ICE  Fall Technical Conference,
     Charleston, SC, October 14-17, 2007.)

134. Busch, S., Bohac, S.V.,  and  D.N. Assanis, "A Study of the Transition Between
     Lean Conventional Diesel Combustion and Lean, Premixed, Low-Temperature
     Diesel Combustion," ASME Transactions: Journal of Engineering for Gas
     Turbines and Power, 130:5, 052804:1-8, 2008.  (Presented at ASME ICE Fall
     Technical Conference, Charleston, SC, October 14-17, 2007.)

135. Chang,  J., Filipi, Z.S.,  Assanis,  D.N.,  Najt,  P.,  Rask,  R.,  Kuo,  T.W.,
     "Investigation of Mixture Preparation Effects on Gasoline HCCI Combustion
     Aided by Measurements of  Wall Heat Flux," ASME Transactions: Journal of
     Engineering for Gas Turbines and Power, 130, 062806:1-9, 2008. (Presented
     at ASME ICE  Fall Technical Conference, Charleston,  SC, October 14-17,
     2007.)

136. Depcik, C. and D. N. Assanis, "Simulating Area Conservation and  the Gas-
     Wall Interface for  One-Dimensional Based Diesel Particulate Filter Models,"
     ASME Transactions: Journal of Engineering for Gas Turbines and Power, 130,
     062807:1-18, November 2008.

137. Jung, D., Yu, S., and D.   N.  Assanis, "Modeling of a Proton  Exchange
     Membrane Fuel   Cell  with a  Large Active Area for  Thermal  Behavior
     Analysis," ASME Transactions: Journal of Fuel Cell Science and Technology,
     5,044502:1-6,2008.

138. Jacobs, T.J., Jagmin, C., Williamson, W.J., Filipi, Z.S., Assanis, D.N., and  W.
     Bryzik,  "Performance and Emission  Enhancements of a  Variable Geometry
     Turbocharger on  a Heavy-Duty Diesel  Engine," Special Issue on Performance
     and Dynamics of Multi-Wheeled and Tracked Military Vehicles, International
     Journal of Heavy Vehicle Systems, 15, 170-187, 2008.

139. Han, M., Assanis,  D. N. and S. V.  Bohac,  "Comparison of HC Species from
     Diesel   Combustion  Modes and   Characterization  of   a  Heat-up  DOC
     Formulation," International  Journal of Automotive Technology, 9:4, 405-413,
     2008.

140. Han, M., Assanis, D. N. and S. V. Bohac, "Characterization of Heat-Up Diesel
     Oxidation Catalysts through Gas Flow Reactor and In-situ Engine Testing," /.

                                                                    Assanis, 51

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     Mech. E. Part D,  Journal of Automobile Engineering, 222:9, pp. 1705-1716,
     2008.

141.  Malikopoulos, A., Assanis, D.N.,  and P.Y. Papalambros,  "Real-Time Self-
     Learning Optimization  of  Diesel Engine Calibration," ASME Transactions:
     Journal of Engineering for Gas Turbines and Power, 131, 022803:1-7, March
     2009. (Based on ASE Paper ICEF2007-1603, Proceedings of ASME ICE Fall
     Technical Conference, 537-545, Charleston, SC, October 14-17, 2007.)

142.  Prucka,  R.G., Filipi, Z.S., Assanis,  D.N., Kramer, D.M., and G.L. Ohl, "An
     Evaluation  of Residual  Gas Fraction  Measurement  Techniques  in  a High
     Degree of Freedom Spark Ignition Engine," SAE Journal of Engines,  1:1, 71-
     84, April 2009. (Presented at 2008 SAE International Congress and Exposition,
     Detroit,  Ml, April  14-17,2008.)

143.  Mosburger, M., Fuschetto, J., Assanis, D.N., Filipi, Z.  and H. McKee,  "Impact
     of High Sulfur  JP-8   Fuel on Heavy Duty  Diesel Engine  EGR  Cooler
     Condensate," 2008 SAE Transactions, Journal of Commercial Vehicles, 1:1,
     100-107, April 2009.  (Presented as SAE Paper 2008-01-1081  at 2008 SAE
     International Congress and Exposition, Detroit, Ml,  April 14-17, 2008.)

144.  Han,  M., Assanis, D.  N.,  Bohac,  S.  V.,  2008,  "Sources of  Hydrocarbon
     Emissions   from   Low   Temperature   Premixed   Compression   Ignition
     Combustion  in a Common  Rail Direct Injection Engine," Combustion Science
     and Technology, 181:3, 496-517, 2009.

145.  Malikopoulos, A.A., Papalambros,  P.Y., and Assanis, D.N., "A Real-Time
     Computational Learning Model for Sequential Decision-Making  Problems
     Under Uncertainty," ASME J. Dyn. Sys., Meas.,  Control,  131:4,  041010(8),
     2009.

146.  Hamosfakidis, V., Im,  H., and D.N. Assanis, "A Regenerative Multiple Zone
     Model for HCCI Combustion," Combustion and Flame, 156:4, 928-941 2009.

147.  Ickes, A.M., Bohac, S.V., and D.N. Assanis, "Effect of Fuel Cetane Number on
     a  Premixed   Diesel Combustion Mode,"  International Journal  of Engine
     Research, 10:4, 251-263, 2009.

148.  Ickes, A., Bohac,  S., and D.N.  Assanis, "Effect of Ethylhexyl Nitrate Cetane
     Improver  on  NOx  Emissions from  Premixed  Low-Temperature  Diesel
     Combustion," Energy and Fuels, 23, 4943-4948, 2009.

149.  Lee,  B., Filipi, Z., Assanis, D.N., and D. Jung, "Simulation-Based Assessment
     of Various Dual-Stage Boosting Systems in Terms of Performance and Fuel
     Economy Improvements,"  SAE Int.  J.  Engines, 2(1):  1335-1346,  2009.
     (Presented as SAE Paper 2009-01-1471, SAE 2009 International  Congress and
     Exposition, Detroit, Ml, April 20-23, 2009.)

150.  Northrop, W. Bohac,  S. and  D.N. Assanis, "Premixed  Low  Temperature
     Combustion  of Biodiesel and  Blends in a  High Speed Compression  Ignition
     Engine," SAE Int.  J. Fuels Lubr., 2(1): 28-40, 2009. (Presented as SAE Paper
     2009-01-0133, SAE 2009 International Congress and  Exposition, Detroit, Ml,
     April 20-23,  2009.)

                                                                   Assanis, 52

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151. Abarham, M., Hoard, J., Assanis, D.N., Styles,  D., Curtis, E.,  Ramesh, N.,
     Sluder, C.S., and J, Storey, "Modeling of Thermophoretic Soot Deposition and
     Hydrocarbon  Condensation in EGR Coolers," SAE Int. J. Fuels Lubr.,  2(1):
     921-931,  2009.  (Presented  as  SAE  Paper  2009-01-1939,  SAE   2009
     International Powertrains, Fuels and Lubricants Meeting, Florence,  Italy, June
     15-17,2009).

152. Cho,  K., Grover, R., Assanis, D.N., Filipi, Z., Najt,  P., Szekely, G., and R.
     Rask, "Combining Instantaneous  Temperature Measurements and  CFD for
     Analysis of  Fuel  Impingement  on  the DISI Engine Piston  Top," ASME
     Transactions: Journal of Engineering for Gas Turbines and Power, 132:7,
     2010.   (Presented  as  ICES2009-76117,  Proceedings of the ASME Internal
     Combustion Engine Division  2009 Spring Technical Conference ICES2009,
     Milwaukee, Wl, May 3-6, 2009.

153. Lavoie,  G.,  Martz, J., Wooldridge,  M.S. and D.N.  Assanis, "Multi-Mode
     Combustion Diagram for Spark  Assisted Compression Ignition," Combustion
     and Flame, 157, 1106-1110, 2010.

154. Malikopoulos,  A.A.,   Papalambros,   P.Y.,   and  Assanis,  D.N.,  "Online
     Identification and  Stochastic  Control for Autonomous  Internal  Combustion
     Engines," ASME1 J. Dyn. Sys., Meas., Control, 132:2, 6 pages, 2010.

155. Depcik, C., Kobiera, A., and D.N. Assanis, "Influence of Density Variation on
     One-Dimensional Modeling of Exhaust Assisted Catalytic Fuel  Reforming,"
     Heat  Transfer Engineering: An  International Journal, 31:13, 1098 - 1113,
     2010.

156. Abarham, M., Hoard, J., Assanis, D.N., Styles, D., Curtis, E.W.,  Ramesh, N.,
     Sluder,  C.S.,  Storey, J.M.,  and  M. Lance, "Review of Soot Deposition and
     Removal  Mechanisms  in  EGR  Coolers," SAE  Int.  J. Fuels Lubr.,  2010.
     (Presented at SAE 2010 World Congress, Detroit, Ml, April 13-15, 2010.)

157. Mamalis,  S.,  Nair,  V.,  Andruskiewicz, P., Olesky,  S.,  Assanis,  D.N.,
     Babajimopoulos, A., Wermuth,  N., and P.  Najt, "Comparison  of Different
     Boosting Strategies for Homogeneous Charge Compression Ignition  Engines -
     A Modeling Study," SAE Int. J. Engines, 2010. (Presented at SAE 2010 World
     Congress, Detroit, Ml, April 13-15, 2010.)

158. Cho,  K.,  Assanis,  D.N.,  Filipi,  Z.,  Szekely,  G.,  Najt,  P.  and  R.  Rask,
     "Experimental Investigation of Combustion  and Heat  Transfer  in  a Direct-
     Injection Spark-Ignition (DISI) Engine via Instantaneous Combustion Chamber
     Surface  Temperature Measurements," Mech. E. Part D, Journal of Automobile
     Engineering,  222:11, pp. 2219-2233, 2008.

159. Northrop, W., Vanderpool, L.M., Madathil,  P.V., Assanis,  D.N.,  and S.V.
     Bohac,  "Investigation of Hydrogen Emissions in Partially Premixed Diesel
     Combustion," ASME Transactions: Journal of Engineering for Gas Turbines
     and Power. J. Eng. Gas Turbines and Power,  132, 112803, 2010. (Presented as
     ASME  Paper  ICEF  2009-14063,  ASME   ICE  Division  Fall  Technical
     Conference, Lucerne, Switzerland, September 20-24, 2009).
                                                                   Assanis, 53

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160. Martz, J.,  Middleton, R., Lavoie, G., Babajimopoulos, A., and D.N. Assanis,
     "A Computational Study and Correlation of Premixed Isooctane-Air Laminar
     Reaction  Front  Properties   under  Spark   Ignited   and  Spark  Assisted
     Compression   Ignition  Engine   Conditions,"   Combustion   and  Flame,
     doi:10.1016/j.combustflame.2010.09.014, 2010.

161. Abarham,  M., Hoard, J.W., Assanis, D.N., Styles, D., Sluder, S., and J. Storey,
     "An Analytical  Study of Thermophoretic Particulate Deposition in Turbulent
     Pipe Flows," Aerosol Science and Technology, Vol. 44  (9), pp. 785-795, 2010.

162. Northrop,  W., Madathil,  P.  Bohac,  S,  and  D.N. Assanis, "Condensational
     Growth of Particulate Matter from Partially  Premixed  Low Temperature
     Combustion of  Biodiesel in  a Compression  Ignition  Engine," accepted  for
     publication in Aerosol Science and Technology, 2010.

163. Ortiz-Sotto,  E.,  Assanis,  D.N, and A.  Babajimopoulos, "A Comprehensive
     Engine  to  Drive-Cycle  Modeling  Framework for  the  Fuel  Economy
     Assessment of Advanced Engine and Combustion Technologies," accepted for
     publication \r\InternationalJournalofEnergyResearch, 2011.
Refereed Conference or Symposium Presentations

1.    Assanis, D. N.,  and A. D. Carmichael, "A Study of Wave Energy Conversion
     for an Offshore  Structure," Proceedings of the American Society of Mechanical
     Engineers 3rd  International  Offshore Mechanics and Arctic Engineering
     Symposium, II, 287-294, 1984.

2.    Kamo, R. and D. N.  Assanis, "Thin Thermal Barrier Coatings for Engines,"
     ASME Paper 89-ICE-14, ASME-ETCE Technical Conference, Houston, TX,
     1989.

3.    Wiese, K., M. Bonne, F. Friedmann, and D. N. Assanis, "Combustion and Heat
     Transfer Studies in a Direct-Injection Diesel Engine," SAE Paper 891902, SAE
     International Off-Highway Meeting and Exposition, Milwaukee, Wl, Sept. 11-
     14,1989.

4.    Assanis,  D.  N.,  R. R. Sekar, D. Baker,  C.  Siambekos, R.  L. Cole, and T.
     Marciniak, "Simulation Studies of Diesel Engine Performance with Oxygen
     Enriched Air  and Water Emulsified Fuels," ASME  Paper 90-ICE-17, ASME-
     ETCE Technical Conference,  New Orleans, LA, Jan. 1990.

5.    Assanis,  D. N., Friedmann, F. A., Wiese, K. L., Zaluzec, M. J.,  and  J.  M.
     Rigsbee,  "A Prototype Thin-film Thermocouple  for Transient Heat Transfer
     Measurements  in  Ceramic-Coated  Combustion  Chambers,"  SAE   Paper
     900691, SAE International Congress  and  Exposition, Detroit, Ml, Feb. 26-
     March 2, 1990.

6.    Varnavas, C., and D. N.  Assanis, "Combustion  Studies in  a Diesel Engine
     Using  a  Multidimensional  Engine  Simulation,"  ASME-ETCE  Technical
     Conference, Houston, TX, Jan. 20-23, 1991.
                                                                   Assanis, 54

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7.    Assanis, D. N., and F. Friedmann,  "A Telemetry Linkage System for Piston
     Temperature Measurements in a Diesel  Engine," SAE Paper 910299, SAE
     International Congress and Exposition, Detroit, Ml, Feb. 25-March 1, 1991.

8.    Assanis,  D. N., and  C. Varnavas, "On the Prediction of Diesel  Engine
     Combustion Using  a  Multi-Dimensional  Computer Code," Proceedings  of
     International Conference on the Analysis of Thermal and Energy Systems, pp.
     539-554, Athens, Greece, June 1991.

9.    Assanis, D. N., and D. Baker, "Thermodynamic and Heat Transfer Analysis of
     Ceramic-Insulated  Diesel  Engine  Part  I:  Methodology,"  Proceedings  of
     International Conference on the Analysis of Thermal and Energy Systems, pp.
     571-583, Athens, Greece, June 3-6, 1991.

10.   Assanis, D. N., and D. Baker, "Thermodynamic and Heat Transfer Analysis of
     Ceramic-Insulated  Diesel Engine  Part II:  A Case Study," Proceedings  of
     International Conference on the Analysis of Thermal and Energy Systems, pp.
     585-599, Athens, Greece, June 3-6, 1991.

11.   Tamamidis,  P., and D. N. Assanis,  "2-D and 3-D Computations  of Engine
     Scavenging  Flows,"  ASME  Paper  92-ICE-1,  ASME-ETCE   Technical
     Conference, Houston, TX, Jan. 26-29, 1992.

12.   Karvounis, E.  and  D.N. Assanis,  "An  Integrated  Framework  for  Internal
     Combustion Engine Simulation and Design," ASME Paper 92-ICE-2,  ASME-
     ETCE Technical Conference, Houston, TX, Jan. 26-29, 1992.

13.   Shin, L,  and  D.  N.  Assanis,  "Modeling  Hydrocarbon  Absorption and
     Desorption Processes into Cylinder Wall Oil Films," Proceedings of American
     Chemical Society National Meeting, Washington, D.C., Aug. 23-25, 1992.

14.   Syrimis, M. and D. N. Assanis, "Combustion of Low-Ash Coal-Diesel  Slurries
     in a  High-Speed, Direct-Injection Diesel Engine," Coal-Fueled Diesel Engines
     1993, 53-61, ICE-19, ASME-ETCE Technical Conference, Houston, TX, Jan.
     31-Feb. 3, 1993.

15.   Assanis, D. N.,  Gavaises, M., and G. Bergeles, "Calibration and Validation of
     the Taylor Analogy Breakup  Model for  Diesel Spray Calculations," ASME
     Paper 93-ICE-11, ASME-ETCE Technical Conference, Houston, TX, Jan. 31-
     Feb. 3, 1993.

16.   Assanis, D. N. and Karvounis, E., and J.  A.E. Bell, "Design Optimization  of
     the  Piston Compounded Adiabatic  Diesel   Engine   Through  Computer
     Simulation", SAE Paper  930986, SAE International Congress and  Exposition,
     Detroit, Ml, March 1-5, 1993.

17.   Varnavas,  C.,  and D. N. Assanis, "Evaluation  of an  Improved  Model  for
     Droplet Evaporation in  High Temperatures," Sixth Annual  Conference on
     Liquid Atomization and Spray Systems, I LASS 93 Americas, Worcester, MA,
     May 17-19, 1993.

18.   Shih, L., and D. N. Assanis, "Experimental Validation of Spray Dynamics and
     Wall Interaction Models in Quiescent Chambers", Sixth Annual  Conference on

                                                                   Assanis, 55

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     Liquid Atomization and Spray Systems, I LASS 93 Americas, Worcester, MA,
     May 17-19, 1993.

19.   Tamamidis, P., and D. N. Assanis, "Benchmarking High Resolution Schemes
     in Two-Dimensional Unsteady Flows," Forum on  Unsteady Flows, FED-157,
     pp. 95-106, ASME International Fluids Engineering Conference, Washington,
     D.C.June 20-24, 1993.

20.   Tamamidis, P., and D.  N. Assanis, "Numerical Simulation of Internal Flows in
     Complex  Geometries  Using  Curvature-Modified  k-e  Models,"  ASME
     International  Fluids Engineering Conference,  Forum on  Turbulent Flows,
     Washington, D.C. June 20-24, 1993.

21.   Li, Q.,  and  D. N. Assanis,  "A Quasi-Dimensional Combustion Model  for
     Diesel  Engine  Simulation,"  Alternate  Fuels,  Engine  Performance  and
     Emissions,  ICE-20,  109-118,  ASME-ICED  Fall Technical  Conference,
     Morgantown, WV, September 26-29, 1993.

22.   Assanis, D. N., and B. Bolton, "Variable Valve Timing Strategies for Optimum
     Engine  Performance and Fuel Economy," ASME Paper 94-ICE-5, ASME
     ETCE Conference, New Orleans, LA, January 23-26, 1994.

23.   Bolton,  B.,  and  D.   N.  Assanis,  "Optimum  Breathing   Strategies  for
     Turbocharged Diesel Engines Based on the Miller Cycle Concept," ASME PD-
     Vol. 64-8.2,  pp. 253-262, Second  Biennial European  Joint Conference on
     Engineering Systems Design and Analysis ESDA,  London, England, July 4-7,
     1994.

24.   Varnavas, C., and  D. N.  Assanis,  "An  Improved Model  for Predicting
     Evaporation of High Pressure Engine Sprays", I CLASS 94, Sixth International
     Conference on Liquid  Atomization and Spray Systems,   Rouen, France, July
     18-22,1994.

25.   Herring,  P.,  and D. N. Assanis, "A  Low Heat Rejection and Low Thermal
     Distortion Piston-Liner Design," ASME-ICED Fall  Technical  Conference,
     Lafayette, IN, October 2-5, 1994.

26.   Varnavas, C., and  D.  N.  Assanis,  "A High Temperature and High Pressure
     Evaporation  Model for the  KIVA-3  Code," SAE Paper 960629,  1996 SAE
     International Congress, Detroit, Ml, February 26-29, 1996.

27.   Agarwal, A.,  Filipi,  Z.,  Assanis,  D.  N.,  and D.  Baker, "On Turbulence
     Modeling for a Quasi-Dimensional Spark Ignition Engine Simulation,"  Sixth
     International  Conference  on  Numerical  Combustion,  SIAM (Society  for
     Industrial and Applied Mathematics),  New Orleans, March 4-6, 1996.

28.   Nelson II, S. A., Filipi, Z., and D.  N. Assanis,  "The Use of Neural Networks
     for Matching Compressors  with Diesel  Engines," Presented  at ASME-ICE
     Spring Technical Conference, Youngstown, OH, April 21-24, 1996.

29.   Papageorgakis,  G., Agarwal,  A.,  Zhang, G.,  and  D.  N. Assanis,  "Multi-
     Dimensional  Modeling of Natural Gas  Injection,  Glow  Plug Ignition, and

                                                                   Assanis,  56

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     Combustion  with  the  KIVA-3  Code,"  ASME-ICE   Spring  Technical
     Conference, Youngstown, OH, April 21-24, 1996.

30.   Sun,  X.,  Assanis,  D.  N.,  and  G.  Brereton,  "Numerical  Modeling  and
     Experimental Validation of Steady-State Hydrocarbon Emissions from Small
     Utility Four-Stroke Engines,"  Presented  in  Session  on  Engine  Emissions,
     ASME-ICE  Spring Technical  Conference,  Youngstown,  OH,  April 21-24,
     1996.

31.   Zhang, G., and D. N.  Assanis, "Application of 1-D and 3-D  Gas Dynamic
     Modeling to Engine Manifolds," invited  paper, Symposium on Supercomputer
     Applications in the Automotive Industries, 29th ISATA, Florence, Italy, June
     3-6,1996.

32.   Filipi, Z., and D.N. Assanis, "On Determining the Optimum Stroke-to-Bore
     Ratio for a Spark-Ignition Engine  of  a Given  Displacement,"  Powertrain
     Systems  Session,  26th International FISITA Congress,  Prague, June 16-23,
     1996.

33.   Zhang, G., and D. N. Assanis,  "3-D Turbulent Flow Predictions Using High-
     Order  Schemes  and   Comparison  with   Measurements,"   Presented  in
     Symposium on Numerical Developments  in  CFD, ASME Fluids Engineering
     Division Summer  Meeting, San Diego, CA, July 7-11, 1996.

34.   Zhang, G., and D. N. Assanis,  "Finite  Volume Predictions of 3D Turbulent
     Compressible  Flows Using a Segregated Solution Approach and High Order
     Schemes,"  International   Symposium  on  Finite  Volumes  for  Complex
     Applications -  Problems and Perspectives, Rouen, France, July 15-18, 1996.

35.   Poola,  R.,  Assanis, D. N., Sekar,  R.,  and  G.  R.  Cataldi,  "Study of Using
     Oxygen-Enriched  Combustion Air for Locomotive Diesel Engines," Presented
     in Diamond Anniversary Conference of the  ASME-ICE  Division, Fairborn,
     OH, October 20-23, 1996.

36.   Filipi, Z. S., and  D.  N. Assanis, "A  Non-Linear, Transient, Single-Cylinder
     Diesel  Engine Simulation for Predictions  of Instantaneous Engine Speed and
     Torque," Presented at ASME-ICE Spring Technical  Conference, Fort Collins,
     Colorado, April 27-30,1997.

37.   Assanis,  D. N., Atreya, A., Borgnakke,  C., Dowling, D., Filipi, Z., Hoffman,
     S., Homsy, S., Kanafani, F., Morrison, K., Patterson, D., Syrimis, M., Winton,
     D., Zhang, G., and Bryzik, W., "Development of a Modular Multi-Cylinder
     Transient  Diesel  Engine  Simulation for System Performance  and Vibration
     Studies," Presented at ASME-ICE Spring Technical  Conference, Fort Collins,
     Colorado, April 27-30,1997.

38.   Zhang, G., and D.  N. Assanis,  "Manifold  Gas Dynamic Modeling  and its
     Coupling with Single Cylinder Engine Models using SIMULINK," Presented
     at ASME-ICE  Spring Technical Conference,  Fort Collins, Colorado, April 27-
     30, 1997.
                                                                    Assanis, 57

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39.   Syrimis,   M.,  and  D.  N.  Assanis,  "Knocking  Cylinder  Pressure  Data
     Characteristics in a Spark-Ignition Engine," Presented at ASME-ICE Spring
     Technical Conference, Fort Collins, Colorado, April 27-30, 1997.

40.   Agarwal,  A.,  and  D.  N. Assanis, "Modeling  the Effect  of Natural  Gas
     Composition on  Ignition  Delay  Under Compression Ignition Conditions,"
     Presented as SAE Paper 971711, 1997 SAE International Fuels and Lubricants
     Meeting, Dearborn, Ml, May 5-8, 1997.

41.   Baker, D. M., and D. N. Assanis, "A Coupled  Methodology for Modeling the
     Transient Thermal Response of SI  Engines Subject to Time-Varying Operating
     Conditions," Presented as SAE Paper 971859, Vehicle Thermal Management
     Systems  VTMS-3 International Conference,  Indianapolis,  IN, May  19-22,
     1997.

42.   Assanis,  D. N.,  Filipi, Z. S., and  G.  Zhang, "Development  of Interactive
     Graphical Software Tools in the  Context of Teaching Modeling  of Internal
     Combustion Engines in a Multimedia  Classroom,"  Presented at 1997 ASEE
     Annual Conference, Milwaukee, Wl, June 15-18, 1997.

43.   Filipi,  Z. S., Homsy, S. C., Morrison, K. M.,  Hoffman,  S., Dowling, D. R., and
     D.  N.  Assanis, "Strain Gage-Based Instrumentation for  In-Situ Diesel  Fuel
     Injection System  Diagnostics," Presented at 1997 ASEE Annual Conference,
     Milwaukee, Wl, June 15-18, 1997.

44.   Nishida,   K., Ceccio,  S.,  Assanis,  D.  N.,  Tamaki,  N,  and  Hiroyasu,  H.,
     "Characterization of Cavitation Flow in a Simple Hole Nozzle," Seventh
     International Conference on Liquid Atomization  and  Spray Systems, Seoul,
     Korea, Aug. 18-22, 1997.

45.   Syrimis,  M., and D. N. Assanis, "Characterization  of Knocking Combustion
     and  its Dispersion," ASME-ICE  Fall  Technical  Conference,  Madison,  Wl,
     Sept. 27-Oct. 1,1997.

46.   Agarwal, A., and Assanis, D. N., "Multi-Dimensional Modeling of Natural Gas
     Ignition under Compression  Ignition Conditions  Using Detailed Chemistry,"
     SAE Paper 980136, SAE  International Congress and Exposition, Detroit, Ml,
     Feb. 23-26, 1998.

47.   Agarwal,  A., and Assanis,  D.  N.,  "Multi-Dimensional Modeling of Nitric
     Oxide  Formation in Direct-Injection Natural  Gas  Engines, COMODIA  98,
     Proceedings of  the  Fourth International Symposium on  Diagnostics  and
     Modeling of Combustion in Internal Combustion Engines, 561 -566, Kyoto,
     July 20-23, 1998.

48.   Assanis,  D.N., Filipi, Z.S.,  Fiveland,  S.B.,  and  Syrimis, M.,  "A  Predictive
     Ignition Delay Correlation Under  Steady-State and  Transient Operation  of a
     Direct-Injection  Diesel  Engine,"  Presented  at  ASME-ICE  Fall  Technical
     Conference, Ann Arbor, Ml, October 16-20, 1999.

49.   Nishimura,  A.,  and D.  N.  Assanis,  "A  Model for Primary Diesel  Fuel
     Atomization Based on Cavitation Bubble Collapse Energy," Eight International

                                                                    Assanis, 58

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     Conference  on  Liquid Atomization  and  Spray Systems,  ICLASS-2000,
     Pasadena, CA, July 16-20, 2000.

50.   Filipi, Z., Wang, Y., and Assanis, D. N., "Effect of Variable Geometry Turbine
     (VGT) on Diesel Engine and Vehicle System Transient Response," Presented
     as SAE Paper 2001-01-1247,  SAE World Congress,  Detroit, Ml, March 5-8,
     2001.

51.   Lin, C. C., Filipi, Z., Wang, Y., Louca, L., Peng,  H., Assanis, D. N. and Stein,
     J.,  "Integrated,  Feed-Forward  Hybrid  Electric  Vehicle  Simulation   in
     SIMULINK and its Use for Power Management Studies," Presented as SAE
     Paper 2001-012-1334, included in Advanced Hybrid Vehicle Powertrains, SP-
     1607, SAE World Congress, Detroit, Ml, March 5-8, 2001.

52.   Buyuktur, S., Wooldridge, M.  and D. N. Assanis,  "Development of a Forward-
     Looking  Fuel Cell  Vehicle Simulation,"  2001 Global Powertrain Congress,
     June 5-7, 2001, Detroit, Ml.

53.   Grover, R. and D. N. Assanis,  "A Spray Wall Impingement Model Based  Upon
     Conservation  Principles,"  COMODIA   2001,  Proceedings  of the  Fifth
     International Symposium on  Diagnostics and Modeling  of Combustion  in
     Internal Combustion Engines,  Nagoya, Japan, July 1-4, 2001.

54.   Hong, S. J.,  D.  N. Assanis and M. Wooldridge, "Multi-Dimensional Modeling
     of NO and Soot Emissions with Detailed Chemistry  and Mixing in a Direct
     Injection Natural Gas  Engine,"  SAE  Paper  2002-01-1112, Session on Multi-
     Dimensional  Engine  Modeling,  2002  SAE World  Congress,  Detroit, Ml,
     March 4-7, 2002.

55.   Bohac, S. and  D.  N.  Assanis,  "Quantification  of Local  Ozone  Production
     Attributable  to Automobile Hydrocarbon Emissions," SAE Paper 2001-01-
     3760,  2001;  presented  at  Environmental   Sustainability  Conference  and
     Exhibition: Land, Sea and Air  Mobility, Graz, Austria, April 8-10, 2002.

56.   Grover, R.O., Assanis, D. N., Lippert, A.M.,  El Tahry, S.H.,   Drake, M.C.,
     Fansler,  T.D., Harrington, D.L.,  "A Critical Analysis of Splash Criteria  for
     SIDI Spray Impingement," ILASS Americas 2002, Madison, Wl, May 14-17,
     2002.

57.   Chryssakis, C. A., Driscoll,  K.D., Sick, V., and D. N. Assanis, "Validation of
     an  Enhanced  Liquid  Sheet Atomisation  Model  Against Quantitative  Laser
     Diagnostic Measurements,"  ILASS-Europe 2002, Zaragoza,  Spain, September
     9-11,2002.

58.   Wu, B.,  Lin, C.-C.,  Filipi, Z., Peng,  H., and D. N. Assanis, "Optimization of
     Power Management  Strategies  for  a  Hydraulic  Hybrid  Medium Truck",
     Proceedings of the 6th International Symposium on Advanced Vehicle Control,
     Hiroshima, Japan, September 2002.

59.   Louca, L., Kokkolaras,  M., Delagrammatikas, G., Michelena, N., Filipi,  Z.,
     Papalambros, P., and  D. N. Assanis,    "Analytical Target Cascading for  the
     Design of an Advanced Technology Truck," IMECE 2002-32860, 2002 ASME
                                                                    Assanis, 59

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     International Mechanical Engineering Congress and Exposition, New Orleans,
     LA, November 17-22, 2002.

60.   Delagrammatikas, G. and D.  N. Assanis,  "Optimization of Advanced Engine
     Controls for Conventional Vehicles: A Driving Cycle Perspective," submitted
     to Symposium on Advanced  Automotive Technologies, IMECE 2002-32087,
     ASME  International Mechanical Engineering  Congress and Exposition, New
     Orleans, LA, November 17-22, 2002.

61.   Jacobs,  T. J., Assanis, D. N., and Z. S. Filipi, "The Impact of Exhaust Gas
     Recirculation on Performance and Emissions of a Heavy-Duty Diesel Engine,"
     SAE Paper, 2003-01-1068, 2003 SAE World Congress, Detroit, Ml, March 3-
     6, 2003.

62.   Chryssakis, C.  A.,  Assanis,  D. N., Lee,  J.  K.,  Nishida,  K.,  "Fuel Spray
     Simulation of High-Pressure Swirl-Injector for DISI  Engines and Comparison
     with Laser Diagnostic Measurements,"  SAE Paper 2003-01-0007, 2003 SAE
     World Congress, Detroit, Ml,  March 3-6, 2003.

63.   Chryssakis, C. A., Assanis, D. N., Lee, J. K., Nishida, K., "An Investigation of
     the  Breakup Mechanisms  for Swirl   Sprays  From High-Pressure  Swirl
     Injectors," ICLASS 2003, Sorrento, Italy, July 13-18, 2003.

64.   Kazancioglu, E., Wu, G., Ko,  J., Bohac, S., Filipi, Z., Hu, S. J., Assanis, D. N.,
     and Saitou,  K., Robust  Optimization of an Automotive Valvetrain Using a
     Multi-Objective   Genetic  Algorithm,   Paper   DETC   2003/DAC-48714,
     Proceedings of DETC'03 ASME 2003 Design  Technical Conference, Chicago,
     IL, Sept. 2-6, 2003.

65.   Zeng, P. and  D. N.  Assanis,  "Time-Resolved  Heat Transfer in Engine Intake
     Manifold," TRCON-03  International  Symposium  on Transient  Convective
     Heat  and  Mass Transfer in  Single and Two-Phase Flows, Cesme, Turkey,
     August 17-22, 2003.

66.   Babajimopoulos, A., Lavoie, G. A. and  D.  N.  Assanis,  "Modeling HCCI
     Combustion with  High Levels of Residual  Gas Fraction  -  A Comparison of
     Two  VVA Strategies",  SAE  Paper 2003-01-3220,  2003 SAE International
     Powertrain and Fluid Systems Conference, Oct.27-30, Pittsburgh, PA.

67.   Hong, S.J, Assanis,  D. N., Wooldridge,  M. S., Im,  H.G., Kurtz, E. M., and H.
     Pitsch,  "Modeling of Diesel  Combustion  and  NO Emissions Based  on a
     Modified Eddy  Dissipation Concept," SAE Paper  2004-01-0107, 2004 SAE
     World Congress, Detroit, Ml,  March 8-11, 2004.

68.   Zeng, P.  and  D.  N. Assanis,  "Cylinder  Pressure Reconstruction  and  its
     Application to Heat Transfer  Analysis," SAE Paper 2004-01-0922, 2004 SAE
     World Congress, Detroit, Ml,  March 8-11, 2004.

69.   Grover,  R. 0., Assanis, D. N., and A.M. Lippert, "A Comparison of Classical
     Atomization Models against Current  Experimental Measurements  within a
     Zero-Dimensional Framework," I LASS  Americas,  17th  Annual Conference on
     Liquid Atomization and Spray Systems, Arlington, VA,  May 2004.
                                                                   Assanis, 60

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70.   Vanzieleghem,  B., Assanis, D.,  Im, H.G., "Modeling  of Gasoline Direct
     Injection Combustion using  KIVA-3V: Development of an Extended Coherent
     Flamelet Model  and  Validation with Optical  Engine Planar  Laser  Induced
     Fluorescence Measurements", COMODIA  2004, Yokohama,  Japan, August
     2004.

71.   Vanzieleghem, B.P., C.A. Chryssakis, R.O. Grover, V. Sick and D.N. Assanis,
     "Modeling of Gasoline Direct Injection Mixture Formation with KIVA-3V and
     Validation   with   Optical  Engine  Planar  Laser  Induced  Fluorescence
     Measurements:  Development of  Spray Breakup   and  Wall  Impingement
     Models," COMODIA 2004, Yokohama, Japan, August 2004.

72.   Zeng, P., Prucka,  R. G., Filipi, Z.  S.,  and D. N.  Assanis, "Reconstructing
     Cylinder Pressure  of a  Spark-Ignition  Engine  for  Heat  Transfer and  Heat
     Release Analysis," ASME Paper ICEF 2004-886, ASME  Internal Combustion
     Engine Technical Conference, Long Beach, CA, October 24-27, 2004.

73.   Zeng, P., and D.N. Assanis, "Unsteady Convective Heat Transfer Modeling
     and Application to Engine Intake Manifolds," IMECE Paper 2004-60068, 2004
     ASME International Mechanical Engineering Congress and R&D  Exposition,
     Anaheim, CA, Nov 13-19, 2004.

74.   Zeng, P., and D.N. Assanis, "The Development of a Computer-Based Teaching
     Tool for Internal  Combustion Engine Courses," IMECE  Paper 2004-61998,
     2004  ASME  International   Mechanical Engineering Congress  and  R&D
     Exposition, Anaheim, CA, Nov 13-19, 2004.

75.   Cho, H., Jung, D., Filipi, Z., Assanis, D. N., Bryzik, W., and  J. Vanderslice,
     "Application of Controllable Electric Coolant Pumps for Fuel Economy and
     Cooling Performance Improvement," IMECE Paper 2004-61056, 2004 ASME
     International  Mechanical   Engineering  Congress   and   R&D   Exposition,
     Anaheim, CA, Nov 13-19, 2004.

76.   Chryssakis,  C.,  Assanis,  D.N., Kook,  S.,  and  C.  Bae,  "Effect of Multiple
     Injections on Fuel-Air Mixing and Soot Formation in  Diesel Combustion Using
     Direct  Flame Visualization  and CFD Techniques,"  ASME Paper  ICES2005-
     1016, ASME Internal Combustion Engine Technical  Conference, Chicago, IL,
     April 5-7, 2005.

77.   Knafl,  A.,  Hagena, J.,  Filipi,  Z.,  and D. N.  Assanis,  "Dual  Use Engine
     Calibration:  Leveraging  Modern Technologies to Optimize Performance and
     Emissions Trade-offs," SAE Paper 2005-01-1549, SP-1962, 2005 SAE World
     Congress, Detroit, Ml, April  11-14, 2005.

78.   Assanis,  D.  N.,  Cho, W., Choi, I., Ickes, A., Jung,  D., Martz, J.,  Nelson, R.,
     Sanko, J., Thompson,  S., Brevick,  J.E., and B.  Inwood,  "Pressure Reactive
     Piston   Technology  Investigation  and  Development  for  Spark  Ignition
     Engines," SAE  Paper  2005-01-1648, Session on Cl  and SI Power Cylinder
     Systems, SP-1964, 2005 SAE World Congress, Detroit, Ml, April 11-14, 2005.

79.   Lee, S., Bae, C., Prucka, R., Fernandes, G., Filipi,  Z. S., and  D.  N. Assanis,
     "Quantification  of Thermal  Shock in a Piezoelectric Pressure Transducer,"

                                                                   Assanis, 61

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     SAE  Paper 2005-01-2092, SAE  Brazil  Fuels  &  Lubricants  Meeting &
     Exhibition (Co-sponsored by SAE International), Rio de Janeiro,  Brazil, May
     11-13,2005.

80.   Chryssakis, C.A. and  D.N. Assanis, "A Secondary Atomization Model for
     Liquid  Droplet  Deformation  and  Breakup  under  High Weber  Number
     Conditions,"  18th Annual Conference  on  Liquid  Atomization  and  Spray
     Systems, Irvine, CA, May 22-25, 2005.

81.   Sampara, C.  Depick, C., and  D.N. Assanis, "Framework for Modeling the
     Components of a Fuel Processing System for Fuel Cell Applications," IMECE
     Paper  2005-81330,  IMECE  2005  Proceedings,   2005  ASME   Design
     Engineering Conference,  Orlando, FLA, November 5-11, 2005.

82.   Hamosfakidis, V,  Im,  H., and D.N. Assanis,  "A  Regenerative Multiple
     Flamelet Model for  PPCI  Engine  Simulations,"  Eastern  States Section
     Combustion Institute Fall Technical Meeting, November 13-16, 2005.

83.   Cho, W., Jung, D. and  D.N. Assanis, "Numerical  Investigation  of Pressure
     Reactive Piston Technology in a Spark-Ignition Engine," Paper 20056083,
     18th  International  Combustion  Engine Symposium, Jeju  Island,  Korea,
     December 20-22, 2005.

84.   Jacobs, T. J., Knafl, A.,  Bohac, S.V., Assanis, D.N.,  and  P.G. Szymkowicz,
     "The Development of Throttled and Unthrottled PCI Combustion in a  Light-
     Duty Diesel Engine," SAE Paper 2006-01-0202, 2006 SAE Congress, Detroit,
     Ml, April 3-6, 2006.

85.   Hagena, J.R.,  Filipi, Z.S., and D.N.  Assanis,  "Transient  Diesel Emissions:
     Analysis of Engine Operation During a Tip-In", SAE Paper 2006-01-1151,
     2006 SAE Congress, Detroit, Ml, April 3-6, 2006.

86.   Chryssakis, C.A., Assanis, D. N., and C. Bae, "Development and Validation of
     a Comprehensive CFD Model of Diesel Spray Atomization Accounting for
     High  Weber Numbers," SAE Paper  2006-01-1546,  SP-2010,  2006  SAE
     Congress, Detroit, Ml, April 3-6, 2006.

87.   Jung,  D., and  D.N. Assanis, "Numerical Modeling of Cross Flow Compact
     Heat Exchanger with Louvered Fins using Thermal Resistance Concept," 2006
     SAE Congress, Detroit, Ml, April 3-6, 2006.

88.   Malikopoulos, A., Filipi,  Z., and D.N. Assanis, "Simulation of an Integrated
     Starter Alternator (ISA) System for the HMMWV," SAE Paper 2006-01-0442,
     SP-2008, 2006 SAE Congress, Detroit, Ml, April 3-6, 2006..

89.   Yoo, S., Jung,  D., and  D.N.  Assanis, "Numerical Modeling  of the Proton
     Exchange Membrane Fuel Cell for Thermal Management,"  Paper  FUELCELL
     2006-97062,  4th International  Conference on Fuel Cell Science,  Engineering
     and Technology, Irvine, CA, June 19-21, 2006.

90.   Knafl, A., Jacobs, T., Bohac, S.V., and  D. N. Assanis, "The Load  Limits of
     Low-Temperature Premixed Compression Ignition Diesel Combustion,"  ISCE

                                                                  Assanis, 62

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     20006, 2nd International Symposium on Clean and High Efficiency Combustion
     Engines, Tianjin, China, July 10-13, 2006.

91.   Hamosfakidis, V. Im, H. and D.N. Assanis, "A Regenerative Multiple Flamelet
     Model  (RMF),"  Poster  Presentation,  31st International  Symposium  on
     Combustion, Heidelberg, Germany, August 6-11, 2006.

92.   Filipi, Z., Hagena, J., Fathy, H., Assanis, D., Stein, J., "Investigating Effects of
     Transients on Diesel Emissions using Engine-in-the-Loop Testing", THIESEL
     2006 Conference on Thermo- and Fluid Dynamic Processes in Diesel Engines,
     Valencia, Spain, September 2006.

93.   Grannell,  S.M.,  Assanis, D.N.,   Bohac,  S.V.,  and  D.  E.  Gillespie, "The
     Operating Features of a Stoichiometric,  Ammonia and Gasoline Dual  Fueled
     Spark   Ignition   Engine,"   Paper  IMECE2006-13048,  Proceedings   of
     IMECE2006 2006 ASME International Mechanical Engineering Congress and
     Exposition, Chicago, IL, November 5-10, 2006.

94.   Hamosfakidis, V., Kobiera, A., Im, H., and D.N.  Assanis,  "A Two Conserved
     Scalar Modeling for HCCI Applications," 5th  UC  Combustion  Meeting, March
     25-28, 2007, San Diego, CA.

95.   Jacobs,  T.J., and D.N. Assanis, "On the Sensitivity of  NOx  to Exhaust Gas
     Recirculation in a Premixed Compression Ignition Engine," 5th US Combustion
     Meeting, March 25-28, 2007, San Diego, CA.

96.   Chang, K.J., Lavoie, G.A., Babajimopoulos, A., Filipi, Z.S., and D.N. Assanis,
     "Control of a Multi-Cylinder HCCI Engine during  Transient Operation by
     Modulating  Residual  Gas Fraction  to  Compensate  for  Wall Temperature
     Effects," SAE Paper 2007-01-0204, SAE 2007 World Congress, Detroit, Ml,
     April  16-19, 2007.

97.   Hattori, K.,  Murotani, T., Sato, E., Chryssakis,  C., Babajimopoulos, A., and
     D.N.  Assanis, "Simultaneous  Reduction of  NOx and Soot in a Heavy-Duty
     Diesel Engine by Instantaneous Mixing of Fuel and Water," SAE Paper 2007-
     01-0125, SAE 2007 World Congress, Detroit,  Ml, April 16-19, 2007.

98.   Knafl, A.,  Han, M.,  Bohac,  S.V., Assanis, D.N., and  P.G. Szymkowicz,
     "Comparison of Diesel Oxidation  Catalyst Performance on an Engine and  a
     Gas Flow Reactor," SAE Paper 2007-01-0231,   SAE 2007 World Congress,
     Detroit, Ml, April 16-19, 2007.

99.   Baglione,  M., Duty,  M.,  Ni, J., and  D.N.   Assanis,  "Reverse  Dynamic
     Optimization Methodology for Maximizing  Powertrain System Efficiency,"
     Fifth IFAC Symposium on Advances in Automotive Control, Monterey Coast,
     CA, August 20-22, 2007.

100. Hamosfakidis, V.,  Kobiera, A., and D.N.  Assanis, "A Regenerative Multiple
     Flamelet Model for  non-Premixed Combustion with non-Uniform EGR," 5th
     IASME/WSEAS  International  Conference   on  Heat   Transfer,  Thermal
     Engineering and  Environment,  Vouliagmeni, Athens, Greece, August 25-27,
     2007.
                                                                   Assanis, 63

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101. Malikopoulos, A.,  Papalambros,  P.Y.,  and  D.N.  Assanis,  "A  Learning
     Algorithm for Optimal Internal Combustion Engine Calibration in Real Time,"
     ASME  2007 International  Design Engineering Technical  Conference and
     Computers and  Information in  Engineering Conference,  Las Vegas,  Nevada,
     September 4-7, 2007.

102. Sethu, C.,  Leustek, M., Bohac, S.V., Assanis D.N. and Z.S. Filipi,  "An
     Investigation in Measuring Crank-Angle Resolved In-Cylinder Engine Friction
     Using Instantaneous IMEP  Method," Powertrain & Fluid Systems  Conference
     & Exhibition, Donald E. Stephens Convention  Center,  Rosemont (Chicago),
     IL, October 29 - November 1, 2007.

103. Malikopoulos, A., Papalambros, P.Y.,  and D.N.  Assanis,  "A  New  State-
     Representation Learning Model for  Sequential Decision-Making Problems
     Under  Uncertainty,"  IMECE  2007-41258,  Proceedings  of  2007   ASME
     International  Mechanical  Engineering  Congress  and   Exposition,  Seattle,
     Washington, November 10-16, 2007.

104. Cho,  K.,  Assanis,  D., Filipi,  Z.,  Szekely,  G.,  Najt,  P.  and R.  Rask,
     "Investigation of Combustion and  Heat Transfer in  a Direct Injection Spark
     Ignition (DISI)  Engine through  Instantaneous Combustion Chamber Surface
     Temperature Measurements," Internal Combustion Engines: Performance, Fuel
     Economy  and Emissions,  Institution  of Mechanical  Engineers, Combustion
     Engines and Fuels Group, London, England, December 11-12, 2007.

105. Malikopoulos, A., Papalambros, P.Y., and D.N.  Assanis, "Optimal  Engine
     Calibration for Individual Driving  Styles,"  2008 SAE International Congress
     and Exposition, Detroit, Ml, April 14-17, 2008.

106. Lee, B., Jung, D., Assanis, D.N., and Z.S. Filipi, "Dual-Stage Turbocharger
     Matching  and  Boost  Control  Options,"   ASME  Paper ICES  2008-1692,
     Proceedings of the ASME  Internal Combustion  Engine Division 2008 Spring
     Technical  Conference, Chicago, IL, April 27-30,  2008.

107. Guralp,  0., Hoffman, M., Assanis, D.N., Filipi, Z., Kuo, T.W., Najt. P. and  R.
     Rask, "Thermal  Characterization of Combustion  Chamber  Deposits on the
     HCCI Engine Piston  and  Cylinder Head  Using Instantaneous Temperature
     Measurements," SAE  Paper 2009-01-0668, SAE 2009 International Congress
     and Exposition, Detroit, Ml, April 20-23, 2009.

108. Abarham,  M., Hoard, J., Assanis,  D.N., Styles, D.,  Curtis,  E., Ramesh, N.,
     Sluder,  C.S., and  J, Storey, "Numerical   Modeling  and  Experimental
     Investigations of EGR Cooler Fouling in a  Diesel Engine," SAE Paper 2009-
     01-1506, SAE 2009 International Congress and Exposition, Detroit, Ml, April
     20-23, 2009.

109. Babajimopoulos,  A., Challa, P.V.S.S., Lavoie, G., and D.N. Assanis,  "Model-
     Based Assessment of Two Variable Cam Timing Strategies for  HCCI Engines:
     Recompression Vs. Rebreathing," ICES Paper 2009-76103, Proceedings of the
     ASME  Internal   Combustion   Engine Division  2009  Spring  Technical
     Conference ICES2009, Milwaukee, Wl, May 3-6, 2009.
                                                                   Assanis, 64

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110.  Martz, J.B.,  Kwak,  H.,  Im,  H.G.,  Lavoie,  G.A, Assanis,  D.N. and  S.B.
     Fiveland,  "Propagation of a Reacting Front in  an  Auto-Igniting Mixture",
     Proceedings of the 6th US  National Combustion Meeting, Ann Arbor, Ml,  May
     17-20,2009.

111.  Grannell, S., Assanis, D.N., Gillespie, D. and S.V. Bohac, "Exhaust Emissions
     from  a Stoichiometric, Ammonia and  Gasoline Dual  Fueled Spark  Ignition
     Engine,"  ICES2009-76131,  Proceedings of the ASME Internal  Combustion
     Engine Division 2009 Spring Technical Conference  ICES2009, Milwaukee,
     Wl, May 3-6, 2009.

112.  Ickes, A., Assanis D.N. and  S. Bohac, "Load Limits with Fuel  Effects  of a
     Premixed  Diesel Combustion Mode," SAE Paper 2009-01-1972, SAE 2009
     International Powertrains,  Fuels and Lubricants Meeting, Florence,  Italy,  June
     15-17,2009.

113.  Klinkert,  S., Hoard,  J.W., Sathasivam, S. R., Assanis, D.N., and S.V. Bohac,
     "Design of a  Flow Reactor for Testing Multi-Brick Catalysts Systems Using
     Rapid Exhaust Gas  Composition Switches," ASME  Paper ICEF2009-14016,
     Presented  as  ASME  Paper  ICEF  2009-14063,  ASME  ICE Division  Fall
     Technical  Conference, Lucerne, Switzerland, September 20-24, 2009.

114.  Keum, S., Im,  H.,  and D.N. Assanis, "Computational Investigation of the
     Effect of  Stratification   on  DI/HCCI  Engine Combustion  at  Low  Load
     Conditions,"  SAE  Paper  2009-01-2703,  2009  Powertrains,   Fuels  and
     Lubricants Meeting,  San Antonio, TX, November 2-4, 2009.

115.  Prucka,  R., Lee, T.-K.,  Filipi, Z,  and  D. Assanis,  "Turbulence Intensity
     Calculation from Cylinder  Pressure  Data in a High  Degree  of Freedom
     Engine," SAE 2010 World Congress, Detroit, Ml, April 13-15, 2010.

116.  Han, D., Ickes, A.M., Bohac,  S.V., Huang,  Z., Assanis, D.N., "Premixed Low-
     Temperature Combustion  of  Blends of Diesel and Gasoline in a High Speed
     Compression   Ignition  Engine,"  Proceedings,  33rd Int. Symposium  on
     Combustion, Bey ing, China, Aug 1-6, 2010.

117.  Martz, J.B., Kwak, H., Im, H.G., Lavoie, G.A., and D.N. Assanis, Combustion
     Regime of a  Reacting  Front  Propagating  into an  Auto-Igniting Mixture,
     Proceedings, 33rd Int.. Symposium on Combustion, Beijing, China, Aug 1-6,
     2010.

118.  Northrop,  W., Bohac, S., Assanis, D. and J.Y. Chin, "Comparison of Filter and
     Smoke Number  and Elemental Carbon Mass from  Partially  Premixed  Low
     Temperature Combustion  in  a Direct  Injection Diesel  Engine," ASME 2010
     Internal Combustion Engine Division Fall Technical Conference, San Antonio,
     TX, September 12-15, 2010.

119.  Smith, M., Filipi, Z.,  Schihl, P. and  D.N. Assanis, "Effect  of  High Sulfur
     Military JP-8  Fuel on Heavy Duty Diesel Engine Emissions and  EGR Cooler
     Condensate,"  ICEF2010-35001, ASME 2010 Internal Combustion Engine
     Division Fall Technical Conference, San Antonio, TX, September 12-15, 2010.

120.  Shingne,  P, Assanis, D.N., Babajimopoulos, A., Keller, P., Roth, D., Becker,
     M., "Turbocharger Matching  for a 4-Cylinder Gasoline HCCI  Engine Using a

                                                                   Assanis, 65

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     1D Engine Simulation,"  SAE Paper 2010-01-2143, SAE 2010 Powertrain,
     Fuels and Lubricants Meeting, San Diego, CA, October 25-27, 2010.

121. Delorme, A., Rousseau, A., Wallner, T., Babajimopoulos, A. and D.N. Assanis,
     "Evaluation  of Homogeneous Charge Compression Ignition (HCCI) Engine
     Fuel Savings for Various Electric Drive Powertrains," The 25th World Battery,
     Hybrid and Fuel Cell Electric Vehicle Symposium and Exhibition," Shenzhen,
     China, November 5-9, 2010.

122. Manofsky, L,  Vavra, J., Assanis, D.N., and A. Babajimopoulos, "Bridging the
     Gap between HCCI and SI: Spark-Assisted Compression Ignition," SAE Paper
     2011-01-1179, SAE 2011 World Congress, Detroit. Ml, April 12-14, 2011.

123. Northrop, W.,  Assanis, D.N. and S.  Bohac, "Evaluation of Diesel Oxidation
     Catalyst Conversion of Hydrocarbons and Particulate Matter from  Premixed
     Low Temperature Combustion of Biodiesel," SAE  Paper 2011-01-1186, SAE
     2011 World Congress, Detroit. Ml, April 12-14, 2011.
Other Conference or Symposium Presentations

1.    Assanis, D. N., J. A. Ekchian, J. B. Heywood, and K. K. Replogle, "Computer
     Simulation of the Turbocompound Diesel Engine System," Proceedings of the
     Society of Automotive Engineers, 22nd Automotive  Technology Development
     Contractor's Meeting, P-I55, 297-316, 1985.

2.    Assanis,  D.  N.,  and E.  Badillo,  "Unsteady Analysis  of  Piston-Liner Heat
     Transfer in Insulated  Diesel Engines," Invited Paper, Proceedings of the Heat
     Transfer Conference Honoring B. T. Chao, Urbana, IL, Oct.  1-2, 1987.

3.    Assanis, D.  N., Wiese,  K., Schwarz, E., and W.  Bryzik, "Investigation of the
     Effect of Thin Ceramic Coatings on Diesel Engine Performance and Exhaust
     Emissions," Proceedings  of the 1990  Coatings for Advanced Heat Engines
     Workshop, Castine, Maine, Aug. 6-10, 1990.

4.    Varnavas, C., and D. N. Assanis, "Critical Evaluation of the  KIVA Evaporation
     Model for Engine Spray Calculations," Third International KIVA Users Group
     Meeting,  Detroit, Ml, Feb. 28, 1993.

5.    Agarwal,  A.,  Papageorgakis,  G. C., Paul,  M.,  Rubas, P. J., Yuen,  L.  S.,
     Coverdill, R. E., Lucht,  R. P., Peters, J. E., and D. N.  Assanis, "Direct Injection
     of Natural Gas: In-Cylinder Measurements and Calculations,"  Proceedings of
     Annual Automotive  Technology  Development  Contractor's Coordination
     Meeting,  Society of  Automotive Engineers P-289,  147-156,  Dearborn, Ml,
     October 24-27, 1994.

6.    Assanis, D.  N., "A Methodology for Characterizing  the Thermal Behavior of
     Internal Combustion  Engine Systems", invited presentation, Proceedings of
     The Best of German/American Automotive Technology Conference, Southfield,
     Ml, June  27-28, 1995.

7.    Assanis, D.  N., "A Methodology for Characterizing  the Thermal Behavior of
     Internal  Combustion  Engine  Systems",  invited presentation,  Engineering
     Foundation Conference, Shonan Village, Japan, September 23-29, 1995.

                                                                   Assanis, 66

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8.    Papageorgakis,  G.,  Agarwal, A.,  and  D.  N.  Assanis,  "Multi-Dimensional
     Modeling of Natural Gas Injection, Glow Plug Ignition, and Combustion with
     the KIVA-3 Code: The Effect of Piston Crown Geometry," Sixth International
     KIVA Users Group Meeting, Detroit, Ml, Feb. 25, 1996.

9.    Papageorgakis,  G.,  Agarwal, A.,  and  D.  N.  Assanis,  "Multi-Dimensional
     Modeling of Natural Gas Injection, Glow Plug Ignition, and Combustion with
     the KIVA-3  Code, Poster Session,  Annual DOE Automotive  Technology
     Development Customers' Coordination Meeting, Dearborn, Ml, Oct. 28 - Nov.
     1,1996.

10.   Assanis,  D. N., "3-D  Modeling  of  Engine Reacting  Flows: Promises and
     Challenges,"  invited  paper,  Panel  on  Automotive Applications of  CFD,
     Atlanta,  1996 ASME  International  Mechanical  Engineering Congress and
     Exposition, Atlanta, GA, Nov. 17-22, 1996.

11.   Papageorgakis,  G., and  D. N. Assanis, "Implementation and Assessment  of
     Alternative Turbulence  Models in  KIVA-3,"  Seventh  International  KIVA
     Users Group Meeting,  Detroit, Ml, Feb. 25, 1996.

12.   Assanis,  D. N., "Engine  Friction  Measurements,"  invited presentation,  Panel
     on  Surface Engineering and  Tribology, SAE  International  Congress and
     Exposition, Detroit, Ml, Feb. 23-26, 1998.

13.   Assanis,  D. N., "Engine Friction Measurements,"  Keynote Presentation, DOE
     Workshop on   Research  Needs  for   Reducing  Friction  and  Wear   in
     Transportation,  Argonne National  Laboratory, March 22-23, 1999.

14.   Delagrammatikas,  G.  and D.N.  Assanis,   "Development  and  Use  of a
     Regenerative  Braking Model in  ADVISOR,"  ADVISOR  User Conference
     Proceedings, Costa Mesa, CA, Aug. 24-25, 2000.

15.   Assanis,  D.N., Louca, L, and Z. Filipi, "Drivetrain Simulation and Modeling
     Based Upshift  Control,"  Modern  Advances  in  Automatic Transmission
     Technology TPOTEC, Ypsilanti, Ml, Aug. 29-30, 2002.

16.   Assanis,   D.  N. and  S. Tung,  "Overview  of  Engine  Friction  and  Wear
     Measurements,"  Future  Trends  in Engine Design  and  Tribology, Society  of
     Tribologists and Lubrication Engineers, Rochester, Ml, August 22, 2001.

17.   Assanis,  D. N., "Modeling of Hybrid Vehicle Systems", invited presentation,
     7th  International Conference on Present and Future Engines for Automobiles,
     Delphi, Greece, May 27-31, 2001.

18.   Assanis,  D. N., "Discussion of the National  Research  Council  Report on
     Corporate Average Fuel  Economy," SAE President's Invited Panel, 2002 SAE
     International Congress and Exhibition,  2002 SAE World Congress,  Detroit,
     Ml, March 4-7, 2002.

19.   Fiveland, S.  and D.  N. Assanis,  "A Quasi-Dimensional  HCCI  Model  for
     Performance  and Emissions Studies,"  Ninth  International  Conference  on
     Numerical Combustion, Sorrento, Italy, April 7-10, 2002.
                                                                    Assanis, 67

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20.   Assanis,  D. N., "Does the  Internal Combustion  Engine Have a  Future?", The
     Advanced Power Technology Forum, Management Briefing Seminars 2002,
     Traverse City, Ml, August 5-9, 2002.

21.   Assanis  D.  N.,  "Does the Internal Combustion Engine  Have a  Future?",
     invited plenary speaker, session  on  "Future Automotive Powertrains," Global
     Powertrain Congress, Ann Arbor, Ml, September 24-26, 2002.

22.   Assanis,  D.N.,  "Securing  a Successful  Academic Career,"  invited  panelist,
     ASME IMECE, New Orleans, LA, November 17-22, 2002.

23.   Bohac,  S.,  Assanis,  D.N.,  and  H.L.S  Holmes, "Speciated  Hydrocarbon
     Emissions from a Contemporary Automotive  Gasoline Engine and  Local
     Ozone Production," Anachem Symposium, Livonia, Ml, November 21, 2002.

24.   Filipi, Z. S., Wu, B., Lin, C.C., and D. N. Assanis, "Fuel Economy Potential of
     Hydraulic Hybrid Propulsion Systems for Medium Trucks," SAE International
     Truck and Bus Meeting and Exhibition,  Cobo Center, Detroit, Ml, November
     18-20, 2002.

25.   Assanis.  D.N., "Internal Combustion Engines and Hybrids: They are Here to
     Stay,"  Testimony to  State of  Michigan's  Senate  Technology and Policy
     Committee," Farnum Building, Lansing, Ml, February 19,  2003.

26.   Assanis,   D.N.,   "A  University  Consortium   on  Homogeneous  Charge
     Compression   Ignition  Engine  Research,"  invited  speaker,   International
     Workshop  on   Advanced  Combustion  and   Fuels,"   Argonne   National
     Laboratory, Argonne, IL, June 16-17, 2003.

27.   Assanis,  D.N.,  "Major  Research   Issues,"  invited  panelist,   International
     Workshop  on   Advanced  Combustion  and   Fuels,"   Argonne   National
     Laboratory, Argonne, IL, June 16-17, 2003.

28.   Vanzieleghem, B.P.,  Chryssakis, C.A., Grover, R.O., Assanis, D.N.,  Im, H.G.,
     and V. Sick, "Gasoline Direct Injection Modeling and Validation with Engine
     Planar   Laser   Induced   Fluorescence   Experiments,"   14th   International
     Multidimensional Engine Modeling User's Group Meeting, Detroit, Ml, March
     2004.

29.   Depcik, C., and  D.N. Assanis, "One-Dimensional Catalyst Modeling and  its
     Application  to  Urea SCR  Devices," Seventh  CLEERS Workshop,  Detroit
     Diesel, Detroit, Ml, June 2004.

30.   Assanis,  D.N., et al., "Clean and  Controllable, Advanced Compression Ignition
     Engine  System for  Improved Power Density and Fuel   Economy", plenary
     session presentation  at the Annual ARC Conference on "Critical Technologies
     for Modeling  and Simulation of Ground Vehicles", Ann Arbor, May 2004.

31.   Babajimopoulos, A.,   Assanis,  D.N.,  Flowers, D.L., Aceves, S.M.,  and R.P.
     Hessel,  "A  Fully Integrated  CFD  and  Multi-Zone  Model with   Detailed
     Chemical Kinetics for the Simulation of PCCI Engines," 15th International
     Multidimensional Engine Modeling  User's Group Meeting, Detroit, Ml, April
     2005.
                                                                   Assanis, 68

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32.   Assanis, et al., "Engine-ln-the-Loop Simulation: A Design and Evaluation Tool
     for Advanced Propulsion Systems", plenary session presentation at the Annual
     ARC Conference on "Critical Technologies for Modeling and Simulation of
     Ground Vehicles", Ann Arbor, May 2005.

33.   Assanis,  D.  N., "Bridging the  Gap  between  Fundamental  Physics  and
     Chemistry and  Applied Models for HCCI  Engines", invited presentation, 9th
     International Conference on Present and Future Engines for Automobiles, San
     Antonio, TX, May 29 to June 2, 2005.

34.   Assanis,  D.  N., "Bridging the  Gap  between  Fundamental  Physics  and
     Chemistry and  Applied  Models for HCCI Engines", invited presentation, 11th
     International Conference on Diesel Engine Emissions Reduction DEER 2005,
     Chicago, IL, August 21 -25, 2005.

35.   Leustek, M.E., Sethu, C., Bohac, S.,  Filipi, Z., and D.N. Assanis, "Crank-angle
     Resolved  In-Cylinder Friction Measurements with the Instantaneous  IMEP
     Method", Proceedings  of World Tribology Congress  III, Washington D.C.,
     Sept. 2005.

36.   Assanis, D.N.,  et al., "Integrative Approach to Advanced Propulsion System
     Design   Using   Simulation  and   Engine-ln-the-Loop",  plenary  session
     presentation at the  Annual ARC Conference on "Critical Technologies for
     Modeling and Simulation of Ground Vehicles", Ann Arbor, May 2006.

37.   Assanis, D. N., "Low Temperature Combustion for High Efficiency Ultra Low
     Emissions  Engines",  invited  presentation, 12th  International Conference  on
     Diesel Engine Efficiency and Emissions Reduction DEER 2006, Detroit, Ml,
     August 20-24, 2006.

38.   Assanis, D. N.,  "Analysis  and Control  of HCCI  Engine  Transient Operation
     Using 1-D Cycle Simulation and  Thermal  Networks", invited presentation,
     SAE  HCCI Engine Symposium, San Ramon, CA, September 24-26, 2006.

39.   Assanis, D. N., "Next Generation  Powertrains and Fuels: Grand Challenges
     and Opportunities",  invited  presentation, UM Symposium on Energy Science,
     Technology and Policy, Ann Arbor, Ml, February 13-14, 2007.

40.   Assanis, D.N.,  "Energy Research: Grand  Challenges and  Opportunities,"
     invited talk, Lehigh University, Bethlehem, PA, February 2, 2007.

41.   Assanis, D.N.,  "Today's Students, Tomorrow's Engineers," invited panelist,
     SAE  2007 World Congress,  Detroit, Ml, April 16-19, 2007.

42.   Assanis, D.N.,  et al, "Energy and Power for Military Vehicles:  Alternative
     Fuels and Hybrid Propulsion", plenary session presentation at the Annual ARC
     Conference on "Critical  Technologies for Modeling and Simulation of Ground
     Vehicles", Ann Arbor, May 2007.

43.   Assanis, D. N., "On  Modeling  HCCI  Engine Transient  Behavior",  invited
     presentation, 10th International Conference on Present and Future Engines for
     Automobiles,  Rhodes, Greece, May 28 to June 5, 2007.
                                                                    Assanis, 69

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44.   Assanis, D.N., "TechKnow:  Alternative Fuel Cars,"  invited  panelist, Power
     Center, Ann Arbor, Ml, June 12, 2007.

45.   Assanis, D.N., "Analysis and  Control of HCCI Engine Transient Operation",
     invited  presentation,  Homogeneous Charge Compression Ignition  (HCCI)
     Symposium, Lund, Sweden, September 12-14, 2007.

46.   Assanis. D.N., "Low Temperature Combustion for High Efficiency, Ultra-Low
     Emission Engines"  invited talk, University of Illinois at Urbana-Champaign,
     April 1, 2008.

47.   Middleton, R. and D. N. Assanis, "Nitrogen Oxides Oxidation as a Function of
     Lean NO Trap Loading," 11th DOE Crosscut Workshop on Lean Emissions
     Reduction Simulation, University of Michigan - Dearborn, May 13-15, 2008.

48.   Assanis, D.N., in  collaboration with  G.  Lavoie  and  A. Babajimopoulos,
     "Advanced Combustion for High Efficiency Ultra-Clean  Engines," Keynote
     Lecture, 6th US National Combustion  Meeting, Ann Arbor, Ml, May 17-20,
     2009.

49.   Assanis,  D.N.,  Invited Panelist  on  "Secure,  Low-Carbon  Transportation
     System," Workshop on Formulation  of A  Bipartisan  Energy and  Climate
     Policy: Toward an Open and  Transparent Process, The  Howard H. Baker Jr.
     Center  for Public Policy and the  Widrow  Wilson International  Center for
     Scholars, Washington, DC, June 18-19, 2009.

50.   Assanis, D.N.,  "On the Road to Clean and  Efficient  Powertrains,"  invited
     presentation,  UMTRI  Symposium  on  Powertrain Strategies  for  the  21st
     Century:  How Are New Regulations  Affecting Company Strategies?", Ann
     Arbor, Ml, July 15, 2009.

51.   Assanis, D.N., Invited Panelist on "Future Transportation and Energy  Policy,"
     5th International IEEE  Vehicle Power and Propulsion Conference VPPC 2009,
     Dearborn Ml, September 10, 2009.

52.   Assanis, D.N.,  Invited Keynote Speaker, "Advanced Combustion for High
     Efficiency Ultra Clean  Engines," American Filtration  Society, 4th Biennial
     Conference on Emission Solutions in Transportation, Ann Arbor, Ml,  October
     5-8,  2009.

53.   Assanis, D.N.,  Invited Keynoter for  Opening Ceremony,  "The Business of
     Plugging-ln", Motorcity Hotel  and Conference Center, October 19-21, 2009.

54.   Assanis, D.N,  Invited Panelist on "High Efficiency 1C  Engines," SAE 2009
     Powertrains, Fuels and Lubricants Meeting, San Antonio, TX, November 2-4,
     2009.

55.   Assanis, D.N., Invited  Panelist on Alternative Energy Sources,  "Meeting the
     Energy Challenge: The Role of Biofuels in Solving Society's Largest Problem
     in the  21st Century",  Energy for the Future  Conference,  University  of
     Dearborn, Ml,  March 16, 2010

56.   Assanis, D.N,  Invited  Panelist on "Pathways to High Efficiency 1C Engines,"
     SAE 2010 World Congress,  Detroit, Ml, April 13-15, 2010.

                                                                    Assanis, 70

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57.   Assanis D.N., Invited Speaker, "Assessing Great Lakes Offshore Wind:  A
     Partnership  between the University  of Michigan  and  Grand  Valley  State
     University," University  of  Michigan  Regents'  Meeting,  Grand Rapids, Ml,
     April 15, 2010.

58.   Assanis,  D.N.,  Ortiz-Soto,  E., Babajimopoulos, A., and G.  Lavoie, "Dual-
     Mode  SI-HCCI  Operation  for  Improved  Drive-Cycle  Fuel  Economy:
     Engine Modeling and Map Generation Framework,"  Invited  presentation  to
     USCAR, Southfield. Ml, May 12, 2010.

59.   Assanis,  D. N., "The  Road  to  Clean Vehicles,"  invited  lecture,  Zhejiang
     Automotive Institute, Hangzhou, China, May 29, 2010.

60.   Assanis, D.N, Invited Speaker on "Pathways to High Efficiency I.C. Engines,"
     11th International Conference on Present and Future  Engines for Automobiles,
     Shanghai, China, May 30-June 3, 2010.

61.   Assanis, D.N., Invited Plenary Speaker, "Towards Carbon Neutral Vehicles,"
     Emissions 2010, Ann Arbor, Ml, June  14-16, 2010.

62.   Assanis, D.N., "A University Consortium on High Pressure  Lean Combustion
     for  Efficient  and  Clean   Internal Combustion  Engines," 16th  Directions
     in Engine-Efficiency and Emissions Research (DEER)  Conference, September
     27-30, 2010, Detroit, Michigan.

63.   Assanis,  D.N., Invited  Speaker,  "Thermodynamic Lessons  Learned  from
     Lean/Dilute Burn Diesels  to  Improve Gasoline Engine  Efficiency," invited
     presentation,  Cummins  Science  and  Technology Council Advisory  Board
     Meeting, Columbus, IN,  October 6-8, 2010.

64.   Assanis, D.N., Invited Speaker, "U.S.-China Clean Energy Research Center for
     Clean  Vehicles",  UMTRI  Focus  on  the Future  Automotive Research
     Conferences, Inside China:   Understanding China's  Current  and Future
     Automotive Industry, The University of Michigan  League, Ann  Arbor, Ml,
     November 10, 2010.

65.   Assanis,  D.N.,  Invited  Panelist,  Erb  Institute Conference,  "Michigan-China
     Clean Tech:  Collaboration and  Competition in Energy, Smart Grid,  Green
     Cities and Transportation," The University of Michigan Union, December 10,
     2010.
Books Edited

       Uzkan,  T., and Assanis, D. N., Editors, "Advanced Engine Simulations,
       Volume  1,  Proceedings   of  the  1997  ASME-ICE  Spring   Technical
       Conference, ICE-Vol. 28-1, ASME, 1997.

       Assanis, D.N., Papalambros, P.Y., and Bryzik, W., Guest Editors, Haug, E.,
       Editor, Automotive Research  Center Special Edition Issue, Mechanics  of
       Structures and Machines, 27:4, 1999.
                                                                    Assanis, 71

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       Zhao, F., Asmus. T., Assanis, D. N., Dec. J. E., Eng, J. A., and P. M. Najt,
       Homogeneous Charge Compression Ignition (HCCI) Engines: Key Research
       and Development Issues,  SAE PT-94, Society of  Automotive Engineers,
       Warrendale, PA, 2003.

       Assanis,  D.N.,  Bryzik, W.,  Gorsich. D., and Haque,  I.,  Guest Editors,
       Automotive Research Center Special Edition Issue, International Journal of
       Heavy Vehicle Systems, 11:3/4, 372-402, 2004.

       Cheng, W.K., Dibble,  R., and  D.N.  Assanis,  Guest Editors,  International
       Journal of Engine Research, Special Issue on HCCI Engines, 6:5, 2005.
Chapters in Books
       Assanis,  D.N.,  Borgnakke,  C., Patterson, D.J., and  Cole,  D.,   "Internal
       Combustion   Engines,"  Marks'  Standard  Handbook  for  Mechanical
       Engineers, pp. 9-90 to 9-121,  10th Edition, McGraw-Hill  Book Company,
       1996.

        Assanis, D.N., Lavoie, G. A. and S.  B. Fiveland, "HCCI Engine Modeling
       Approaches," pp. 529-655, published  in Homogeneous Charge Compression
       Ignition (HCCI) Engines: Key Research and Development Issues, SAE PT-
       94, Society of Automotive Engineers, Warrendale, PA, 2003.

       Assanis,  D.N.,  Cole,  D.,  Jacobs,  T.J.,  and  D.J.  Patterson,    "Internal
       Combustion   Engines,"  Marks'  Standard  Handbook  for  Mechanical
       Engineers, pp. 9-93 to 9-127, 11th Edition, McGraw-Hill  Book Company,
       2007.

       Chryssakis, A., Assanis, D.N.  and  F.X. Tanner, "Atomization Models,"
       Handbook of Atomization and Sprays: Theory  and Applications, Springer,
       2011.
Reports
       Assanis, D. N., "A Study of the Heat Transfer, Combustion and Emissions
       Characteristics of Low-Heat Rejection  Diesel Engines," U.S. Army Tank-
       Automotive  Command  Research,  Development  and  Engineering Center
       Technical Report No. 13589, June 1991.

       Poola, R. B., Sekar, R., and D.N. Assanis, "Application of Oxygen-Enriched
       Combustion   for  Locomotive   Engines,  Phase  I,"  Argonne   National
       Laboratory Report ANL/ESD/TM-135, September 1996.

       National  Academy  of Sciences Committee  to  Assess Fuel  Economy
       Technologies for  Medium- and Heavy-Duty Vehicles; National  Research
       Council; Transportation Research Board,  "Technologies and Approaches to
       Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles,"
       Washington,  DC,  The National  Academies  Press,  September  2010.
                                                                   Assanis, 72

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       Available electronically from the National Academies Press Web site at
       http://www.nap. edu/catalog.php ?record_id=12845

       President's Council  of Advisors on  Science and  Technology  (PCAST)
       Working Group on  Energy Technology  Innovation System, "Report to the
       President  on  Accelerating  the  Pace of Change  in  Energy Technologies
       through an Integrated Federal Energy Policy," November 2010.
Inventions and Patents

       Church, C., Smith, F., and D.N. Assanis, "Use of Singlet Delta Oxygen to
       Enhance the Performance of Internal Combustion Engines, Diesel Engines in
       Particular," Patent No. 6,659,088, granted 12/9/2003.

       Wu, B., Filipi, Z., Assanis,  D.N., Kramer, D.,  Ohl, G., Prucka, M., and E.
       DiValentin, "Artificial Neural Networks for Estimating the Air Flow Rate
       through a VVT  Engine", Invention Development Record P706964 disclosed
       04/21/2004.  Filed by ajoint team of DM and OCX researchers.

       Shih, A.J., Filipi, Z., and D.N. Assanis, "Pre-Turbocharging Catalyzed Porous
       Metal Foam  Filter for Diesel Particulates Treatment", Invention Disclosure No.
       2924 to UM  Tech Transfer Office, July 2004.

       Najt, P.M., Eng, J.A., Chang, J., Filipi, Z.S., Guralp, 0., and D.N. Assanis,
       "Method for Mid-Load Operation of Auto-Ignition Combustion," Patent No.
       7,128,062  B2, granted 10/31/2006.

       Kuo, T.W., Najt, P., Eng, J.A., Rask, R.B., Guralp, 0., Hoffman, M., Filipi, Z.S.,
       and D.N. Assanis, "Method and Apparatus to Determine Magnitude of
       Combustion  Chamber Deposits," Patent No. 7,367,319, granted 12/31/2007.

       Najt, P., Kuo, T.W., Rask, R., Babajimopoulos, A., Filipi, Z.S.., Lavoie, G., and
       D. N. Assanis, "Hybrid Powertrain System Using Free Piston  Linear Alternator
       Engines,"  Utility patent application, US serial no. 12/504,502, filed July 16,
       2009.
                                                                     Assanis, 73

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Scott T. McBrodm, P.E.

1915 Great Ridge St.
San Antonio, TX 78248
(210) 240-7123 (m)
(210)492-4116 (h)
Email: scott.mcbroom@sbcglobal.net
OBJECTIVE
PROFESSIONAL
SUMMARY
EXPERIENCE
  To obtain  a management position  within an  innovative/entrepreneurial engineering
  company.

  Experience with successfully managing all aspects of an advanced  vehicle  powertrain
  research and development activity. I  have 7 years management experience and a total
  17 years in vehicle research development.  Responsibilities have included;  personnel,
  cash  flow, marketing,  engineering,  contracting,  strategic planning,  client  relations,
  proposal writing, technical writing, presentations and  significant  travel. I believe my
  experience has been equivalent to  founding  and managing a  small  research and
  development business, which I lead from an initial staffing of 5 to 14 in 4 years,

  Southwest  Research  Institute -  Manager  of Advanced  Vehicle Technology
  (www.avt.swrl.org). San Antonio, TX, May 1998 - present
  •   Manage a staff of 13 engineers (2 PhD's, 6 MS's and  5 BS's),  with annual gross
     revenues  averaging $2.7M with a client portfolio of US Gov, US commercial, and
     foreign commercial clients, and a technology portfolio that includes; test systems,
     hybrid electric vehicles,  hybrid hydraulic vehicles, software  development, fuel cell
     systems, automated manual transmissions and electrification of engine accessories.
 •   Spearheaded the  development of a commercial-of-the-shelf software package  to
     simulate  vehicle performance and fuel economy (RAPTOR).   RAPTOR is now
     licensed by DaimlerChrysler,  U.S. Army, AND Technologies, FAW Corporation and
     Denso. (www.raptor.swri.orQ)

 Southwest Research Institute - Senior Research Engineer, San Antonio, TX, 1996 -
 1998
 •   Developed software simulation tools to model vehicle performance,  emissions and
    fuel economy for the  Partnership  for  a New  Generation Vehicle's (PNGV) 80-mpg
    car. Sponsored by Ford, GM and Chrysler.
 •  Powertrain Systems Analysis for the U.S. Army National Automotive Center's Future
    Truck program to improve the efficiency, safety and emissions of trucks in the US.

 Southwest Research  Institute - Research Engineer, San Antonio, TX, 1991  -1996
 •  Conducted evaluation,  simulation,  design, and integration of electric,  hybrid-electric,
    and solar-powered vehicles.
 •  Championed an internal research  project for modeling the performance, emissions,
    and efficiency of conventional, hybrid and electric vehicles, which has since led  to
    over$9M of client funded simulation projects.

 Southwest Research Institute -Engineer, San Antonio, TX, 1988 - 1991
 *   Developed a retractable, compressible fluid, suspension system for an amphibious
    military vehicle.
 •   Designed and developed a regenerative active suspension system  for a tour bus
 •   Reduced  to practice  a patented  pump/motor for regenerative active suspension
    systems.
•   Performed stability  testing and failure analysis of an electro-hydraulic control valves.
•   Designed and tested an air cycle refrigeration system.

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Scott T. McBroom, P.E.
EDUCATION
SKILLS
ACTIVITIES &
AWARDS
Professional
Affiliations

Professional
Development
                  Bachelor of Science in Mechanical Engineering, May 1988
                  The University of Maryland, College Park, Maryland

                  Master of Science In Mechanical Engineering, May 1998
                  The University of Texas at San Antonio, San Antonio, Texas

                  MATLAB/SimuLINK, Microsoft Office, Fluent in French, Cost Point, Project Management,
                  Proposal Writing, Personnel Management, Public Speaking

                  Professional
                     »   Recognized by the San  Antonio  Business  Journal as  one of the top 40
                         individuals under 40 yrs old in the San Antonio business community - 2004
                     «   Society of Automotive Engineers Outstanding Younger Member - South Texas
                         Section 1 994-95
                     «   R & D Magazine 2004 R&D 100 Award for RAPTOR software (for the 100 most
                         significant innovations)
                        and '99
                 Personal
                     «   Alamo Heights United Methodist Church {Production Team, Hospitality Team,
                        Fishing Under the Bridge Team, and Alpha)
                     •   Bonneville Salt  Flats  Racing  Association - Land Speed Record for Electric
                        Vehicles Under 500kg {101.3 mph)~ ( 1994)
                     •   Fourth place out of 16 in the first Solar and Electric 500 at Phoenix International
                        Raceway and first place for hybrid electrics the second year. (1991)
                     •   Completed the San Antonio, Austin and Columbus Marathons
                     •   NEISD - Mentor for High School Students interested in Engineering Careers

                 Society of Automotive Engineers (member since 1 986, Past  Chair South Texas Section)
                 Registered Professional Engineer, State of Texas

                 Lean Six Sigma
                 Family Medical Leave Act Overview
                 Government Property Administration
                 Supervisory Management: Managing A Drug-Free Workplace
                 Time Management
                 Sexual Harassment Prevention And Resolution
                 Coaching For Improved Performance
                 SwRl Manager Support Briefings
                 Care-Employee Assistance Program
                 Fundamental Skills Of Managing People
                 Establishing Performance Expectations
                 Fundamental Skills Of Communicating With People
                 Getting Employee Commitment To The Plan
                 Project Financial Management Methods
                 Topics In Statistics 6: Methodologies For Fitting A Curve To  Data
                 Successful Cost Estimating Methods
                 Statistical Design Of industrial Experiments
                 Proposal Preparation
                 Undergraduate Mathematics Review : Partial Differential Eqn's
                 Research Program Development
                 State Variable Modeling Of Linear Systems

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Scott T. McBroom, P.E.
Publications      "The 1989 Formula SAE Student Design Competition," with L. Bendele, E. Bass, Society
                  of Automotive Engineers, International Congress  and  Exposition, SAE  Paper 900840,
                  Detroit, Ml, February 1990.

                  "System Tradeoffs - Design of Hybrid Electric Vehicles," with D. Mairet, J. Buckingham,
                  E. Bass, ESD Technology, November 1994.

                  "PNGV Goal 3 Systems Analysis Toolkit," with K. Hardy, A. Sabharwal, Partnership for a
                  New Generation of Vehicles Simulation Technology Design Team, August 1996.

                  "Analysis and Design of a  Propane Gas/Electric  Parallel Hybrid Vehicle,"  Masters Thesis
                  for College of Sciences and Engineering, University of Texas at San Antonio, December
                  1998.

                  "Analysis  for  a  Four-Wheel  Propane-Electric Parallel Hybrid Vehicle,"  Society  of
                  Automotive Engineers, Future Transportation Technology Conference, SAE Paper No.
                  1.999-01-2907, Costa Mesa, CA, August 1999.

                  "Modeling  Future Automobiles: The Role of Industry and Government," co-authored with
                  Larry Turner,  Robert  Larsen, Michael  Duoba, Ashok Nedungadi, and Keith  Wipke.
                  COMPEL:  The International Journal for Computation and Mathematics in Electrical and
                  Electronic Engineering  Volume 19, No. 4, 2000, Pp. 1036-1044.

                  "Class  2B  - Light Duty Trucks and the 21st Century Truck Initiative," Clean SUV and
                  Light Truck SAE TOPTEC, Dearborn, Ml, June 2000.

                  "The 21st  Century Truck  -  Comparing  Various Efficiencies  and Emissions  Using
                  Simulation-Based  Parametric  Analysis," Presented at  Hybrid Vehicles 2000, Windsor,
                  Canada, September 2000.

                 "A Parallel Hybrid System for Class IV Truck,"  presented at EnV 2001, sponsored  by
                  Engineering Society of  Detroit  in Detroit, Ml, June 2001.

                 "Hybrid Power Trains for Future Tactical Wheeled Vehicles," Presented at Hybrid Electric
                 Truck Users Forum (H-TUF), sponsored by WestStart in Indianapolis, IN, January 2002.

                 "Hybrid Technology Overview," Presented at Hybrid Electric Truck Users Forum  (H-
                 TUF), sponsored by WestStart in Indianapolis, IN, January 2002.

                 "A New Approach to Improving  Fuel Economy and  Performance  Prediction Through
                 coupled Thermal  Systems Simulation," 2002 SAE Congress Paper No.  2002-01-1208,
                 Presented  at SAE 2002 Word  Congress & Exhibition, March  20O2, Co-Authors Joe
                 Steiber and Angela  Trader of  SwRI, Alan Berry and Martin  Blissett  of  Flowmaster
                 International Ltd.

                 "Roadmap  for Hybridization of Military Tactical  Vehicles:  How Can We Get There?",
                 Presented  at  International  Truck  and Bus Meeting and  Exhibition in  Detroit, Ml  on
                 November 18-20, 2002. SAE Paper No. 2002-01-3048

                 "System Analysis  of the Effects of Hybridization on  the Family  of  Medium  Tactical
                 Vehicles," presented  at Hybrid Truck  Users Forum in San Antonio, Texas  on October
                 2003.

                 "The  Impact of Hybridization on Engine Life: A Qualitative Assessment", presented as  an
                 oral only paper at the 2005 SAE Powertrain and Lubrication Conference, San Antonio,
                 TX October 2005.

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                                         CURRICULUM VITAE
                                  SHAWN W. MIDLAM-MOHLER, PH.D.
                                          3938NorbrookDr.
                                        Columbus, Ohio 43220
                                            (614)307-4176
                                       midlam-mohler. l@osu.edu
EDUCATION
                                        Engineering Education

Ph.D.           Mechanical Engineering                                                        6/2005
                The Ohio State University                Columbus, OH
                Dissertation Title: "Modeling, Control, and Diagnosis of a Diesel Lean NOX Trap Catalyst"

M.S.            Mechanical Engineering                                                        3/2001
                The Ohio State University                Columbus, OH
                Thesis Title:  "A Novel Fuel-Operated Heater for Automotive Thermal Management"

B.S.            Mechanical Engineering                 Summa cum Laude                      6/1999
                Wright State University                  Dayton, OH
                Senior Design Project: "Aerodynamic Design and Simulation of a Wind-Turbine"

                                        Academic Fellowships

Graduate Automotive Technology Education Program - Ph.D. Studies         Source: Dept. of Energy
      • Awarded to select graduate students conducting research supporting DOE goals for transportation research

University Fellowship - M.S. Studies                                      Source: Ohio State University
      • Awarded in a university-wide search to attract high-caliber graduate students


RESEARCH    I
EXPERIENCE  I	


                                       Research Appointments

Research Scientist                                                             10/2008 to present
Ohio State University Center for Automotive Research,  Columbus,  OH
      •   Conduct research in the area of clean and efficient transportation, including emissions reduction, Diesel
          engines, alternative  combustion, hydrogen generation, heavy fuel atomization, and advanced powertrains
      •   Directed and advised graduate students in this area of research


Senior Research Associate                                                      11/2005 to 9/2008
Ohio State University Center for Automotive Research,  Columbus,  OH
      •   Conducted research in the area of clean and efficient transportation
      •   Directed and advised graduate students in this area of research

Research Associate II                                                           2/2004 to 10/2005
Ohio State University Center for Automotive Research,  Columbus,
      •   Conducted research in the area of clean and efficient transportation
S.Midlam-MohlerC.V.                                                                      Page  1

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Research Intern                                                                 6/2003 to 9/2003
Ford Scientific Research Labs, Dearborn, MI
      •   Conducted research on emissions reductions for gasoline hybrid-electric vehicles
      •   Three-month assignment resulted in three Ford invention disclosures and two U.S. patents
Projects as PI / Co-Pi:

$1,800,000/3 years


$50,000/1 years


$40,000/0.5 years


$144,500/3 year


$2,000,000/3 years1


$943,108/4 years


$724,531/3 years


 $234,760/2 years


$673,550/3 years
                                           Research Funding
Title: Systems Level Development for Engine Thermal Management   Start: 10/2010
Source: DOE via Chrysler subcontract

Title: Analysis of Secondary Powertrain Systems in HEVs
Source: CAR Industrial Consortium

Title: Life Cycle Analysis of Landfill Derived Natural Gas
Source: FirmGreen

Title: Fleet Studies of Plug-In Electric Hybrid Vehicles
Source:  SMART@CAR Consortium

Title: EcoCAR Challenge Hybrid Electric Vehicle Project
Source: US Department of Energy and numerous other sponsors

Title: Coordinated Diesel Engine and Aftertreatment Control
Source: Cummins

Title: Hierarchical Approach to Engine Modeling
Source: General Motors

Title: Soot Filter Regeneration though External Heat Addition
Source: Tenneco Automotive

Title: On-Board Fuel Reformation for Diesel Aftertreatment
Source: Tenneco Automotive
Projects with Major Research Role (not co-PD:
$940,863/4 years


$1,327,954/5 years
Title: Next Generation Charge Estimation for 1C Engines
Source: General Motors

Title: Next Generation APR Control for 1C Engines
Source: General Motors
Role: co-Pi

Start: 10/2010
Role: PI

Start: 4/2009
Role: PI

Start: 1/2009
Role: PI

Start: 6/2008
Role: Co-Pi

Start: 4/2008
Role: PI

Start: 4/2007
Role: Co-Pi

Start: 11/2005
Role: Co-Pi

Start: 11/2005
Role: Co-Pi
Start: 7/2004
Role: Researcher

Start: 7/2004
Role: Researcher
1 This is the estimated cost of the research conducted under this problem if funded from an external sponsor. This
project is heavily leveraged by the Department of Energy, General Motors, Ohio State University, and a number of
other sponsors through in-kind contributions as well as direct funding and fellowships.
S.Midlam-MohlerC.V.
                                                                        Page 2

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TEACHING
EXPERIENCE
                                       Instructional Appointments
Adjunct Assistant Professor                                                             7/2009 to present
Ohio State University Department of Mechanical Engineering, Columbus, OH
      •   Granted in recognition of significant educational service to the Mechanical Engineering Department
      •   Service includes one-on-one student advising, student project advising, and supervision of undergraduate
          research

Instructor                                                                             4/2007 to present
Ohio State University Department of Mechanical Engineering, Columbus, OH
      •   Sole instructor of record for two applied thermal and fluids courses on internal combustion engines
                                          Course Development

ME 631 - Powertrain Laboratory (3 CR)                                                          1/2009
Ohio State University Department of Mechanical Engineering, Columbus, OH
      •   Developed course material for two quarter hours of classroom lecture which reinforced lab work
      •   Developed eight new lab experiments based on in-depth knowledge of the automotive industry
      •   Facilitated donation of a gasoline engine from General Motors and a Diesel engine from Cummins, both
          with a calibration system to provide students access to cutting-edge equipment

ME 730 - Internal Combustion Engine Modeling (3 CR)                                            4/2007
Ohio State University Department of Mechanical Engineering, Columbus, OH
      •   Developed all new lecture material to bring in personnel research experience
      •   Developed new homework assignments to better engage students by building a fully functioning engine
          model in stages of greater fidelity and complexity
      •   Facilitated the donation of industry-standard engine simulation software for use by students
      •   Developed capstone project which allowed students to become engaged in a topic of interest

Seminar - Alternative Fuels Short Course                                                         1/2007
Ohio State University Center for Automotive Research Distance Education Program
      •   Developed 10 hours of lecture and lecture notes for industrial distance education program
      •   Provided case studies of alternative-fueled vehicles to reinforce concepts for the industry audience

                                          Teaching Experience

ME 631 - Powertrain Laboratory (3 CR)                    Sole Instructor of Record                  1/2011
Overall Teaching Rating: 5.0/5.0                           Class Size: 16

ME 631 - Powertrain Laboratory (3 CR)                    Sole Instructor of Record                  1/2010
Overall Teaching Rating: 5.0/5.0                           Class Size: 15

ME 730 - Internal Combustion Engine Modeling (3 CR)      Sole Instructor of Record                  4/2009
Overall Teaching Rating: 4.4/5.0                           Class Size: 7

ME 631 - Powertrain Laboratory (3 CR)                    Sole Instructor of Record                  1/2009
Overall Teaching Rating: 4.8/5.0                           Class Size: 12

ME 730 - Internal Combustion Engine Modeling (3 CR)      Sole Instructor of Record                  4/2007
Overall Teaching Rating: 4.5/5.0                           Class Size: 8
S.Midlam-MohlerC.V.                                                                         Page  3

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                                         Academic Advising
Since 2005, Dr. Midlam-Mohler has become increasingly involved in student advising.  He has served in an
advisory or supervisory capacity to the following students at the M.S. and Ph.D. level:
                          Student
                          Quiming Gong
                          Bernhard Grimm
                          John Davis
                          Jason Meyer
                          Katherine Bovee
                          John Davis
                          Ryan Everett
                          Kenny Pollen
                          Beth Bezaire
                          Brad Cooley
                          Chris Hoops
                          Ming Fang
                          Chris Hoops
                          Rajaram Maringanti
                          Joshua Supplee
                          Adalbert Wolany
                          Sai Rajagopalan
                          Sergio Hernandez
                          Andrea Pezzini
                          Patrick Rebechi
                          Rhisee Bhatt
                          Simone Bernasconi
                          Josh Cowgill
                          Kenny Pollen
                          Courtney Coburn
                          Adam Vosz
                          Eric Snyder
Role
Research Supervisor
Research Supervisor
Co-Advisor
Research Supervisor
Acting Advisor
Acting Advisor
Acting Advisor
Research Supervisor
Acting Advisor
Acting Advisor
Acting Advisor
Acting Advisor
Acting Advisor
Acting Advisor
Acting Advisor
Supervisor
Committee Member
Acting co-advisor
Supervisor
Supervisor
Acting co-advisor
Supervisor
Acting co-advisor
Acting co-advisor
Acting Advisor
Acting Advisor
Acting co-advisor
   Graduation Date or
Expected Graduation Date
          2012
          2010
          2011
          2011
          2010
          2010
          2010
          2010
          2010
          2010
          2010
          2009
          2009
          2009
          2009
          2009
          2009
          2008
          2008
          2008
          2007
          2007
          2007
          2007
          2006
          2006
          2005
                              Undergraduate Student Research Assistants:

Dr. Midlam-Mohler has supervised the following students on research outside of a formal degree program:
                          Student
                          Abbey Underwood
                          Sarah Jadwin
                          Andrew Arnold
                          John Macauley
                          Alixandra Keil
                          Jennifer Loy
Role
Supervisor
Supervisor
Supervisor
Supervisor
Supervisor
Supervisor
          Year
          2010
          2010
        2009-2010
         2009-10
         2009-10
         2009-10
S. Midlam-Mohler C.V.
                                          Page  4

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B.S.                      SeanEwing                Supervisor                         2009
B.S.                      David Griffin              Supervisor                         2009
B.S.                      Ross Wang                Supervisor                         2009
B.S.                      Orlando Inoa               Supervisor                       2008-09
B.S.                      Al Godfrey                Supervisor                       2008-09
B.S.                      JohnLutz                  Supervisor                         2008
B.S.                      KonradSvzed              Supervisor                         2008
B.S.                      Joshua Supplee             Supervisor                         2007

                                Mentor for Local High School Students

Dr. Midlam-Mohler has mentored seven local high school students for ~30 hours of activity per student since 2007.

                                    Student Organization Advising

EcoCAR Challenge Hybrid Electric Vehicle Team                                        6/2008 - present
Ohio State University
      •   Co-advise 40 member (-80% undergraduate) student design project team competing in U.S. Department
          of Energy sponsored vehicle competition
      •   Oversee day-to-day operation of team as they model, design, build, and test a hybrid electric SUV
      •   Team won 1st place in first year, 4th place in second year
      •   Nominated by team for "NSF Advisor of the Year Award"

Challenge-X Hybrid Electric Vehicle Team                                               8/2006 - 6/2008
Ohio State University
      •   Co-advised primarily undergraduate team competing in Department of Energy Sponsored advanced
          technology vehicle completion
      •   Over the course of the four year competition from 2004 - 2008, OSU placed 3rd, 4th, 4th, and 3rd
          respectively in the premier advanced technology vehicle competition


PROFESSIONAL I
SERVICE	I	


                                         Professional Service

EPA GEM Model Reviewer, Columbus, OH
Peer Reviewer                                                                          12/2011
      • Conducted peer review of a heavy-duty truck model developed by the U. S. EPA used for predicting fuel
        economy  and green house gas emissions.

Clean Fuels Ohio, Columbus, OH                                                        9/2009 to present
Member of the Board of Directors
      • Elected to Board of Directors of Clean Fuels Ohio, a non-profit committed to cleaner transportation fuels

State of Indiana                                                                       4/2009
Proposal Reviewer
      •   Reviewed multi-million dollar proposal for Indiana grant program in area of internal combustion engines

Natural Gas Fleet Stakeholders Meeting, Grove City, OH                                  11/2008
Panel Member
      • Served as panel technical expert on alternative vehicular fuels
      • Meeting attended by designees' from the Governor's office and from both of Ohio's U.S.  Senators' staff


S. Midlam-Mohler C.V.                                                                       Page  5

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McMaster Fuel Ltd., Perrysburg, OH                                                    9/2006 to 1/2007
Independent Consultant
      •   Provided analysis of a hydrogen production technique against other methods of hydrogen production
      •   Provided analysis of these techniques for emissions reduction
      •   Assisted McMaster Fuel Ltd. in making strategic decisions regarding their technology

Publication Reviewer                                                                  Continuous
      •   Review numerous publications for conferences and journal submission of ASME, SAE, IEEE, etc.
PUBLICATIONS
                                        Scholarly Publications
Journal Articles:

1.   Gong, Q. (supervised by SMM); Midlam-Mohler, S.; Marano, V. ; Rizzoni, G. ; "Statistical Analysis forPHEV
    Virtual Fleet Study", International Journal of Vehicle Design (IJVD). Accepted but undergoing revisions.
2.   Meyer, J. (supervised by SMM); Midlam-Mohler, S.; Yurkoich, S. (colleague); "In-cylinder Oxygen
    Concentration Estimation for Diesel Engines Via Transport Delay", American Control Conference 2011;
    Accepted but undergoing revisions.
3.   M. Canova, S. Midlam-Mohler, P. Pisu, A. Soliman, "Model-Based Fault Detection and Isolation for a Diesel
    Lean NOx Trap Aftertreatment System," Control Engineering Practice, November 2009.
4.   M. Canova, S.  Midlam-Mohler, Y. Guezennec, G. Rizzoni, "Mean Value Modeling and Analysis of HCCI
    Diesel Engines with External Mixture Formation," ASME Journal of Dynamic  Systems, Measurement and
    Control,  Vol. 131, No. 11, 2009.
5.   M. Canova, S.  Midlam-Mohler, Y. Guezennec, G. Rizzoni, "Theoretical  and Experimental Investigation on
    Diesel HCCI Combustion with  External Mixture Preparation," International Journal of Vehicle Dynamics,
    Volume  44, Nos 1-2, 2007.
6.   N. Szabo, C. Lee, J. Trimbolil, O. Figueroa, R. Ramamoorthy, S. Midlam-Mohler, A. Soliman, H. Verweij, P.
    Dutta and  S. Akbar, "Ceramic-Based Chemical Sensors, Probes  and Field-Tests  in Automobile Engines,"
    Journal of Materials Science, November, 2003.

Conference Papers:

1.   Gong, Q.; Tulpule, P.,Midlam-Mohler, S.; Marano, V; Rizzoni, G.; "The Role of ITS in PHEV Performance
    Improvement", American Control Conference (ACC) 2011. Accepted but undergoing revisions.
1.   Gong, Q. ; Midlam-Mohler, S.; Marano, V.; Rizzoni, G.; "An Iterative Markov Chain Approach for Generating
    Vehicle Drive Cycles", Accepted by SAE World Congress 2011. Out for final review.
3.   Cooley, B; Vezza, D.; Midlam-Mohler, S.; Rizzoni, G.; "Model Based Engine Control Development and
    Hardware-in-the-Loop Testing for the EcoCAR Advanced Vehicle Competition", Accepted by SAE World
    Congress 2011. Out for final review.
4.   K. Pollen, M. Canova, S. Midlam-Mohler, Y.  Guezennec, G. Rizzoni, B. Lee, G. Matthews,  "A High Fidelity
    Lumped-Parameter Engine Model for Powertrain Control Design and Validation." In: ASME Dynamic Systems
    and Control Conference. Cambridge, MA, United States.
5.   Qi. Gong, S. Midlam-Mohler, V. Marano, G. Rizzoni, Y. Guezennec, "Statistical analysis based PHEV fleet
    data study", 2010 IEEE Vehicle Power and Propulsion Conference, September, 2010.
6.   Kerem Bayar, Beth Bezaire, Brad Cooley, John Kruckenberg, Eric Schact, Shawn Midlam-Mohler, Giorgio
    Rizzoni,  "Design  of  an  Extended-Range Electric Vehicle for the  EcoCAR  Challenge",  ASME  2010
    International Design Engineering Technical Conference, August, 2010.
7.   J. Meyer, S. Yurkovich, S. Midlam-Mohler, "Architectures for Phase Variation Compensation in APR Control,"
    2010 American Controls Conference, June, 2010.
S. Midlam-Mohler C.V.                                                                       Page  6

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8.   R. Maringanti, S. Midlam-Mohler, M. Fang, F. Chiara, M. Canova, "Set-Point Generation using Kernel-Based
    Methods for Closed-Loop Combustion Control of a CIDI Engine," ASME DSCC2009, September, 2009.
9.   J. Meyer, S. Rajagopalan, S. Midlam-Mohler, Y.  Guezennec,  S. Yurkovich, "Application of an Exhaust
    Geometry Based Delay Prediction Modal to an Internal Combustion Engine," ASME DSCC2009, September,
    2009.
10.  M. Fang, S. Midlam-Mohler, R. Maringanti, F. Chiara, M. Canova, "Optimal Performance of Cylinder-by-
    Cylinder and Fuel Bank Controllers for a CIDI Engine," ASME DSCC2009, September, 2009.
11.  S. Midlam-Mohler, E. Marano, S. Ewing, D. Ortiz, G. Rizzoni, "PHEV Fleet Data Collection and Analysis,"
    IEEE VPPC09, September 2009.
12.  L. Headings, G. Washington,  S. Midlam-Mohler, J. Heremans, "Thermoelectric Power Generation for Hybrid-
    Electric Vehicle Auxiliary Power," Proc. SPIE Int. Conference on Smart Structures and Materials, 2009, Vol.
    7290, No. 13.
13.  M. Canova,  S. Midlam-Mohler, G. Rizzoni, F. Steimle, D. Boland, M. Bargende, "A Simulation Study of an
    E85 Engine  APU for a Series Hybrid Electric Vehicle," 9th Stuttgart International Symposium on Automotive
    and Engine Technology, Stuttgart, Germany, 2009.
14.  S. Rajagopalan, S. Midlam-Mohler, S. Yurkovich, Y. Guezennec, K. Dudek,  "Control Oriented Modeling of a
    Three Way Catalyst Coupled with Oxygen Sensors," ASME Dynamic System and Controls Conference, Ann
    Arbor, MI, 2008.
15.  L.  Headings, S.  Midlam-Mohler, G. Washington,  and J. P. Heremans, "High Temperature Thermoelectric
    Auxiliary Power Unit for Automotive  Applications,"  ASME  Conference  on  Smart Materials,  Adaptive
    Structures and Intelligent Systems, 2008, Paper #610.
16.  K. Koprubasi, A. Pezzini, B. Bezaire, R. Cooley, P. Tulpule, G. Rizzoni, Y. Guezennec, S. Midlam-Mohler,
    "Application of Model-Based Design Techniques for the Control Development and Optimization of a Hybrid-
    Electric Vehicle", SAE World Congress 2009, Detroit, MI.
17.  K. Sevel, M. Arnett, K.  Koprubasi,  C. Coburn, M.  Shakiba-Heref, K. Bayar, G. Rizzoni,  Y. Guezennec, S.
    Midlam-Mohler,  "Cleaner Diesel Using Model-Based Design and Advanced Aftertreatment," SAE 2008-01-
    0868, 2008 International Congress, Detroit, MI, April 2008.
18.  K. Dudek, B. Montello, J. Meyer,  S.  Midlam-Mohler, Y.  Guezennec, and S.  Yurkovich, "Rapid  Engine
    Calibration for Volumetric Efficiency and Residuals by Virtual Engine Mapping," International Congress on
    Virtual Power Train Creation 2007, Munich, Germany, October 24-25,  2007.
19.  M. Canova,  S. Midlam-Mohler,  Y. Guezennec, A.  Soliman, and G. Rizzoni, "Control-Oriented Modeling of
    NOx Aftertreatment Systems," SAE ICE'07 Conference, Capri, Italy, September 2007.
20.  M.  Canova, F. Chiara,  J. Cowgill,   S.  Midlam-Mohler,  Y. Guezennec,  G.  Rizzoni, "Experimental
    Characterization of Mixed-Mode HCCI/DI Combustion on a Common Rail  Diesel Engine," 8th International
    Conference on Engines for Automobile (ICE2007), Capri, Italy.
21.  M. Canova, F. Chiara, M. Flory, S. Midlam-Mohler, Y. Guezennec, G.  Rizzoni, "Experimental Characterization
    of Mixed Mode HCCI/DI  Combustion on a Common Rail  Diesel Engine,"  submitted to SAE  ICE'07
    Conference,  Capri, Italy, September 2007.
22.  M. Canova, M. Flory, Y. Guezennec, S. Midlam-Mohler, G. Rizzoni, and F. Chiara, "Dynamics and Control of
    DI and HCCI Combustion in a multi-cylinder Diesel engine," Paper 44, submitted to 5th IF AC Symposium on
    Advances in Automotive Control, Pajaro Dunes/Seascape, CA, August  2007.
23.  A. Vosz, S. Midlam-Mohler, and Y. Guezennec, "Experimental Investigation of Switching Oxygen Sensor
    Behavior Due to Exhaust Gas  Effects," Proc. of IMECE  '06, Paper IMECE 2006-14915, Chicago, IL,
    November 2006.
24.  S.  Midlam-Mohler  and  Y. Guezennec, "A Temperature-Based Technique for Temporally and Spatially
    Resolved Lean NOx Trap  Catalyst NOx Measurements," Proc.  of IMECE  '06,  Paper IMECE 2006-14887,
    Chicago, IL, November 2006.
25.  M. Canova,  S. Midlam-Mohler, Y. Guezennec,  G. Rizzoni,  L.  Garzarella, M. Ghisolfi, and F.  Chiara,
    "Experimental Validation for Control-Oriented Modeling of Multi-Cylinder  HCCI Diesel Engines," Proc. of
    IMECE '06, Paper IMECE 2006-14110, Chicago, IL, November 2006.
26.  A. Soliman, S. Midlam-Mohler,  Z. Zou, Y. Guezennec,  and G. Rizzoni, "Modeling and Diagnostics of NOx
    Aftertreatment Systems," Proc. FISITA '06, Yokohama, Japan, October 2006.
27.  Z. Zou, S. Midlam-Mohler, R. Annamalai, Y. Guezennec, V. Subramaniam, "Literature Survey of  On-Board
    Hydrogen Generation Methods for Diesel Powertrains," Global Powertrain  Conference, Novi, MI, Not Peer
    Reviewed, September 2006.
S. Midlam-Mohler C.V.                                                                      Page  7

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28.  K. Pollen, S. Midlam-Mohler, Y. Guezennec, "Diesel Paniculate Filter Regeneration with an External Burner,"
    Global Powertrain Conference, Novi, MI, Not Peer Reviewed, September 2006.
29.  S. Midlam-Mohler and Y. Guezennec,  "Regeneration Control for a Bypass-Regeneration Lean NOx Trap
    System," American Control Conference '06, Minneapolis, MN, Invited paper, June 2006.
30.  A. Soliman, I. Choi, S. Midlam-Mohler, Y. Guezennec, G. Rizzoni, "Modeling and Diagnostics Of NOx After-
    Treatment Systems," SAE Paper 2006-05-0208, 2006 International Congress, Detroit, MI, April 2006.
31.  S. Midlam-Mohler and Y. Guezennec,  "Design, Modeling and Validation of a Flame Reformer  for LNT
    External By-Pass Regeneration,"  SAE Paper 2006-01-1367, 2006 SAE International Congress,  Detroit, MI,
    April 2006.
32.  S. Midlam-Mohler, and Y. Guezennec, "Modeling of a Partial Flow Diesel, Lean NOx Trap System," Proc. of
    IMECE '05, Paper IMECE 2005-80834, Orlando, FL, November 2005.
33.  M. Canova, L. Garzarella, M. Ghisolfi, S. Midlam-Mohler, Y. Guezennec, and G. Rizzoni, "A Control-Oriented
    Mean-Value Model of HCCI Diesel Engines with External Mixture Formation," Proc. of IMECE '05, Paper
    IMECE 2005-79571, Orlando, FL, November 2005.
34.  A. Soliman,  P. Jackson, S.  Midlam-Mohler,  Y. Guezennec,  and  G.  Rizzoni, "Diagnosis of a  NOx
    Aftertreatment System," ICE 2005 7th International Conference on Engines for Automobiles,  Capri,  Italy,
    September 2005.
35.  M. Canova, L. Garzarella, M. Ghisolfi,  S. Midlam-Mohler, Y. Guezennec,  and G. Rizzoni, "A  Mean-Value
    Model of a Turbo-Charged HCCI Diesel Engine with External Mixture Formation," ICE 2005 7th  International
    Conference on Engines for Automobiles, Capri, Italy, September 2005.
36.  M. Canova, R.  Garcin, S. Midlam-Mohler, Y. Guezennec, and G. Rizzoni, "A Control-Oriented Model of
    Combustion Process in HCCI Diesel Engines," American Control Conference  '05, Portland, OR, June 2005.
37.  C. Musardo, B.  Staccia, S. Midlam-Mohler, Y.  Guezennec, and G. Rizzoni, "Supervisory Control for NOX
    Reduction of an HEV with a Mixed-Mode HCCI/CIDI Engine," American Control Conference '05,  Portland,
    OR, June 2005.
38.  M. Canova, A. Vosz, D. Dumbauld, R. Garcin, S. Midlam-Mohler, Y. Guezennec, and G. Rizzoni, "Model and
    Experiments of Diesel Fuel HCCI Combustion with External Mixture Formation,"  6th Stuttgart  International
    Symposium on Motor Vehicles and Combustion Engines, Stuttgart, Germany, Not peer reviewed,  February
    2005.
39.  S. Midlam-Mohler, S. Haas, Y. Guezennec, M. Bargende, G. Rizzoni, S. Haas, and H. Berner, "Mixed-Mode
    Diesel HCCI/DI with External Mixture Preparation," Paper F2004V258, Proc. FISITA '04 World Congress,
    Barcelona, Spain, May 2004.
40.  Y. Guezennec, C. Musardo, B. Staccia,  S. Midlam-Mohler, E. Calo, P. Pisu, and G. Rizzoni, "Supervisory
    Control for NOx Reduction of an HEV with a Mixed-Mode HCCI/DI Engine," Paper F2004F233, Proc. FISITA
    '04 World Congress, Barcelona, Spain, May 2004.
41.  M. Gilstrap,  G.  Anceau, C.  Hubert, M. Keener, S.  Midlam-Mohler,  K. Stockmeier, J-M  Vespasien,  Y.
    Guezennec,  F.   Ohlemacher,  and G.   Rizzoni, "The  2002  Ohio State  University FutureTruck  - the
    BuckHybrid002," 2003 SAE International Congress and Exposition, Detroit, MI, March 2003.
42.  Y. Guezennec,  S. Midlam-Mohler, M.  Tateno,  and M, Hopka,  "A 2-Stage Approach to  Diesel Emission
    Management in Diesel Hybrid Electric Vehicles," Proc.  2002 IF AC Meeting, Barcelona, Spain, July 2002.
43.  M. Hopka, A. Brahma, Q. Ma,  S. Midlam-Mohler, G. Paganelli, Y. Guezennec,  and  G. Rizzoni,  "Design,
    Development and Performance of Buckeyebrid: The Ohio State Hybrid Electric FutureTruck 2001,"  SAE SP-
    1701, Not peer reviewed, March 2002.

Scholarly Presentations Independent of Paper Publications:

1.   S. Midlam-Mohler and Y. Guezennec, "Lean NOx Trap Modeling Based on Novel Measurement Techniques,"
    CLEERS Conference Workshop 3, Not peer reviewed, May 4, 2006.
2.   S. Midlam-Mohler,  and Y. Guezennec,  "Design, Modeling and  Validation of a Flame Reformer  for LNT
    External By-Pass Regeneration," 2005 DEER Conference, Chicago, IL, Not peer reviewed, August 2005.
3.   M. Canova,  S.  Midlam-Mohler, Y. Guezennec,  and G. Rizzoni, "Control-Oriented Modeling of HCCI
    Combustion," 2005 DEER Conference, Chicago, IL, Not peer reviewed, August 2005.
4.   S. Midlam-Mohler and Y. Guezennec, 2004 DEER Conference, San Diego, CA, Not peer reviewed, August
    2004.
5.   S. Midlam-Mohler, Y. Guezennec, G. Rizzoni, M. Bargende, and S. Haas,  "Mixed-Mode Diesel HCCI with
    External Mixture Preparation," 2003 DEER Conference, Newport, R. I., Not peer reviewed, August 2003.
S. Midlam-Mohler C.V.                                                                      Page  8

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6.   S.  Midlam-Mohler, Y. Guezennec, "An Active, Thermo-Chemically Managed Diesel NOx After-Treatment
    System," CLEERS Conference Workshop 2, Not peer reviewed, October 11, 2001.


                                     Intellectual Property Activity

Issued Patents:
1.   S.  Midlam-Mohler, B. Masterson, "System System for Controlling NOx Emissions During Restarts of Hybrid
    and Conventional Vehicles," U.S. Patent 7,257,493, awarded 3/21/07.
2.   S.  Midlam-Mohler, "System and Method for Reducing NOx Emissions after Fuel Cut-Off Events," U.S. Patent
    7,051,514, awarded 5/30/06.


Patent Applications:
1.   S.  Liu,  K. Dudek,  S. Rajagopalan,  S.  Yurkovich, Y. Hu,  Y.  Guezennec, S. Midlam-Mohler, "Off-Line
    Calibration of Universal Tracking Air Fuel  Ratio  Regulators,"  U.S.  Patent  Application 20090271093,
    10/29/2009.
2.   S.  Rajagopalan, K.  Dudek, S. Liu,  S.  Yurkovich, S. Midlam-Mohler, Y. Guezennec, Y.  Hu, "Universal
    Tracking Air-Fuel Regulator for Internal Combustion Engines,  U.S.  Patent  Application 20090266052,
    10/29/2009.
3.   K. Dudek, S. Rajagopalan, S. Yurkovich, Y.  Guezennec, S. Midlam-Mohler, L. Avallone,  I.  Anilovich, "Air
    Fuel Ratio Control System for Internal Combustion Engines,"  U.S.  Patent  Application 20090048766,
    2/19/2009.
4.   Y. Guezennec  and  S. Midlam-Mohler, Shawn, "Fuel Preparation System for Combustion Engines,  Fuel
    Reformers and Engine Aftertreatment," U. S. Patent Application 20040124259, 7/1/04
5.   S.  Midlam-Mohler and B. Masterson,  "System and Methods for the Reduction of NOx Emissions after Fuel
    Cut-Off Events," U.S. Patent application 20060021326, filed 2/2/03.
6.   S.  Midlam-Mohler and B. Masterson, "Strategy for Controlling NOx Emissions During Hot Restarts for Hybrid
    and Conventional Vehicles," U.S. Patent Application 20060021330, filed 2/2/03.

Patent Applications in Preparation:
1.   J. Meyer, S. Midlam-Mohler, K. Dudek, S. Yurkovich, Y. Guezennec, Topic: Engine emissions control, Status:
    submitted to patent office 9/09.
2.   J.  Meyer, S. Midlam-Mohler, K. Dudek,  S. Yurkovich, Y. Guezennec, Topic: Engine emissions control, Status:
    submitted to patent office 9/09.
3.   S.  Midlam-Mohler, S. Rajagopalan, K. Dudek, S. Yurkovich, Y. Guezennec, Topic:  Catalyst modeling for
    improved emissions control, Status: Patent application being prepared  by outside counsel.
S. Midlam-Mohler C.V.                                                                       Page  9

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ROBERT F. SAWYER                                 BS,  MS, MA, PhD, PE, NAE

        Dr. Sawyer studied at Stanford University in the Department of Mechanical Engineering (B.S. 1957,
M.S. 1958).  He served as a Rocket Test Engineer, Rocket Propulsion Research Engineer, and Chief of the
Liquid Systems Analysis Section at the Air Force Rocket Propulsion Laboratory, Edwards AFB, California
(1958-1961).  His  later graduate and doctoral degree work was at  the Guggenheim Aerospace  Propulsion
Laboratories of the Department of Aerospace Sciences at Princeton University (M.A. 1963, Ph.D. 1966).

        He joined the faculty of the Mechanical Engineering Department of the University of California  at
Berkeley as an assistant professor in 1966 and served through the rank of full professor (1991). He held a joint
appointment as a  Senior Faculty Scientist at the Lawrence Berkeley Laboratory. At Berkeley he was Vice
Chairperson for Graduate Studies of the Department of Mechanical Engineering (1980-1983) and Chairperson
of the Energy and Resources  Group (1984-1988), an interdisciplinary graduate department treating energy,
resource, and environmental  policy. He was selected  the first Class of 1935 Professor of Energy (1988).
Visiting appointments included: Visiting Research Scientist at the Johns Hopkins University Applied Physics
Laboratory (1971), Visiting Researcher at Imperial College (1978-1979), Visiting Professor at  Hokkaido
University (1984), Visiting Professor at the Toyohashi University of Technology (1984), Visiting Scientist  at
the Sandia National Laboratory Combustion Research Facility (1988-1989), and Honorary Research Fellow  at
University College London (1991).

        Dr. Sawyer served on the  President's  Council on Environmental  Quality Advisory Committee on
Alternative Automotive Power Systems (1971-1976), headed the  Technology Panel of the National Academy
of Sciences Committee on Motor Vehicle Emissions  (1973-1974), chaired the State of California ad hoc
Committee on Atmospheric Carcinogens (1978-1979), chaired the National Academy of Sciences Committee
on Diesel Engine Technology (1979-1982), served as a member of the National Research Council Committee
on Army Basic Research (1987-1988), a member of the  California Air Resources Board (1975-1976), a
director of KVB, Inc. (1975-1978), a director of the Center for Emissions Research and Analysis (1991-1994),
a member of the External Advisory Panel to the World Bank Mexico City Transport Air Quality Management
Program (1992-1996), a Senior Policy Advisor to the Office of Air and Radiation of the U.S. Environmental
Protection Agency (1994-1995), a member of the Distinguished Advisory Panel to the Joint  Auto/Oil Air
Quality  Improvement Research  Program (1988-1996),  a member of the U.S. EPA Blue Ribbon Panel on
MTBE,  and  a member of the National Research Council  Committee to Review the  MOBILE Model, the
Committee on Congestion Mitigation and  Air Quality  (CMAQ), and the Committee on Light Duty Vehicle
Fuel Economy. He chaired the Health Effects  Institute Special  Committee on Emerging Technologies. He
chaired  the Bay Area Air  Quality Management District Advisory Council (2003) and was co-chair of the
USEPA Mobile Sources Technical Advisory Sub-committee (1996-2003).

        In 2005 Dr. Sawyer accepted  the  appointment by Governor Schwarzenegger to chair the California
Air Resources Board, a position  he held until 2007. This agency  with 1200 employees and a budget of more
than 750 million dollars oversees California's air quality and global warming programs. He was a member  of
the United Nations International  Civil Aviation Organization  Independent  Experts  Panel on  Fuel  Burn
Reduction Technology (2009-2010). He is a member of the Advisory Committee to the College of Engineering
Center for Environmental Research and Technology at the University of California at Riverside  and of the
Board of Advisors of the Institute of Transportation Studies at the University of California at Davis, and the
International Advisory Board of the Center for Combustion Energy, Tsinghua University. He serves on the
National Research Council Board  on  Environmental  Science and  Toxicology,  the National  Academy  of
Engineering/National Research  Council Committee  on Analysis of Causes of the Deepwater Horizon
Explosion, Fire, and Oil Spill to Identify Measures to Prevent Similar Accidents  in the Future, and the National
Research Council Committee on Transition to  Alternative  Vehicles and Fuels. He serves on the USEPA
Mobile  Sources Technical  Review Sub-committee and is  a member of the International Council  for Clean
Transportation. He serves on the board of directors of the American Lung Association in California.

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        Dr. Sawyer served as President of the International Combustion Institute (1992-1996), is a Fellow of
the  Society of Automotive Engineers,  Associate Fellow of  the  American  Institute of Aeronautics and
Astronautics, and a member of American Society of Mechanical Engineers and the American Association of
University Professors. He is a Registered Professional Engineer (Mechanical Engineering and Fire Protection
Engineering) in the State of California. He is a recipient of the Berkeley Citation and the Sechiro Honda Medal
of the Society of Mechanical Engineers. He is listed in Who's Who in America, American Men and Women of
Science,  Who's Who  in Technology, Who's Who in Engineering, Who's Who in  Science and Engineering, and
Who's Who in the  West. Dr.  Sawyer is a  member of the National Academy of Engineering. He is a partner of
Sawyer Associates, an engineering consulting business.

        At Antelope Valley College (Lancaster, California) Dr. Sawyer was a part-time instructor of physics
and  mathematics  (1959-1961). At the University of California  at Berkeley,  he taught undergraduate and
graduate courses in combustion, propulsion,  thermodynamics, energy conversion, engines,  air pollution, and
fire safety (1966-1991). As Professor of the Graduate School, the Class of 1935 Professor of Energy Emeritus,
and  Senior Research Engineer at the Lawrence Berkeley Laboratory (1991-2005) he conducted research and
advised undergraduate and graduate research students in motor vehicle  emissions and control, toxic waste
incineration, and regulatory policy. He continued some teaching at Berkeley during this period including the
undergraduate courses, "Energy and Society" and  "The Automobile, Energy, and The Environment" and the
graduate courses, "Interdisciplinary Energy Analysis" and "Critical Issues in Air Pollution for the 1990s." He
is a  Visiting Professor of Energy and Environment at University College  London (1995-). He directed the
University of California Study Abroad Center in London, England (2003-2005). Following his service in the
California  state government, he resumed his work  at Berkeley where teaches the freshman seminar "The
Science,  Technology, Policy, and Politics of California Air Pollution." He is the author or co-author of more
than 350 publications and the co-author of two books, The Chemistry ofPropellants and Combustion Sources
of Air Pollution and Their Control.

Dr. Sawyer was born in Santa Barbara, California in 1935.  He  served in the  U.S. Air Force (active duty,
1958-1961), reaching the rank  of captain (USAFRes). He lives in Oakland, California with his wife, Barbara
Sawyer,  who is a  faculty  member and past  Chair of the Academic Senate at  Diablo Valley College.  Their
daughters, Allison  Shaffer, a finance analyst, and Lisa Sawyer, an architect, live in Davis, California.
 University of California
 Department of Mechanical Engineering
 61 Hesse Hall
 Berkeley CA 94720-1740 USA
 Cellphone: 510-305-6602
fax: 510-642-1850
 lab administrator: 510-642-0215
 email: sawyer@berkeley.edu
633 7 Valley View Road (home)
Oakland CA 94611-1226
phone: 510-339-9857

Sawyer Associates
PO Box 6256
Incline Village, NV 89450-6256
email: rsawyer@sawyerassociates. us
February 2011

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                           Wallace R. Wade, P.E.
                             50786 Drakes Bay Dr.
                                Novi, Ml 48374
                             Phone: 248-449-4549
                          Email: wrwadel (S)gmail.com
1.  Academic Background
MSME      University of Michigan, Ann Arbor             Mechanical Engineering
BME        Rensselaer Polytechnic Institute              Mechanical Engineering

2.  Professional Licenses/Certification

Registered Professional Engineer, State of Michigan

3.  Relevant Professional Experience

Areas of Expertise:
      Engine research and development
      Emission control systems
      Powertrain electronic control systems
      Powertrain calibration
      Systems engineering

1994 - 2004       Chief Engineer and Technical Fellow
(Retired Oct 2004)  Powertrain Systems Technology and Processes
(32+ years service) Ford Motor Company, Dearborn, Ml

Responsible for development, application and certification of emission and powertrain
control system technologies for all Ford Motor Company's North American vehicles.
      Developed technologies for emission control systems, powertrain control
      systems, OBD II (On-Board Diagnostic) systems and powertrain calibration
      procedures.  Achieved U.S. EPA (Environmental Protection Agency) and GARB
      (California Air Resources Board) certifications for all 1993-2005 model year North
      American vehicles.
      Developed and implemented, in production, new technology catalyst systems for
      increasingly stringent emission standards with significant reductions in precious
      metal usage.
      Developed technologies for California LEV II (Low  Emission Vehicle - 2nd
      Generation) and EPA SFTP (Supplemental Federal Test Procedure) regulations.
      Developed key low emission technologies for the engine, powertrain control
      system, exhaust emission and vapor emission control systems in the 2003
      California SULEV (Super Ultra Low Emission Vehicle) Ford Focus, which was the
      first domestic production vehicle complying with the most stringent emission
      levels required by the California Air Resources Board.
WRWCurriculum Vitae 03121 l.wrw      1                        3/12/2011

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      Developed the first analytical and laboratory based (engine and vehicle)
      automated powertrain calibration process with objective measures of driveability
      to replace the traditional on-the-road calibration process resulting in significant
      reductions in test vehicles and significant improvements in efficiency.
      Initiated production implementation of the first domestic application of a diesel
      particulate filter (DPF) with active regeneration.

Co-Chairman of the Ford Corporate Technical Specialist Committee which provided
corporate overview in promoting deep technical expertise through the selection and
appointment of technical specialists.

1992-1994         Assistant Chief Engineer
                  Powertrain Systems Engineering
                  Ford Motor Company, Dearborn, Ml

Responsible for the development and certification of emission and powertrain control
systems for all Ford Motor Company's North American vehicles.
      Developed and implemented, in production, the California LEV (Low Emission
      Vehicle) requirements featuring palladium-only catalysts and coordinated
      strategy for starting with reduced emissions (CSSRE).
      Developed and implemented OBD II, which was phased-in on all North American
      vehicles over the 1994-1996 model years.
      Developed and phased in the advanced EEC V electronic engine control system
      on all production vehicles over the 1994-1996 model years.
      Led the development and implementation of enhanced evaporative emission and
      running loss controls that were phased-in over the 1995-1999 model years.
      Led the establishment of systems engineering in the development of powertrain
      systems. Design specifications were developed for all powertrain sub-systems.

1990-1992         Executive Engineer/Manager
                  Powertrain Electronics (Containing 4 Departments)
                  Ford Motor Company, Dearborn, Ml

Responsible for the development and production implementation of powertrain
electronic control systems (hardware and software) for all of Ford Motor Company's
North American vehicles.
      Developed production powertrain electronic control systems for all North
      American vehicles.
      Developed the technology for OBD II and the advanced EEC V electronic engine
      control system.
      Led the Powertrain Electronics Control Cooperation (PECC) program resulting in
      the application of Ford EEC V systems on 30% of Mazda vehicle lines by the
      2000 model year.
      Initiated the development of Ford's next  generation 32-bit powertrain electronic
      control system (PTEC) (implemented in the 1999 model year).
WRWCurriculum Vitae 03121 l.wrw      2                        3/12/2011

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1987-1990        Manager
                  Advanced Powertrain Control Systems Department
                  Ford Motor Company, Dearborn, Ml

Responsible for the development of powertrain control system technology for future
applications.
      Developed the first Ford California ULEV (Ultra Low Emission Vehicle) emission
      control system. Major improvements in air/fuel ratio control were achieved using
      a UEGO (universal exhaust gas oxygen) sensor and a proportional control
      algorithm.
      Developed enhanced evaporative and running loss emission control concepts.
      Developed the first Ford traction control system using engine torque modulation
      combined with brake modulation.
      Developed the first Ford electronic throttle control (drive-by-wire) system for
      improved driveability (implemented in production for the 2003 model year).
      Developed engine torque modulation during shifting for imperceptible automatic
      transmission shifts.
      Initiated the requirements specification for a new 32-bit powertrain electronic
      control system (PTEC).

1978-1987        Manager
                  Engine Research Department
                  Research Staff
                  Ford Motor Company, Dearborn, Ml

Responsible for the creation, identification and feasibility prove-out of advanced engine
concepts for next generation vehicle applications.
      Developed the first Ford passenger car, direct-injection diesel that met current
      emission requirements and provided 10-15% fuel economy improvement vs.
      indirect injection diesel.
      Developed light-duty diesel electronic control systems that achieved significant
      reductions in emissions.
      Developed the first Ford adiabatic diesel engine with a ringless ceramic piston
      operating in a ceramic cylinder.
      Developed the concept and demonstrated the first Ford diesel particulate filter
      (DPF) with active regeneration that provided over 90% reduction in particulate
      emissions (scheduled for production in a Ford vehicle in 2007).

1974-1978        Supervisor, Development Section
                  Diesel Engine and Stratified  Charge Engine Department
                  Ford Motor Company

Responsible for the research and development of low emission, fuel-efficient stratified
charge engines (PROCO stratified charge, 3 valve CVCC (Compound Vortex Controlled
Combustion), spark ignited-direct injection) and diesel engines.
WRWCurriculum Vitae 03121 l.wrw       3                        3/12/2011

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1972-1974         Supervisor/Senior Research Engineer
                  Turbine Controls and Combustion Section
                  Ford Motor Company

Responsible for the research and development of low emission combustion systems for
a high temperature, ceramic gas turbine engine.
      Developed the first successful premixed,  pre-vaporized, variable geometry gas
      turbine combustion system that met the most stringent emission standards in the
      1970's.

1967-1972         Research Engineer
                  General Motors Research Laboratory, Warren, Ml

Responsible for the research and development of low emission combustion systems for
gas turbine, Stirling and steam engines for potential automotive applications.

4. Consulting

2007-2008         Expert Witness for Orrick, Herrington and Sutcliffe, LLP

Expert witness for the plaintiff in a trade secret case involving diesel emission control
systems (represented by Orrick, Herrington and Sutcliffe, LLP).  Case was successfully
settled after expert testimony. (May 2007 - December 2008)

2009              U.S. Environmental Protection  Agency/ICF Consulting Group, Inc.

Evaluated the U.S. EPA's methodology for analyzing the manufacturing costs of vehicle
powertrain and propulsion system technologies with low greenhouse gas emissions.

2009-Present      Technical Advisory Board, Achates Power, Inc.

Technical advisor to Achates Power, Inc. for the development of unique technologies for
new, fuel efficient, high power density engines.

2010              Expert Witness for Scott L. Baker, A Professional Law Corp.

Expert witness for the plaintiff in a case involving retrofit emission control systems
(represented by Scott L. Baker). Case was successfully settled after expert testimony.
(October - November 2010)

5. Associated Experience

1965-1966         1st and 2nd Lieutenant
                  U.S. Army

      1965 Frankford Arsenal - Responsible for developing improvements in the save
      capability of high-speed aircraft emergency ejection seats using propellant
      actuated devices.
      1966  Cam Ranh Bay, Vietnam - Assistant Adjutant, U.S. Army Depot

WRWCurriculum Vitae 03121 l.wrw      4                        3/12/2011

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1967-1991         Lt. Col. and prior ranks
                  U.S. Army Reserve

Annual Training (Mobilization Designation Training)- Deputy Chief of Staff for
Research, Development and Acquisition (DCSRDA), Department of the Army,
Washington, DC
      Responsible for technical analysis of critical powerplant programs for the Army's
      mobility equipment

6.  Professional Affiliations

Society of Automotive Engineering (SAE) - Fellow Member
American Society of Mechanical Engineers (ASME)- Fellow Member
Engineering Society of Detroit (ESD) - Member

7.  Patents

Issued 29 U.S. patents and numerous foreign patents in the following areas:
      Low emission combustion systems
      Diesel particulate filters
      Adiabatic engine design
      Engine control systems
      OBD II monitor systems
      Traction control

8.  Publications

Published 25 technical papers on powertrain  research and development in SAE,
IMechE, FISITA, ASME, API, NPRA (National Petroleum Refiners Association) and
CRC.

9.  Significant Awards

      Elected a member of the National Academy of Engineering (NAE), which is
      among the highest professional distinctions accorded to an engineer- For
      outstanding contributions in the implementation of low-emission technologies in
      the automotive industry (2011).
      Recognized as an innovator in the automotive industry by being appointed as
      one of the first Henry Ford Technical Fellows (1994) (technical ladder position
      equivalent to Engineering Director in Ford Motor  Company).
      ASME Soichiro Honda Medal for technical achievements and leadership  in every
      phase of automotive engineering, including 26 patents related to both gasoline
      and diesel engines (2007).

WRWCurriculum Vitae 03121 l.wrw       5                        3/12/2011

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      SAE Edward N. Cole Award for Automotive Engineering Innovation - For
      outstanding creativity and achievement in the field of automotive engineering
      (2006).
      Honored by being invited to present the 2003 Soichiro Honda Lecture at the
      ASME Internal Combustion Engine Division Meeting (September, 2003). The
      lecture provided a comprehensive description of the technology incorporated in
      the first domestic SULEV vehicle.
      Honored by the Inventors  Hall of Fame as a Distinguished Corporate Inventor
      (1997).
      Elected by ASME to Fellow Member Grade in recognition of outstanding
      accomplishments in engine combustion, efficiency and emissions research and
      development (2010).
      Elected by SAE to Fellow  Member Grade in recognition of major technical
      contributions in the area of diesel engine research (1985).
      Honored with 5 SAE Arch T. Colwell Merit Awards for SAE technical publications.
      Selected as SAE Teetor Industrial Lecturer (1985-86 and 1986-87) and invited to
      present lecture at multiple universities.
      Received the prestigious Henry Ford Technology Award for development of
      regenerative diesel particulate filter systems (1986).
      Honored with the SAE Vincent Bendix Automotive Electronics Engineering Award
      (1983).

10.  Professional Service

      Chair, ASME Soichiro Honda Medal Committee (2008-Present)
      Member of the 21st Century Truck Partnership-Phase 2 Study Committee of the
      National Research Council (2010 - Present)
      Past member of the 21st Century Truck Partnership Study Committee of the
      National Research Council (2007-2008)
      Past member of the Low Heat Rejection Engines Study Committee of the
      National Research Council (1985-1986)
      Past participant in Workshop for the National Research Council's Study on
      "Automotive Fuel Economy - How Far Should We Go?" (1991)
      Past member of the SAE Forum on Sustainable Development in Transportation
      to provide a technical response to President Clinton's initiative on future
      technology and the environment.
      Past member and chairman of the SAE Teetor  Educational Awards Committee
      Past member of SAE ABET Relations Committee
      Past member of SAE Transaction  Selection Committee for Advanced
      Powerplants and Emissions
      Past member of SAE Gas Turbine Committee (early 1970's)
WRWCurriculum Vitae 03121 l.wrw       6                        3/12/2011

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C-1

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                                   Report Review on

 "Computer Simulation of Light-Duty Vehicle Technologies for Greenhouse Gas
                 Emission Reduction in the 2020-2025 Timeframe"
                                     Ricardo, Inc.
                                   Dennis  Assanis

SUMMARY COMMENTS

The objective of this reported study is to identify the relative impact of novel and advanced light-
duty vehicle technologies on fuel economy and greenhouse gases in the 2020-2025 timeframe.
The objective is pursued by comparing different "packages" of advanced powertrain technology
through the application of a model-based vehicle  simulation software in conjunction  with
experimental  data and  empirical rules.  Vehicles comprising seven different platforms are
considered.  Representative vehicles from each platform are  identified for relevance and for
limited  validation of  the  simulation  predictions  against measured  acceleration  and fuel
consumption for a 2010 baseline case. In the spirit of improving the quality of the study and the
report, the  reviewer provides several general and  detailed comments for consideration by the
contracting agency and the authors of the report.

The report is intended to provide administrators, product planners and legislators a practical tool
for assessing what is achievable, as  well as insight into the complexity of the  path forward to
reach those advances that will be  useful for  productive discussions  between EPA and the
manufacturers.  This path forward involves trade-offs among many design choices involving
available, and soon-to-be-available advances in engine technologies, hybridization, transmissions
and accessories. The current version of the simulation effort seems reasonably balanced in the
attention paid to each of these areas.  The  range of improvements  shown in the technologies
considered and examples is encouraging.

Overall, the  project attempts to undertake an analytical technology  assessment  study  of
significant scope.  It does a fairly competent job at analyzing a select number of technologies and
packages, mostly  aimed at improving the gasoline 1C engine, and  to a less extent the diesel
engine. It complements improvements on  the engine  side with synergistic developments on the
transmissions,  hybrids  and  accessories.   The  main shortcoming  of the study is that the
methodology relies extensively on proprietary and  undisclosed data, as well as empirical rules,
correlations and modifiers without citing  published  reference  sources.   Beyond the perceived
lack of transparency, keeping up with new technologies or approaches will necessarily involve
new versions of the program since the actual models of the technologies used are proprietary and
the choice and range of parameters available to users is fixed and to some extent hidden.  Due to
these constraints, the simulation tool is limited in its ability to provide fundamental insight; this
will require a more basic thermodynamic approach,  perhaps best carried out by universities.

For the most part,  the  right technologies are  being considered.  However, certain promising
technologies and fuel options for 1C  engine technologies (other than gasoline and diesel) that  can
make a significant contribution to the improvement of mpg and reduction of CO2 emissions have
not been considered, or even mentioned at all.  Primary  examples  are advanced combustion

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technologies, such as high pressure, dilute burn, low temperature combustion (e.g., Homogeneous
Charge   Compression   Ignition,  Partially  Premixed  Compression  Ignition,  Spark-Assisted
Compression Ignition), and closed-loop, in-cylinder pressure feedback. Some of these combustion
technologies  have the  potential to  improve fuel economy by up to 25%.  Another significant
assumption is that fuels used are equivalent to either 87 octane pump gasoline or 40 cetane pump
diesel.  However, advanced biofuels, particularly from cellulosic or lingo-cellulosic bio-refinery
processes, which  from the standpoint of a life cycle analysis have strong potential for reduction of
CCh emissions, can have significantly different properties (including octane and cetane numbers)
and  combustion  characteristics  than the  current fuels.  Note that over 13 billion gallons  of
renewables were used in 2010, primarily from corn-ethanol  and some biodiesel.  According to the
Renewable Fuel Standard, 36 billion gallons of renewables need to be used by 2022.  Also, a joint
study carried-out  by Sandia and General Motors has shown that ninety billion gallons of ethanol
(the energy equivalent of approximately 60 billion gallons of gasoline) can be produced in the US
by year 2030 under an aggressive biofuels deployment schedule.

The report is lengthy at places, for instance in the description of technologies which users of the
simulation software are likely to be already familiar with, while too laconic at other places, e.g.
how the selected  technologies were modeled in  some detail.  The draft can benefit from better
balancing of its sections.  There should also be more words summarizing the illustrative results
(e.g., provide ranges of benefits), and assessing them critically (e.g., which technologies seem to
incrementally or  additively contribute the most), rather than just stating  that the results are in
Table 7.1 or in Appendix 3. A discussion  of uncertainties present in the analysis should  be
presented so as to enable the reader to place the findings into proper perspective.

The characterization of the modeling methodology as objective and "scientific" suggests that the
simulation is  composed of rigorous,  first-principle  expressions  for the various phenomena
without using "correlations", "empirical formulas", and "phenomenological models". Are these
conditions truly met? For instance, in many  cases, steady-state dyno test data are the basis of an
engine map featuring a certain technology.  In other cases,  available data were scaled based  on
empirical/proprietary factors and modifiers.   The  report should not characterize the study  as
"scientific"  unless data uncertainty is discussed and shown in  appropriate  situations. For
example, Table 7.1 presents comparisons between simulated and actual  vehicle fuel economy
performance.  Given the various subjective assumptions involved in the analysis, the authors
should comment whether the noticeable differences in certain cases are significant.
TECHNICAL COMMENTS

(1) Inputs and Parameters.  Please comment on the adequacy of numerical  inputs to the model as
represented by default values, fixed values, and user-specifiable parameters.  Examples might include:
engine technology selection, battery SOC swing, accessory load assumptions, etc.  Please comment on
any caveats or limitations that these inputs and parameters would affect the final results.

•  The report describes a comprehensive set of engine and vehicle technologies for the prediction
   of GHG emissions  and performance. However, the full range of inputs and parameters is not
   explicitly presented.  It requires the reader to refer to the Data  Visualization Tool figures to
   understand what exactly can be varied when querying the RSM. Even within the actual tool

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   simulation environment, it is impossible to extract details on, or judge the basis for a number of
   critical inputs.  In some occasions, the report mentions that published data have been used, but
   there are no references to the source.  Baseline  engine maps, torque converter maps  and
   shifting maps, electric machine efficiency maps, and control strategies for hybrids,  which have
   very direct effects on vehicle performance and emissions, should be presented in the report, at
   least in a limited format.   Below are some examples of the types of inputs and parameters  that
   would be helpful to include the following in the report:

   (i)     Any published  fuel economy maps, or other related data,  with actual  numbers.  For
          proprietary  maps and data, a  normalized  representation would be useful, as well,
          without the actual bsfc values shown on the map.
   (ii)    Baseline maps used to represent turbomachinery, in actual or normalized form
   (iii)   The baseline vehicle cooling system and accessory schematic vs. cooling  system  and
          accessory load schematics of the future engines considered in the simulation
   (iv)   Details of EGR modeling parameters,  such as maps showing percentage of EGR being
          used at various loads.
   (v)    Details of warm-up model parameters, such as ambient temperature; warm up friction
          correction; cold start fuel consumption correction factor; generation of heat rejection
          maps for various combinations in the simulation matrix

  The  engine  technology selection  appears  somewhat  limited  in terms  of the selected
  combinations.  For example, why  is the Atkinson engine not boosted  as well? Moreover,  a
  variable valve actuation  technology, as common and important as variable cam  phasing, is not
  included.  As already stated in the introductory comments, advanced combustion technologies,
  such as HCCI, are worth considering.  More flexibility in the engine and vehicle parameters
  would also allow better understanding of the improvements obtained for individual technologies
  and possibly even show some potential synergies not currently identified.

  Alternative fuels  are currently a key  research topic  and very important for future  energy
  independence. Because usage of these fuels can have an impact on efficiency and emissions, the
  study would be enhanced if engine performance maps with various fuels were included.
(2) Simulation methodology.  Please comment on the validity and applicability of the methodologies
used in simulating these technologies with respect to the  entire  vehicle.  Please comment on any
apparent unstated or implicit assumptions and related caveats or limitations. Does the model handle
synergistic affects of applying various technologies together?

•   The RSM approach is certainly a good way to provide quick access to wide range of results,
    but it has the limitation that a large number of assumptions have to  be made ahead of time in
    order to determine the design space. Also, creating these encompassing RSM's  requires a
    significant amount  of simulations, and all the results will not necessarily be of interest. If a
    more flexible model/simulation was created  and coupled to a user-friendly interface, users
    might be able to obtain and analyze the desired results instead of being  constrained by the
    design space previously determined.

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•  Even though the authors attempt to describe the simulation methodology and assumptions in
   the report, it lacks details of the models  employed, which  makes it hard to determine if
   refinements need to be made, or even if more appropriate models/methods should be used. It is
   understandable that, due  to the proprietary data, it is not possible  to present everything.
   However, without any of this information, the RSM results are more difficult to interpret.

Specific suggestions regarding models that need more detailed coverage are given below:

   Engines and Engine Models (Sections 4.1  and 6.3)
   It is  not  clear whether the engine maps in the simulation  tool were generated based on
   simulations or existing  experimental data,   somehow  fitted  and  scaled  to the  various
   configurations.  In general, the explanation on how maps were obtained is vague for  such an
   important component. In  one section, the report states that the fueling maps and other engine
   model parameters used in the study were based on published data.  If so, it would be nice to
   have  a list of the published materials that have been used as the resource.  In Section  4.2, the
   report states that the  performance of the engines in 2020-25 were developed by taking the
   current research engines and assuming the performance of the 2020 production engines will
   match that of the research engine under consideration.  Does this assumption take into  account
   the emission standards  in 2020, and do  the current research engines match those emission
   standards? What is the systematic methodology that has been adopted to scale the performance
   and fuel economy of current baseline engines to engine models for 2020-25?  Also, the report
   lacks detail concerning the methodology of extrapolating from available  maps to  maps
   reflecting the  effects on overall  engine  performance of the  combination  of  the future
   technologies considered.

   The report lacks detail on the specifics on the different engine design and operating choices.
   For instance,  what was the compression  ratio (and  limit)  that was used?   What is  the
   equivalence ratio, or range considered, for the lean burn engine?  How much EGR has been
   used across the speed and load range? What constraints, if any, were applied to the simulations
   to account for combustions limitations such  as knock and flammability limits? The NOx
   aftertreatment/constraints section could also be expanded.

   In cases where engine  models  have been used  to  generated  maps, how was  combustion
   modeled? For instance,  discussion is made as to the heat transfer effect resulting from surface
   to volume changes connected to downsizing. More detail on the heat transfer assumptions that
   go into the applied heat  transfer factor would be helpful. Was heat transfer modeled based on
   Woschni's correlation?  What about friction  scaling with piston speed? This would change
   with stroke at a constant RPM. Also friction would change with the number of bearings and
   cylinders.

   Turbocharger systems (Section 4.1.3)
   There is no discussion of turbocharger efficiencies and their range. Did the simulations assume
   current boosting  technologies?  Were  maps  used  for  this  simulation  or some  other
   representation? Was scaling used? What were the allowed boost levels?

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Intelligent Cooling Systems (Section 4.3.1)
The report describes intelligent cooling systems,  but does not provide any estimates of the
anticipated reductions in fuel consumption over the FTP cycle,  though related papers have
been published in the open literature.

Sizing of various cooling components plays a very  crucial role in fuel economy predictions.
The report does not provide any detail on how the optimum cooling flow required for a given
engine- transmission combination was determined.  This would significantly affect the oil,
coolant and transmission  oil pump  RPMs, which  would  in  turn significantly change the
accessory loads.

In addition, the report does not have any discussion on how  modified cooling  components
(radiator, condenser, etc.) would be sized for more efficient powertrains.  For instance, a more
efficient engine that would reject less heat  would likely need a smaller radiator and lesser
airflow through the radiator; hence, the grill opening could be reduced to cut down on aero
drag.  A high efficiency transmission will not reject a lot of heat to the transmission oil; thus, a
smaller transmission oil cooler could be used.

Warm-up methodology (Section 6.3.1)
This section talks about using engine warm-up profile during the cold start portion to  ascertain
additional fueling requirements. It talks about a correction factor to account for this additional
fuel. How was this factor determined?  Has a different correction  factor been used for various
engines? For instance, for a lean-burn engine that reject less heat, the oil warm-up is slower
compared to a baseline engine. Was a new heat rejection map generated to account for start-up
enrichment while modeling the  warm-up? What is the ambient temperature that has been
considered while performing the FTP 75 fuel economy test? Have the viscous effects of
engine oil considered in the warm up simulation? How have  the friction losses for various
valvetrain engine combinations been modeled?

Accessories Models (Section 6.3.2)
Alternator efficiency has been assumed to be constant around 55% for baseline.  In the current
baseline vehicles the alternator efficiencies do vary with the temperature and load.

Has AC compressor load been considered in any of the simulations? In some of the new cycles
being proposed by EPA, it is required that AC  remains ON throughout the cycle.  Hence,
management of the AC load is very critical.

Transmission Models (Section 6.4)
The  transmission  efficiencies  vary  by  almost  10-15%  based on  the  transmission  oil
temperature. How have these effects been modeled?

Constraints
There is no discussion in the report that discusses the constraints on the combinations that can
be implemented in real life. For example, would a multi-air system that is currently  designed
for small size engines work for a full size car?

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(3) Results. Please comment on the validity and applicability of the results to the light-duty vehicle fleet
in the 2020-2025 timeframe. Please comment on any apparent unstated or implicit assumptions that
may affect the results, and on any related caveats or limitations.

•   For the vehicle performance simulation results shown in Table 7.1, were there any significant
   adjustable parameters used to fit these vehicles?

•   Even though it appears that the validation results from the simulation have "acceptably" close
   agreement with the test data, there are up to 15% off.  Even for the small car where all data is
   available, the error is on the  order of 5%.  These discrepancies are usually not negligible and
   should  be taken  into  account when  conclusions are drawn from the results,  especially if
   regulation is to be proposed based on these.

•   There is also no baseline hybrid configuration and no validation of the hybrid model. Due to
   the increased complexity of these vehicle systems, it is important to ensure the parameters and
   assumptions are valid.

•   It would be desirable to include a complete test case  with the appropriate inputs, analysis and
   outputs as part of the report. The sample results presented in figures  seem to have been
   included to indicate the RSM and Data Visualization  Tool's capabilities, but they do  not
   provide a complete picture from which to draw solid conclusions.

•   The plots showing simulation results in blue, red, etc.  could be  better labeled (i.e.  legends
   could be inserted in the plots) and possibly presented in a  relative format indicating percent
   improvements over the baseline  engine rather than  absolute numbers.   This  is more of a
   personal choice for  a  more  clear representation  of  the predicted improvement, rather than
   stating that there is anything wrong with the current representation.
(4) Completeness.  Please  comment on whether the report adequately describes the entire  process
used in the modeling work from input selection to results.

  Some  of the aspects lacking form the report have already been mentioned and discussed in the
  relevant sections.

  In general, the report provides a fair description of the modeling process.  Unfortunately, there
  are no equations, plots or maps showing any specific modeling item, thus making this part of the
  report vague.

  It might be  possible  to shorten the  descriptions  related  to  the individual  technologies
  implemented and their  improvements and  add more details on how they have been modeled.
  People using this tool will most likely not use the brief descriptions of the various technologies
  to draw conclusions and make decisions.

  The "Conclusions"  section of the report should be renamed "Summary" since it does not present
  any  actual conclusions based on the results,  but it does provide a summary of the project.

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(5) Recommendations. Please comment on  the overall adequacy of the report for  predicting the
effectiveness of these technologies, and on any improvements that might reasonably be adopted by the
authors for improvement. Please note that the authors intend the report to be open to the community
and transparent in the assumptions made and the methods of simulation.  Therefore recommendations
for clearly defined improvements that would  utilize publicly available  information would be preferred
over those that would make use of proprietary information.

  Various suggestions have already been included in the relevant sections.

  The authors should expand the  modeling sections.  In  particular, they should cite literature
  references (where possible) and provide  more detail when empirical data, modifiers, or scaling
  laws are used.

  Flexibility should be added to the models.  Some engine technologies, such as  variable cam
  phasing, HCCI and alternative fuels should be considered.

  A  self-contained  study  should be presented as a test  case for  the  results  so  that  specific
  conclusions can be drawn and the utility of the approach more easily understood.
 (6) Other comments.  Please provide your comments on report topics not otherwise captured by the
aforementioned charge questions.

It would be desirable to show the analysis used to convert fuel consumption savings to vehicle
greenhouse gas  (GHG) emissions equivalent output.   Ultimately, what matters is the  GHG
savings resulting from the combined production and use cycle of alternative fuel  options for
combustion engines.

Some additional  detailed comments on specific sections are given below.

  Advanced Valvetrains (Section 4.1.1)
  The  report states  that  advanced  valvetrain  systems improve fuel  consumption  and  GHG
  emissions mainly by improving engine breathing.  Other benefits cited are in supporting engine
  downsizing and faster aftertreatment warm-up. Beyond improving volumetric efficiency and
  reducing  pumping  losses,  advanced  valvetrains  can enable compression ratio variation to
  increase fuel economy and avoid knock, alter the combustion process by modulating trapped
  residual, and enable cylinder deactivation to reduce pumping losses.  From the report, it is not
  clear which of the possible benefits of the advanced valvetrain packages have been harnessed
  in each case. A more systematic analysis of technology package combinations is warranted as
  several are synergistic but not additive.

  Boosting System (4.1.3 and 6.3)
  A two-stage system is indeed promising for advanced turbocharging concepts.   A distinction
  should be made between series and sequential configurations.  Air flow manipulation can make it
  a series system (two-stage expansion and compression) or a sequential system (turbos activated
  at different rpm). Variable geometry or twin-scroll turbines can be good options for the low or
  high pressure  stages, respectively.  A two-stage turbocharging system like this would  take

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advantage of the lean SI exhaust enthalpy, reduce pumping work (or even aid pumping), avoid
mechanical work penalties, improve engine transient response, enable high  dilution levels (if
desired) and probably help keep in-cylinder compression ratio below 12:1, since significant
compression would be done before the cylinder.  EGR flow could be driven through  a  low
pressure loop (after the turbines) or an intermediate pressure loop (between the turbines).  The
resulting turbo lag will depend on the details of the configuration and the control logic used.
Note that the assumption of a time constant of 1.5 seconds (as stated in the report) to represent
the expected delay may not hold true in all cases.

Lean-Stoichiometric Switching (Section 4.2.2)
The mixed-mode operation considered in the report seems to switch between stoichiometric and
lean  SI direct injection operation.   There are several multi-mode combustion  efforts  under
development that encompass  several more combustion modes, including HCCI and  Spark-
assisted compression ignition with amounts of EGR dilution.

P2 Parallel Hybrid (Section 4.3.2)
P2 refers to pre-transmission parallel hybrid, where an electric machine is placed in between the
engine and the transmission.  While the report does not discuss details, there are two possible
configurations: (i) a single clutch, located in between the engine and the electric machine, such
as in the Hyundai Sonata, and (ii) two clutches, one in between the engine and  the motor, and the
other one in between the motor and the transmission, such as in the Infiniti M35 HEV.  The P2
system looks promising to achieve good  efficiency, but remaining barriers include cost, drive
quality, durability and to a lesser extend packaging. Careful consideration of details is needed to
properly assess benefits compared to a single mode power split.  Early reports have indicated that
Nissan got 38% mpg increase out  of their  P2  and Hyundai got  42%,  both  with  higher
horsepower, as well.  However,  the P2  Touareg  doesn't seem  to  meet EPA 2012  CAFE
standards.

Transmission Technologies (Section 4.4)
What about automatic transmissions with automated clutch replacing the torque converter and
lock-up clutch? This is also a possibility.

Efficient Components (Section 4.4.9)
Efficient components should also include gears since rotating gears are also  a major source of
drag.  Designing a better profile for gear teeth can reduce drag losses.

Transmission Models (Section 6.4)
It is claimed that gear selection will be optimized for fuel economy for a given driver input and
road load.  Can this also be adaptive? Engine performance degrades  with age.  This strategy
could also lead to more gear shifts; the latter would increase hydraulic loads and frictional power
losses in the clutch, thus eroding some of the possible fuel economy gains.

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 Peer review of the report, "Computer Simulation of Light-Duty Vehicle Technologies for
            Greenhouse Gas Emission Reduction in the 2020-2025 Timeframe"
                              Report by: Scott McBroom
                             Date of Report: May 15, 2011
Charge to Peer Reviewers:
       As EPA and NHTSA develop programs to reduce greenhouse gas (GHG) emissions and
increase fuel economy of light-duty highway vehicles, there is a need to evaluate the
effectiveness of technologies necessary to bring about such improvements.  Some potential
technology paths that manufacturers might pursue to meet future standards may include
advanced engines, hybrid electric systems, mass reduction, along with additional road load
reductions and accessory improvements.

       Ricardo Inc. has developed simulation models including many of these technologies with
the inputs, modeling techniques, and results  described in the Ricardo Inc. document that you
have been provided dated March 10, 2011.

       EPA is seeking the reviewers' expert opinion on the inputs, methodologies, and results
described in this document and their applicability in the 2020-2025 timeframe.  The Ricardo Inc.
report is provided for review.  We ask that each reviewer comment on all aspects of the Ricardo
Inc. report.  Findings of this peer review may be used toward validation and improvement of the
report and to inform EPA and NHTSA staff on potential use of the report for predicting the
effectiveness of these technologies. No independent data analysis will be required for this
review.

       Reviewers are asked to orient their comments toward the five (5) general areas listed
below. Reviewers are expected to identify additional topics or depart from these general areas as
necessary to best apply their particular set of expertise toward review of the report.

       Comments should be sufficiently clear and detailed to allow readers familiar with the
report to thoroughly understand their relevance  to the material provided for review. EPA
requests that the reviewers not release the peer review materials or their comments until Ricardo
Inc. makes its report and supporting documentation public. EPA will notify the reviewers when
this occurs.

       Below you will find a template for your comments. You are encouraged to use this
template to facilitate the compilation  of the peer review comments, but do not feel  constrained by
the format.  You are free to revise as needed; this is just a starting point.

       If a reviewer has questions about what is required in order to complete this  review or
needs additional background material, please contact Susan Elaine at ICF International
(SBlaine@icfi.com or 703-225-2471). If a reviewer has any questions about the EPA peer review
process itself, please contact Ms. Ruth Schenk in EPA's Quality Office, National Vehicle and
Fuel Emissions Laboratory by phone (734-214-4017) or through e-mail (schenk.ruth@epa.gov).

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Scott McBroom
Charge Questions:

(1) Inputs and Parameters. Please comment on the adequacy of numerical inputs to the model
as represented by default values, fixed values, and user-specifiable parameters. Examples might
include: engine technology selection, battery SOC swing, accessory load assumptions, etc.)
Please comment  on any caveats or limitations that these inputs and parameters would affect the
final results.

(Section 3.2 Ground Rules for Study)  The vehicle and technology selection process needs
further discussion.  My experience in these large simulation studies is that the vast majority of
the time needs to be spent on the selection and once selected agreeing upon the model/data.

(Section 4) There was no model data provided. Engine maps, transmission efficiency maps,
battery efficiency maps etc need to be in the Appendices. The black box nature of the inputs is
disconcerting.

(Section 4.1.1.1 CPS) How were the profiles selected? Was there an optimization process for
each engine size  of a given engine type?

(Section 4.1.1.2 DVA) Was the actuation power requirement accounted for?  What were the
timing/lift profiles  and what control strategy was used to select the timing/lift profile? Was this
an active model or was the timing/lift profile preset and then unchangeable. I would expect that
as the engine size changes and the boost changes the timing/lift profile will have to change with
it.

(Section 4.1.3 Boosting Systems) What about superchargers? Eaton's AMS supercharger
systems offer high  efficiency supercharges that are comparable to turbo's and don't have the lag
problem.

(Section 4.1.4 Other Engine Technologies) regarding global engine friction reduction, what
value(s) was assigned to that? Was it the same across all engines? If so, why?

How was the FEAD electrification energy balance accomplished? Was additional load placed on
the alternator?

No mention or consideration of cylinder deactivation technologies. This seems like pretty low
hanging fruit, even on downsized boosted engines, especially if you deploy DVA.

(Section 4.2 Engine Configurations) Quantification needed .. ."The combinations of technologies
encompassed in each advanced engine concept provide benefits to the fueling map...."

How were baseline BFSC maps modified? Was it across the board improvement or were
improvements only attributed to certain parts of the map?

(6.3 Accessories) I think the assumption that LDT cooling fans will  be engine driven is incorrect.
The new FISO's  have electric fans.

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Scott McBroom
Limiting the alternator to 200A is very conservative, particularly if the system voltage stays at
14V.

Is there any accounting for the energy conversion on hybrids from the high voltage bus to the
low voltage?

(6.4 Transmission Models) no efficiency maps, no description of the efficiency maps. What was
efficiency a function of?  Typically it's gear ratio, torque and speed.

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Scott McBroom
(2) Simulation methodology. Please comment on the validity and applicability of the
methodologies used in simulating these technologies with respect to the entire vehicle.  Please
comment on any apparent unstated or implicit assumptions and related caveats or limitations.
Does the model handle synergistic affects of applying various technologies together?

(Section 3.4 CSM Approach) Is the CSM approach used in other applications?  If so it would be
helpful to give citations.  If it was developed by Ricardo, that should be stated.  The discussion
refers to physics based models, but other than that very little about the type of modeling is
discussed. I recall on the phone call that lumped parameter models were mentioned. There is no
discussion of that.

Some assessment of the model uncertainty would be helpful. This could be a qualitative rating
assigned by the  advisory committee or a more rigorous method could be used.

More detail on the types  of models is required.  Do some models use first principals of physics
and others lumped parameter?

ANOVA or some other analytical approach to consider technology interactions needs to be
deployed.

It says a statistical analysis was used to correlate variations in the input factors to variations in
the output factors. This is ambiguous. What analysis method was used? Where is it reported? I
didn't see anything in the results about this. It was used to generate the RSM, but what was the
measure of fitment? How did the RSM fit compare from vehicle config to vehicle config

(Section 4.1.1 Advanced Valvetrains) There is no explanation of how CPS and DVA systems
were modeled. There was only a description of what CPS and DVA is.

(Section 4.2.1 Stoich DI  Turbo) Quantify how did the cooled exhaust manifold/lower turbine
inlet temp improved the BSFC map.  This is a good example of technology interaction.. .how did
the radiator size grow to  accommodate the additional heat rejection; how did the frontal area of
the vehicle change to accommodate the larger radiator?

(Section 4.2.2 Lean Stoich Switching) This type of tech points to one of the dangers of
optimizing configuration/technology/control strategy to the drive cycles; that is that it has the
potential to over constrain the design and effect the "real  world" performance/fuel economy.

(Section 4.2.4 Atkinson Cycle) How do the 2020-2025 maps differ from the 2010 maps?

(Section 4.2.5 Advanced Diesel) Why were only the benefits of improved pumping losses or
friction  considered? What improvements were assigned to these benefits? Was it across the
board or regional? What  about advanced boosting technology for these engines?

Ricardo's expectation for pace and direction: I thought there was an advisory committee making
these decisions.  I'm surprised that they think boost will be limited to 17-23bar.

(4.4 Transmission Technologies) How were the gear ratios selected? What about shift logic?

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Scott McBroom
(Section 6 Vehicle Models) No discussion of how driveline inertia is handled. This is important
in forward-looking models.

There are several types of rolling resistance models, what type was used?

Was coast-down data from the baseline vehicles obtained or where the coefficients of rolling
resistance and Cd modified to get the data to match?

(6.3 Engine Models) two methods to develop engine models were discussed. It is not disclosed
which approach was used for which engine.  I recommend that one approach be developed for all
engines or both approaches be applied to each engine to converge to a solution.

Regarding engine downsizing, I'm not sure that the scaling approach applies to boosted engines,
especially engine with multiple compressors as well as DVT and CPS technology.

Turbo lag applied as a first order transfer function with a time constant. How was the time
constant selected? Was it validated? How was the improvement attributed to turbo compounding
modeled?

(6.3.1 Warm-up Methodology) How was the engine warmup modeled? Is it a first order transfer
function with a time constant? It said  proprietary data was used, but how? Does the method
allow for different warmup depending on size and engine technology?

(6.3.2 Accessories) Constant alternator efficiency and load is not a very good assumption.  New
alternator technologies and higher alternator loads due to electrification and increased electrical
demands.  Will the future still continue to use 14V or will higher voltages be used?

(6.8 Hybrids) Were separate optimization runs to determine the best control strategy done? How
are we assured the best control strategy is implemented?

(7.2 Nominal Runs) Was a separate matrix of simulations run to obtain the nominal sizes for the
advanced engine or was it merely a matter of matching the peak torque.

How was a 20% reduction in engine size for the nominal hybrid engine arrived at? Even for the
micro-hybrid (engine start/stop)?

"These summary results... .used to  assess the quality of the simulation...." Where is the data for
this assessment published? What were the criteria that said pass or fail?

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Scott McBroom
(3) Results. Please comment on the validity and applicability of the results to the light-duty
vehicle fleet in the 2020-2025 timeframe. Please comment on any apparent unstated or implicit
assumptions that may affect the results, and on any related caveats or limitations.

(Section 4.4.6 Shifting Clutch Technology) "The technology will be best suited to smaller
vehicle segments because of reduced drivability expectations" - not in the US market.

(Section 4.4.7 Improved Kinematic Design) Assumes a sweeping improvement without
identifying a clear rationale.. .doesn't appear to describe a scientific or objective approach.

(Section 4.4.11 Lubrication) Assumes a sweeping improvement without identifying a clear
rationale.. .doesn't appear to describe a scientific or objective approach.

(Section 4.5.1 Intelligent Cooling System) The system as described seems more appropriate for
regulated emissions reduction opportunity rather than fuel economy or GHG.  I think  these
systems enable engine control strategies that aren't part of this study that would have  a greater
impact on fuel economy than warming up the engine faster.

(5.2 Vehicle Configuration and technology combinations) Also there is  no scientific or objective
reason given for the DoE ranges.  It appears that I can make any vehicle 60% less mass, 70% less
rolling resistance etc... .This will skew the results towards that end of the DoE, when they may
not be practically achievable.

(6.1 Baseline Conventional Vehicle Model) Results were compared to the EPA Vehicle
Certification Database.  These results often include correction factors and allowances  that aren't
documented on the sticker. Recommend that actual testing be run to perform the benchmark.

(6.3.1 Engine Warmup Methodology) Were there hot and cold engine maps? No mention.

(6.4 Transmission Models) Fig 6.1 appears to be a comparison of desired cvt ratio vs  desired
6spd gear ratio.  Should be stated as such. The shift logic controller should take into account the
time to shift and whether or not the desired shift is achievable.

What are the shift optimizer inputs? What are it's basic decision criteria?

There is no discussion of engine downspeeding.

There is no discussion of gear ratio selection.

(6.5 torque Converter models) The lockup strategy seems very conservative.  Large gains are
achievable with more sophisticated control and are in use today.

What was the basis for the minimum rpm's for lockup sited? Should be based on lugging the
engine.  The controller should recognize when it needs to unlock the TC based on the engines
ability to keep up.

(6.6 Final Drive Model) Only discussed the baseline, what improvements for 2020 and what final
drive selection criteria for the future vehicles was used?

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Scott McBroom
(6.7 Driver Model) How was the soak modeled? Were there hot engine maps and cold engine
maps?

(7.1 Baseline Conventional Vehicle Models)
Better definition of what "acceptably close" means. This doesn't meet the criteria for
objectivity. Something like, "the advisory committee determined that the baseline models had to
predict within x% to be usable for this study."

On the performance runs, a few tenths of a second represent measurable difference in engine
torque for example.

(8.1 Evaluation of Design Space) Why was Latin hypercube sampling methodology picked over
other sampling methods? While it's attributes are mentioned, what other methods were
considered?

(8.2 RSM)  A description of how the neural network is deployed is needed, only the why it was
used is discussed in this section.  What were the best fit criteria? What types of equations  did the
neural net have to play with? Where are the fit's published? How was it determined that the "one
fit per transmission" was the best way to go?

(9.1 Basic Results) Why lOHz sampling rate? By what criteria was a run considered good vs
bad?

(9.3 Exploration of the Design Space) If boundaries of acceptable performance were applied, a
considerable number of simulation runs could be eliminated.

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Scott McBroom
(4) Completeness. Please comment on whether the report adequately describes the entire
process used in the modeling work from input selection to results.

(Section 2 Objectives) A discussion of appropriate/anticipated use of the results is required.

(Section 3.3 Ground Rules)  How did the group arrive at the seven vehicles?  While it show
comprehensiveness, it's possible to see that there could be some overlap. If one looks at the
engine and transmissions packages available in these vehicles already you can see the overlap.
Reducing the number of vehicles might save on the number of runs you'll need to make.

(Section 3.3 Technology Selection Process) Who is on the Advisory Committee? Is it
independent? How did the program team come up with the comprehensive list of potential
technologies? (From the phone call it sounded like it was based on what models Ricardo had in
their library. This is concerning.)

It said there was a comprehensive list of technologies that the group started with, that list should
be shown and a comment on why it wasn't included.

Why wasn't HCCI technology considered? From the publications this seems to be a candidate
for production in the next 10 yrs.

(Section 4. Technology Review and Selection) Regarding qualitative evaluation of technology
"Potential of the technology to improve GHG emissions on a tank to wheels basis", since this
was a qualitative assessment I think it would be better to include well to wheels.

Regarding "Current (2010) maturity of the technology", how was maturity ranked?

Citations required for statement" SI engine efficiency to  approach CI efficiency in the time
frame considered"  This represents relatively large gains in SI technology compared to CI,
however EU and Japanese engine companies are making big improvements on CI as well.

(Sections 4.1 and 4.2) There's no descriptions of the models. There are  only descriptions of the
technologies and their perceived benefits. The reader has to assume that the same modeling
approach was used to model each technology, but I know from personal experience this is very
difficult and most likely not the case.

(Section 4.1.2 DI Fuel Systems)  No discussion of DI control strategy. How was it selected? Was
there a separate optimization of DI control or was it one size fits all?

(Section 4.1.3 Boosting Systems) It says that other boosting systems were included in the study,
but only turbocharging is discussed.

(Section 4.3 Hybrids) Don't see any data on the battery technology, battery management, SOC
control strategies. No discussion of regen braking strategies.

(Section 4.3.1 Micro Hybrids) It is implied that electrified accessories aren't used in this
configuration. I don't see that as the case.

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Scott McBroom
(Section 4.3.2 P2 Hybrid) No discussion of why DCT was only transmission used for P2 hybrids
instead of CVT and AMI.

(4.4 Transmission Technologies) What types of CVT's were in the original mix? Toroidals,
push-belts, Miller?

No transmission data was shown. No mass, no inertia to efficiency maps, no gear ratios.

(4.4.1 Automatic Transmission) No logical explanation for the 20-33% improvement.. .how was
this number arrived at?

(4.4.3 Wet clutch) It said these were expected to be heavier, cost more and be less efficient than
DCT's so why where they included?

(4.4.10 Super Finishing) How much improvement is attributed to super finishing?

(4.5 Vehicle Technologies) No values for mass, rolling resistance or drag given. No discussion
of the improvement possibilities. This would be a good place to use historical trends for vehicle
mass reduction, aero improvements and parasitic loss improvement.

(5.2 Vehicle Configuration and technology combinations) While the tables show the vehicle
configurations, more discussion regarding the selection criteria for each vehicle is warranted.  In
some cases this discussion was attempted in the technology sections, but I don't think it should
go there.

(Section 6 Vehicle Models) No discussion  of how driveline inertia is handled.  This is important
in forward-looking models.

There are several types of rolling resistance models, what type was used?

(6.8 Hybrid Models) Too much data is missing. What were the  pack voltages? What were the
battery technologies? Was there only one or more? Other than  improved resistance, what other
future improvements were included, like improved power density,  improved usable SOC range?
What was the control strategy for each type?

Load leveling the engine by charging the batteries has been shown to not be a very good idea
because the round trip efficiency hit is a killer. Should only be used when SOC falls below a
certain level.

We're left to assume that SOC leveling is accomplished, but there is no description of how? Was
an EPA/SAE method used.

When it comes to GHG reductions  why weren't plug-in hybrids considered?

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Scott McBroom
(5) Recommendations. Please comment on the overall adequacy of the report for predicting the
effectiveness of these technologies, and on any improvements that might reasonably be adopted
by the authors for improvement. Please note that the authors intend the report to be open to the
community and transparent in the assumptions made and the methods of simulation. Therefore
recommendations for clearly defined improvements that would utilize publicly available
information would be preferred over those that would make use of proprietary information.

    1)  Instead of using proprietary Ricardo data/models/control  algorithms citable data should
       be used.
   2)  Without stating how this model is going to be used in the regulatory decision making
       process, it is very difficult to assess its appropriateness.
   3)  Considerably more time in this effort is required up front in the report, to discuss the
       process of building consensus on data and models. Because this is not really discussed, it
       gives the impression that not much was done.
   4)  Guidelines for appropriate use should be given.
   5)  An uncertainty rating for each model/data set should be published to highlight the relative
       differences in the assumptions/extrapolation of future technologies.
   6)  Should use coast down data for baseline vehicles to model parasitic losses.
   7)  In terms of acceptable use: rather that trying to use the model to assess the boundaries of
       the envelope (or which technology is better), the tool could be used to find the areas of
       maximum overlap. In other words, knowing that the same performance and fuel economy
       is achievable using different technologies lends more confidence that the result is
       achievable.  Theoretically this number could be a calculated value generated from the
       RSM's.
   8)  Recommend allowing "real world" drive cycles to assess the robustness of the results.
       Could be a user generated result from a composite of the  data sets already generated.
   9)  Should define the process  for data selection... .eventually you'll be asked by a
       manufacturer, 'how do we get 'x' technology included for consideration in the study.
    10) Where lumped improvements are made, I recommend using historical results to publish
       technology improvement curves. For example, the parasitic losses (Cd, Crr) should be
       quantifiable. Vehicle mass reductions as well.
(6) Other comments. Please provide your comments on report topics not otherwise captured by
the aforementioned charge questions.


                                           10

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Scott McBroom
Having conducted a similar effort for USCAR on the PNGV program, I understand that
considerable effort is required to develop such a model. I don't want to diminish all the hard
work that was done, by only offering criticism in the above sections. It appears that the intent of
the approach to this activity is in the right place, just better documentation is needed and
appropriate use guidelines.
                                           11

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                       PEER REVIEW:
       Computer Simulation of Light-Duty Vehicle
Technology for Greenhouse Gas Emission Reduction in
              the 2020-2025 Timeframe
                     Review Conducted for:

                        U.S. EPA
                     Review Conducted By:

                    Shawn Midlam-Mohler
                        Review Period:

                      4/28/2011-5/16/2011

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Contents




   Executive Summary	3




   Simulation Methodology	4




     Vehicle Model	5




     Engine Models	5




     Aftertreatment/Emissions Solutions	7




       Advanced Valvetrains	7




       Direct Injection Fuel Systems	8




       Boosting Systems	8




       Engine Downsizing	8




       Warm-Up Methodology	9




       Accessory Models	9




       Engine Technology "Stack-Up"	10




     Baseline Hybrid Models	11




       Hybrid Control Strategy	11




       Electric Traction Components	12




       HEV Battery Model	12




     Transmissions	13




   Data Analysis Tool	13




   Conclusions	14
Shawn Midlam-Mohler - Peer Review                                           Page 2

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Executive Summary
   For  the  purpose of  describing the modeling approach  used in the forecasting  of the
performance of future technologies, the report reviewed is inadequate. In virtually every area,
the report lacks sufficient information to answer the charge questions provided for the reviewer.
It is entirely possible that the approach used is satisfactory for the intended purpose.  However,
given the information provided for the review, it is not possible for this reviewer to make any
statement regarding the suitability of this approach.  Some brief comments on each of the five
charge questions are provided below:
   Inputs and Parameters - From a high level, it is clear what the inputs to the design space
tool are, which are listed in tables  8.1 and 8.2.  At the next level down (i.e. the vehicle and
subsystem models) there is  no  comprehensive handling of inputs in  parameters in the  report.
Some models are partially fleshed out in this area but most are lacking. By way of example, the
engine models are described as maps which are "defined by their torque curve, fueling map, and
other input parameters" where "other input parameters" are never defined.
    Simulation  Methodology - The vehicle model is reported as  "a complete, physics-based
vehicle  and powertrain system  model" - which it is not.  The modeling approach used relies
heavily  on maps and empirically determined data which is decidedly not physics-based.  This
nomenclature issue aside, the model is not described in sufficient detail in the report to make an
assessment in this  area.   An excellent example of this is the  electric traction drives and HEV
energy storage system for which the report mentions no  details,  even qualitative ones,  on the
structure of the models.
   Results - The  third charge questions deals with the validity  and the  applicability  of the
resulting prediction.   The  difficulty in this task is  that it  is an  extrapolation from present
technology that uses an extrapolation method (i.e. the model) and a set of inputs to the model
(i.e. future powertrain data.)  Since it is not possible to validate the results against vehicles and
technology that  do not exist, one  can only ensure that the model and  the  model inputs are
appropriate for the task.   Because  of the lack  of transparency in the model and  inputs  it is
difficult to make any claims regarding the results. In trying to validate results, one example is

Shawn Midlam-Mohler - Peer Review                                             Page 3

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cited in the body of the report that shows the baseline engine getting superior HWFET and US06
fuel economy than all of the other non-HEV powertrains with other factors being the same - this
leaves some skepticism regarding the results.
    Completeness -  Based on the above, it is  clear that this reviewer feels the report  is
inadequate at describing the  entire  process of modeling work from input selection to results.
There was not a single subsystem that was documented at the level desired.  It is understood that,
in some cases,  there  are things of  a proprietary nature that  must be concealed.  As a trivial
example,  the frontal  area of the vehicle classes does not seem to be anywhere in the report  or
data analysis tool.  This is one parameter amongst hundreds  excluding the real details of the
models (i.e. equations or block diagrams),  methods used to  generate engine maps, details on
control laws, etc.  On the topic  of proprietary data,  there are  many ways of obscuring data
sufficiently that can  demonstrate  a key point (i.e. simulation  accuracy) without compromising
confidentiality of data - this  should not be a major barrier to providing some insight into the
inner working of the simulator.
    Recommendations - Given the  low level  of detail given in the report, it does seem that the
strategy used is consistent with the goal of the work and what others in the field are doing.  That
being said, the report is inadequate in nearly every respect at documenting model inputs, model
parameters,  modeling methodology, and the sources and techniques used to develop the
technology performance data. Given the need for transparency in this effort, this reviewer feels
that the detail in the report is wholly inadequate to document the process used. The organization
responsible for the  modeling has  expertise  in  this area it is certainly possible  that the
methodology is sound, however, given just the information  in the report there is simply no way
for an external reviewer to make this conclusion.
    Because of the lack of hard  information to answer the charge questions, this peer review
evolved mainly into a suggested list of details that should be brought forward in order to allow
the charge questions to be answered properly.  With this information, it is hoped that a person
with expertise in the appropriate areas will be able comment on the work more fully.


Simulation Methodology
 Shawn Midlam-Mohler - Peer Review                                             Page 4

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   The simulation methodology is generally not described in the report in sufficient detail to
assess  the validity and  accuracy of the approach.  The models  and approach are described
qualitatively; however, this is insufficient to truly evaluate the ability of the modeling approach
to perform the desired function.  The following subsections address  specific issues with the
models, inputs, and parameters and suggest possible corrective actions to address these issues.
Vehicle Model
   The vehicle model is described as "a complete, physics-based vehicle and powertrain system
model" developed in the MSC.EasyS™  simulation  environment.    This  description  is  not
particularly helpful in defining the type of model as portions of the model are clearly not physics
based,  such as the various empirical maps used or sub-models like the warm-up model which is
by necessity an empirical model due to the complexity of the warm-up process compared to the
expected level of fidelity of the model. It is assumed that a standard longitudinal model accounts
for rolling losses, aero losses, and grade is used to model the forces acting on the vehicle.  Input
parameters for the vehicle model are not described.  The baseline vehicle platforms are listed,
however, the relevant loss coefficients are not provided (rolling resistance, drag coefficient,
inertia.)
Suggested Corrective Action:
   1.  List the dynamic equation describing the longitudinal motion of the vehicle
   2.  List all parameters used for each vehicle class for simulation
Engine Models
       The engine model is the most important element in  successfully modeling the capability
of future vehicles, since  it is the responsible for the largest loss of energy.  It is also one of the
most difficult aspect to predict since it involves many complicated processes (i.e.  combustion,
compressible flow) which must  be  considered in parallel  with emissions compliance (i.e. in-
cylinder formation, catalytic reduction.)  Because of this, this sub-model must be viewed with
extreme scrutiny in order to ensure quality outputs from the model.
       The engine models are  "defined by their  torque curve, fueling map, and other input
parameters."  This implies that the maps are static representations of fuel consumption  versus
torque, engine speed, and other  unknown input parameters. Generally speaking,  representing
engine performance in this fashion is consistent with typical practice for this class of modeling.
Shawn Midlam-Mohler - Peer Review                                             Page 5

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This comment deals only with the representation of the engine performance in simulation, the
generation of the data contained within the map is much more challenging.
       The report outlines two methods were used to produce engine models.  The first method
was used for boosted engines and relied upon published data on advanced concept engines which
would represent production engines in the 2020-2025 timeframe.  The second method was used
with Atkinson and diesel engines and somehow extrapolated from current production engines to
the 2020-2025 time  frame.   The description of  both of these methods in the report is
unsatisfactory.  It also fails to address how the various technologies are used to build up to a
single engine  map  for a specific powertrain.   Validation, to the extent possible with future
technologies, is also lacking in this area.
       This reviewer took some time to look  at the data via the tool provided.  One table is
shown in Figure 1 which shows some unexpected results. The results are for a small car with the
dry clutch transmission and it shows the baseline engine having superior fuel economy over all
other non-hybrid powertrain options.  This is unexpected behavior and, since there is minimal
transparency in the model, it cannot be investigated any further.
Engines
Baseline
Stoich_DI_Turbo
Lean_DI_Turbo
EGR_DI_Turbo
Atkinson CPS
Atkinson_DVA
FTP
42.1
46.3
48.3
48.2
44.5
45.5
HWFET
62.5
55.3
56.4
57.6
59.0
57.1
US06
37.0
33.7
33.9
35.2
35.4
34.5
   Figure 1: Simulation Results Different Engines for Small Car with 8Dry_DCT and all other Parameters Constant
Suggested Corrective Action:
   1.  Provide fuel and efficiency map data for all engines used in simulation
   2.  Describe what the "other inputs" are to the engine maps
   3.  Provide specific references of which published data was used to predict performance of
       the future engines. Some references are given, however, it is not clear how exactly these
       references are used.
   4.  Wherever possible, provide validation against data on similar technologies
   5.  Describe in detail the approach  used  to "stack up" technologies for a given powertrain
       recipe
Shawn Midlam-Mohler - Peer Review
Page 6

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Aftertreatment/Emissions Solutions
       Based on the report, it seems that emissions solutions are assumed to be available for all
powertrain technology packages selected.  The report discusses this in some qualitative detail in
section  4.2.2 with respect to lean-stoichiometric switching.   This discussion  is  somewhat
incomplete, in that the way it is written it assumes operating at stoichiometry lowers exhaust gas
temperature.  In reality, switching from lean to stoichiometric  operation at constant load results
in higher  exhaust gas temperatures.  Despite this factual inconsistency, it is indeed generally
better to operate a temperature sensitive catalyst hot and stoichiometric or rich rather than hot
and lean - so the concept of lean-stoich switching is valid even  if the explanation provided is not.
Even without this factual  inconsistency, some additional discussion of aftertreatment systems
would be of benefit given that lean-burn gasoline engines are at present a well-known technology
for many years that is still  problematic with respect to emissions control. A separate issue is the
topic of fuel enrichment for  exhaust  temperature management  which will have an  important
impact on emissions  and,  if emissions are  excessive, reduce the peak torque available from an
engine.
Suggested Corrective Action:
    1.  Provide better evidence that powertrain packages have credible paths to meet emissions
       standards
   2.  Provide evidence that fuel enrichment strategies are consistent with emissions regulations

Ail  Mi' ed Valve I rn m s
       Two types of advanced valvetrains were included in the study, cam-profile switching and
digital valve actuation.  Both of these technologies  are aimed at reducing pumping losses at part-
load.   The  impact  of these  technologies is  difficult to predict using  simplified  modeling
techniques and  typically require consideration of compressible flow and a 1-D analysis at  a
minimum. Even with an appropriate fidelity model, these systems require significant amounts of
optimization in  order to determine the best possible performance across the torque-speed plane
of the engine. It is unclear how these systems were used to generate accurate engine maps given
the level of detail provided in the report.
Suggested Corrective Action:
Shawn Midlam-Mohler - Peer Review                                             Page 7

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    1.  Describe how variable valve timing technologies were applied to the base engine maps
    2.  Describe the process of determining the extent of the efficiency improvement
    3.  Describe  how  optimal  valve  timing  was determined  across the variety of engines
       simulated
Direct              Systems
       Because of the availability of research  and production data in this area, it is expected that
performance from this technology was used to predict performance rather than any type of
modeling approach. That being said, the report does not describe where or how this data might
have been used to develop the fuel consumption map of the engines simulated  nor what data
sources were used.

Suggested Corrective Action:
    1.  Cite sources of data used to predict DI performance
    2.  Describe how this data was used to develop the future engine performance maps
    3.  Provide validation of modeling techniques used


       Boosting was applied to many of the  different  powertrain packages simulated.  Beyond
stating what maximum BMEP that was achievable, very little is mentioned in how the efficiency
of the boosted engines were determined. Among other factors, boosting often creates a need for
spark retard which costs efficiency if compression ratio is fixed.  These complex issues are tied
to combustion which is inherently difficulty to  model.  This aspect of the engine model is not
well documented in the report.
Suggested Corrective Action:
    1.  Describe the process of arriving at the boosted engine maps
    2.  Describe how factors like knock are addressed in the creation of these maps


       Engine scaling is  used  extensively in the report.  Basic scaling based on brake mean
effective pressure is common in modeling at  this level of fidelity,  thus,  this does not need any
special description.  However, the report mentions some means of modeling the  increased
Shawn Midlam-Mohler - Peer Review                                             Page 8

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relative heat loss with small displacement engines which is not a standard technique.  The model
or process used to account for this effect should be explicitly described given that engine size is
one of the key parameters in the design space.
Suggested Corrective Action:
    1.  Properly document the process of scaling engines
   2.  Validate the process used to scale engines


   The report describes a 20% factor applied to bag 1 of the FTP-75 for baseline vehicles and a
10% factor applied to the advanced vehicles.   The motivation for these factors is described
qualitatively  and  is valid,  as  many organizations are currently  investigating  strategies  to
selectively heat powertrain components to combat friction effects. However, the values for these
factors that were  selected are not backed up with any data or citation.  It is suspicious that the
two values cited are such round numbers - the data from which these numbers are derived should
be cited.  Because of the  complexity of this phenomenon, some type of empirical  model is
justified. The model described in the report is not sufficiently validated to judge its suitability.
Suggested Corrective Action:
       1.  Cite sources of data for 10% and 20% factors applied to the cold bag fuel  economy
          data
       2.  Cite and/or validate the modeling approach used

Accessory
       The accessory model is divided into electrical and mechanical loads. The electrical sub-
model assumes alternator efficiency's of 55% and 70% for the  baseline and advanced vehicles
respectively.   Given the required simplicity of the model,  a simple  model like this is likely
acceptable, however, there is no  source described for the alternator efficiencies.   The  base
electrical load of the vehicle is mentioned  briefly, however, no numerical values are given for
each vehicle class or any type of model described.
       The electrical system also includes an  advanced alternator  control which  allows for
increased  alternator usage during decelerations for kinetic energy recovery.   The control
description given is valid but simplistic,  but seems to fit the expected level of accuracy required
for the purpose. There is an  issue regarding with the approach  for modeling the battery during
Shawn Midlam-Mohler - Peer Review                                              Page 9

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this process.  When charging the battery at the stated level of 200 amps, the charging efficiency
of the battery will be relatively poor. During removal of the energy later, there will once again
be an efficiency penalty. There is no description of a low-voltage battery model in the report nor
any explicit reference to such charge/discharge efficiencies.  Additionally, an arbitrary limit of a
200 amp alternator is defined for all vehicle classes - it is unlikely that a future small car and a
future light heavy duty truck will have an alternator with the same rating.
       On  the mechanical  side, it is  assumed  that "required accessories"  (e.g. engine water
pump,  engine oil  pump)  are included  in the  engine  maps.  The mechanical loading of a
mechanical fan is mentioned but no description of the model which, at a minimum, should be
adjusted based on engine speed and engine power.
Suggested Corrective Action:
       1.  Cite and/or validate the alternator efficiency values of 55% and 70%
       2.  Account for charge/discharge  losses  in the advanced  alternator control  and/or
          describe the 12V battery model used for the simulation
       3.  Describe, cite, and validate the accessory fan model used in the simulation
       4.  Justify the use of a 200 Amp advanced alternator across all of the vehicle platforms.
                   "Stack-Up"
       There are a host of different technologies superimposed to create the future powertrain
technologies.  There is not a clear process described  on how this technology "stack-up" is
achieved.  For instance,  an advanced engine technology  may allow for greatly improved BMEP.
Greatly improved BMEP often comes at the expense of knock limits which are difficult to model
even with sophisticated modeling techniques.   In this  simulation,  many layers of powertrain
technology are being compounded upon each other which will not simply sum up to the best
benefits of all of the technologies - there are simply too many  interactions.  At  the level of
modeling described, which are maps which are altered in various unspecified ways; it is not clear
how the technology stack-up is captured.
Suggested Corrective Action:
    1.  Describe in greater detail  the  approach used  to model technology  stack-up  on  the
       advanced vehicles
   2.  Provide some form  of validation that this  approach is justified

Shawn Midlam-Mohler - Peer Review                                             Page 10

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Baseline Hybrid Models
The following subsections deal with issues related to the hybrid component models.
Hybrid Control Strategy
      Hybrid vehicles are particularly challenging to model because of the extra components
which allow multiple torque sources, and thus, require some form of torque management strategy
(i.e.  a  supervisory control.)  The report briefly describes  a proprietary supervisory  control
strategy that is used to optimize the control strategy for the FTP, HWFET, and US06 drive cycle.
The  strategy claims to  provide the "lowest possible fuel consumption"  which seems to be
somewhat of an exaggeration - this implies optimality which is quite a burden to achieve and
verify for such a complicated problem.  The strategy also is reported to be "SOC neutral over a
drive cycle" which is also difficult to achieve in practice in a forward looking model. Once can
get SOC  with a certain window, however, short of knowing the future or simply not using the
battery - it is impossible to develop a totally SOC neutral  control strategy.
      Another factor that must be considered is that a hybrid strategy that achieves maximum
fuel  efficiency on FTP, HWFET, and US06  does not  consider many other relevant  factors.
Performance metrics like 0-60 time  and drivability metrics often suffer in practice.  In  today's
hybrids, the number of  stop-start  events is sometimes  limited from the optimum number for
efficiency because of  the emissions concerns.   Because of these factors and others, a strategy
achieving optimal efficiency may be higher than what can be achieved in practice.
      Without even basic details on  the hybrid control strategy, it is simply not possible to
evaluate this aspect of the work. Because of the batch simulations with varying component sizes
and characteristics, this problem is  not trivial.  Supervisory control strategies used in practice and
in the literature require  intimate knowledge of the efficiency characteristics and performance
characteristics of all  of the  components (engine,  electric motors/inverters,  hydraulic braking
system, and energy storage system) to develop control  algorithms.  This concern is amplified by
the lack of validation of the hybrid vehicle model against a known production vehicle.  It is
unclear how a "one-size  fits all" control strategy can be truly be perform near optimal over such
widely varying vehicle platforms.

Shawn Midlam-Mohler  - Peer Review                                            Page 11

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       A  last comment  is that there  is  no validation of  the  HEV model against current
production vehicles.  At  a minimum, the  Toyota Prius has  been dissected sufficiently in the
public domain to conduct  a validation of this class of hybrid electric vehicle.
Suggested Corrective Action:
    1.  Better describe  the hybrid  control strategy and validate  against a current production
       baseline vehicle
    2.  Validate that the HEV control algorithm performs equally well on all vehicle classes
    3.  Validate that other vehicle performance metrics, like emissions and acceleration, are not
       adversely impacted by an algorithm that focuses solely on fuel economy.  The emission
       side of things will challenge to validate with this level of model, however,  some kind of
       assurance should be made to these factors which are currently not addressed at all.
Electric Traction Components
       The model  of electric traction components is not discussed in any detail, as the  only
mention in the report is that current technology systems were altered by "decreasing losses in the
electric machine and power electronics." Given the importance of the electric motor and inverter
system in hybrids this is not acceptable.
Suggested Corrective Action:
    1.  Describe the method used to model electric traction components
    2.  Provide  validation/basis  for the  process used to generate future technology versions of
       these components
    3.  Describe the technique used to scale these components

HEV
       Battery models for HEVs are necessary to adequately model the performance of an HEV.
The report provides no substantive description of the battery pack model, other  than that the
model was developed by "lowering internal  resistance in the  battery  pack to represent 2010
chemistries under development." Battery pack size is also not a currently a factor in the model -
this has a impact of charge and discharge efficiency of the battery pack.
Suggested Corrective Action:
    1.  Describe the method used to model the HEV battery

Shawn Midlam-Mohler -  Peer Review                                             Page 12

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   2.  Provide validation/basis for the process used to generate future technology versions of the
       battery
   3.  Describe the technique used to scale the HEV battery

Transmissions
       This peer  reviewer  is not as well-practiced  in transmissions as in  other areas in  this
review. Because  of this, a  more limited review was conducted of this aspect of the report.  As
with the other areas of the report, the general  concern in this  area is  the inadequacy of
documentation of the modeling  approach and validation.  Generically, the same issues noted
above are applicable here:
   1.  Cite data sources used in modeling
   2.  Validate models wherever possible
   3.  Fully describe transmission models/maps and processes used to generate them
   4.  Fully describe clutch/torque converter models/maps and processes used to generate them
   5.  Fully describe the process used to generate shift maps and the operation of the shift
       controller
   6.  Fully describe the lockup  controller (i.e. how soon can it enter lockup after shifting?)
   7.  Fully describe the process for modeling torque holes during shifting
   8.  Fully describe the model used for the final drive (i.e. inputs/structure/outputs)


Data Analysis Tool
       The vehicle simulator is used to generate several  thousand simulations using a DOE
technique.  This data is then fit with a neural-network-based response surface model in which the
"goal was to achieve low residuals while not over-fitting the data." This response surface model
then becomes the method  from  which vehicle design performance is estimated in the data
analysis tool. In this case, the response surface model is nothing more than a multi-dimensional
black-box curve fit.  There  was no error analysis given in the report regarding this crucial step.
By way  of example, the vehicle simulator could provide near perfect predictions of future
vehicle performance; however, a bad response surface fit could corrupt all of the results.
Shawn Midlam-Mohler - Peer Review                                            Page 13

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Suggested Corrective Action:
                                                              r\
    1.  Provide error metrics  for the neural network RSMs (i.e.  R ,  min absolute error, max
       absolute error, error histograms, error standard deviation, etc.) before combining the fit
       and validation data sets
    2.  Provide the  error metrics described above for the RSMs after  combining the fit and
       validation data sets
    3.  Provide validation that the data analysis tool correctly uses the RSM to predict results
       very close to the source data (i.e. demonstrate the GUI software behaves as expected)
Conclusions
   As outlined in the executive summary, it was not possible to answer the charge questions
provided for this peer review due to lack of completeness in the report.  Thus, this report was
aimed at providing feedback on what information would be helpful to allow a reviewer to truly
evaluate the spirit of the charge questions. With the above in mind, the following conclusions are
made.
   The modeling approach describe in the report could be appropriate for the simulation task
required  and is generally consistent with approaches used by other groups in this field.  The
conclusions from the report could very well be sound; however, there is insufficient information
and validation provided in  the report to determine if this is the case. The technique used to
analyze the mass simulation runs could also be sound, although  the  accuracy of the  response
surface model is not cited in the report.
   These issues are summarized in the following key areas:
       1.  The  process of arriving at the performance of the future technologies is  not  well
          described
       2.  The majority of models are only described qualitatively making it hard or impossible
          to judge the soundness of the model
       3.  Some of  the  qualitative descriptions of the  models  indicate  that models do not
          consider some important factors
       4.  Because of the qualitative nature of the model descriptions, there is a major lack of
          transparency in the inputs and parameters in the models

Shawn Midlam-Mohler - Peer Review                                             Page 14

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       5.  Where precise value(s) are given for parameters in the model, the report generally
          does not cite the source of the value(s) or provide validation of the particular value
       6.  Validation of the model  and sub-models is not satisfactory (It is acknowledged that
          many of these technologies do not exist, but the parameters and structure of the model
          have to be based on something.)
Shawn Midlam-Mohler - Peer Review                                            Page 15

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                       Review of the report
COMPUTER SIMULATION OF LIGHT-DUTY VEHICLE TECHNOLOGIES
         FOR GREENHOUSE GAS EMISSION REDUCTION
                 IN THE 2020-2025 TIMEFRAME
                          17 May 2011
                          Prepared for

                        ICF International
               Environmental Science & Policy Division
                   Contracts Management Group
             9300 Lee Highway, Fairfax, VA 22031-1207 USA
                      Robert F. Sawyer, PhD
                                   Partner

                  SAWYER ASSOCIATES
                              PO Box 6256
           Incline Village, NV 89450-6256 USA
                         Phone 1-510-305-6602
             email: rsawyer@sawyerassociates.us

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OVERVIEW

This is a review of the report, Computer simulation of light-duty vehicle technologies for
greenhouse gas emission reduction in the 2020-2025 timeframe, 6 April 2011, prepared by
Ricardo, Inc. Additionally the "Complex System Tool," which uses the results of about 500,000
computer simulations to generate fuel economy and CC>2 emissions for combinations of vehicle
architectures, engines, and transmissions was examined. Up to 11 parameters may be varied
within constrained limits to explore the sensitivity of fuel economy and CC>2 emissions. Jeff
Cherry of USEPA/OTAQ assisted in the installation and running of the tool. Examination of the
tool provided additional perspective on how the computational results are to be used and the
nature of some of the hidden assumptions. This review does not include the Complex System
Tool, except as it may reveal the nature of the computer simulation.

Computer simulation of light-duty vehicle technologies for greenhouse gas emission reduction in
the 2020-2025 timeframe describes engine and vehicle technologies that are or could be available
to improve light-duty vehicle efficiency and thereby reduce carbon dioxide emissions. It does not
treat other greenhouse gas emissions or alternative fuels. The Federal Test Procedure (FTP)
framework for vehicle certification constrains the analysis, thereby excluding technologies
related to vehicle downsizing, reduced performance, and "real world" operation such as driver
behavior compensation, air  conditioning and heating load management, and loads as affected by
speed, acceleration, turning, hills, and wind, all of which are outside of the certification tests.

The work includes the integration of selected technologies through a "data visualization tool"
(The Complex System Tool) for assessment of user-elected technologies. The technologies
include both drive-train technologies and technologies to reduce vehicle load, such as drag
reduction, rolling resistance reduction, light weighting, and improved accessories efficiency (but
limited to intelligent cooling systems and electric power steering). Seven light-duty vehicle types
represent the 2010 baseline  and future 2020-2025 fleets. Battery electric vehicles (BEVs), plug-
in hybrid electric vehicles (PHEVs), and fuel-cell electric vehicles (FCEVs) are not included.

The report describes, qualitatively, the technologies considered in a clear, logical fashion.
Because of its proprietary nature, quantitative performance data, such as engine maps, are
missing from the report and not accessible for this review.

REVIEW

This review  follows the structure of the 'charge questions".

   (1) Inputs and Parameters. Please comment on the adequacy of numerical inputs to the
       model as represented by default values, fixed values, and user-specifiable parameters.
       Examples might include: engine technology selection, battery SOC swing, accessory load
       assumptions, etc.) Please comment on any caveats or limitations that these inputs and
       parameters would affect the final results.

The vehicle  classes and baseline exemplars are reasonably chosen, within the constraint that
vehicle size, footprint, and interior volume for each class be locked to the 2010 base year. It is

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likely that new vehicle classes will emerge by 2025 and/or that these "locking" restraints will be
relaxed.

The design of experiment (DoE) ranges, Tables 5.4, 5.5, 8.1, and 8.2, are reasonable and do not
exclude likely sizings. The assumed alternator baseline and advanced alternator efficiencies are
reasonable. The assumed reduction in automatic transmission losses is reasonable, but not
aggressive for 15 development years from the baseline year. Similarly the state-of-charge swing
for hybrid modeling of 30-70% is reasonable, but does not reflect improved battery technology
for the 2020-25 period, which should allow a greater swing for reduced battery size, weight, and
cost.

   (2) Simulation methodology. Please comment on the validity and applicability of the
      methodologies used in simulating these technologies with respect to the entire vehicle.
      Please comment on any apparent unstated or implicit assumptions and related caveats or
      limitations.  Does the model handle synergistic affects of applying various technologies
      together?

Ricardo simulated dynamic vehicle physical behavior using MSC EasyS   software with 10
Hz time resolution. This software and the time resolution are appropriate for the
computations to show the effect of component interactions on  vehicle performance. 10
Hz time resolution is sufficient to capture both driver behavior and vehicle response.
Should the application of information technology, as is being implemented, as a means of
vehicle control for reducing fuel consumption become  a future strategy, the model should
be able to provide a suitable simulation.

Drivetrain synergistic effects seem to be predicted reasonably. This was demonstrated by
calculation of fuel economy of the baseline vehicles and comparison with EPA
certification test data.  The model does not seem to have the capability to capture vehicle
weight-drivetrain synergistic effects. Vehicle weight reductions associated with drivetrain
efficiency improvements are input rather than modeled internally. This is an important
deficiency. Similarly,  from the Complex System Tool,  weight  reductions do not seem to
result in reduction in engine displacement.

   (3) Results. Please comment on the validity and applicability of the results to the light-duty
      vehicle fleet in the 2020-2025 timeframe. Please comment on any apparent unstated or
      implicit assumptions that may affect the results, and on any  related caveats or
      limitations.

Performance calculations tied to the FTP, HWFET, and US06 test cycles do not adequately
capture vehicle behavior under real-world operation. Therefore, technologies that address
improving fuel economy under real-world operation are either excluded or their contribution not
included. The application of a 20% reduction in fuel economy to the FTP75 bag 1 portion of the
drive  cycle for 2010 baseline vehicles and 10% for 2020-2025 is crude, arbitrary, and treats only
one of many problems with the driving simulation in the test cycles. Test cycle difficulties carry
over into the simulation of hybrid control strategies.

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It is conceivable that BEVs and PHEVs (and less likely FCEVS) will be a significant part of the
2020-2025 vehicle fleet. That they are excluded from the model is a deficiency.

   (4) Completeness. Please comment on whether the report adequately describes the entire
       process used in the modeling work from input selection to results.

The selection of drivetrain technologies (other than the electric storage technologies) is
comprehensive. The qualitative description of the drivetrain technologies is complete and clear,
but quantitative performance data are missing. Transparency in the actual performance data is
entirely lacking. This includes engine performance maps, shift strategies, battery management in
hybrids, and more. That much of that data is proprietary to the companies that generated it and/or
to Ricardo is a problem for what is proposed as a regulatory tool.

The assumptions are difficult to extract from the text.

   (5) Recommendations. Please comment on the overall adequacy of the report for predicting
       the effectiveness of these technologies, and on any improvements that might reasonably
       be adopted by the authors for improvement. Please note that the authors intend the
       report to be open to the community and transparent in the assumptions made and the
       methods of simulation.  Therefore recommendations for clearly defined improvements
       that would utilize publicly available information would be preferred over those that
       would make use of proprietary information.

The failure to model the drivetrain-weight interactions  is a major shortcoming. Appendix 2
should clearly  state that vehicle weights are held constant (assuming that I am correct in that
assumption).

There should be a table describing the baseline  vehicles.

Summarizing assumptions in tabular form would be a great assistance to the reader.

The design space should be expanded to include performance parameters, such as power/weight
or 0-60 times.

   (6) Other comments.  Please provide your comments on report topics not otherwise  captured
       by the aforementioned charge questions.

The conclusions, Section 11, are a reasonable summary of the work conducted.

Including the membership of the advisory committee would be appropriate.

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 Peer review of the report, "Computer Simulation of Light-Duty Vehicle Technologies for
            Greenhouse Gas Emission Reduction in the 2020-2025 Timeframe"
                             Report by:  Wallace R. Wade
                             Date of Report: May 15, 2011
Charge to Peer Reviewers:
       As EPA and NHTSA develop programs to reduce greenhouse gas (GHG) emissions and
increase fuel economy of light-duty highway vehicles, there is a need to evaluate the
effectiveness of technologies necessary to bring about such improvements.  Some potential
technology paths that manufacturers might pursue to meet future standards may include
advanced engines, hybrid electric systems,  mass reduction, along with additional road load
reductions and accessory improvements.

       Ricardo Inc. has developed simulation models including many of these technologies with
the inputs, modeling techniques, and results described in the Ricardo Inc.  document that you
have been provided dated March 10, 2011 (version received was dated April 6, 2011).

       EPA is seeking the reviewers' expert opinion on the inputs, methodologies, and results
described in this document and their applicability in the 2020-2025 timeframe.  The Ricardo Inc.
report is provided for review.  We ask that  each reviewer comment on all  aspects of the Ricardo
Inc. report.  Findings of this peer review may be used toward validation and improvement of the
report and to inform EPA and NHTSA staff on potential use of the report for predicting the
effectiveness of these technologies. No independent data analysis will be required for this
review.

       Reviewers are asked to orient their  comments toward the five (5) general areas listed
below. Reviewers are expected to identify  additional topics or depart from these general areas as
necessary to best apply their particular set of expertise toward review of the report.

       Comments should be sufficiently clear and detailed to allow readers familiar with the
report to thoroughly understand their relevance  to the material provided for review. EPA
requests that the reviewers not release the peer review materials or their comments until Ricardo
Inc. makes its report and supporting documentation public. EPA will notify the reviewers when
this occurs.

       Below you will find a template for your comments. You are encouraged to use this
template to facilitate the compilation  of the peer review comments, but do not feel  constrained by
the format.  You are free to revise as needed; this is just a starting point.

       If a reviewer has questions about what is required in order to complete this  review or
needs additional background material, please contact Susan Elaine at ICF International
(SBlaine@icfi.com or 703-225-2471). If a  reviewer has any questions about the EPA peer review
process itself, please contact Ms. Ruth Schenk in EPA's Quality Office, National Vehicle and
Fuel Emissions Laboratory by phone (734-214-4017) or through e-mail (schenk.ruth@epa.gov).
                                                                           W. R. Wade
                                                                              5/15/2011

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Charge Questions:

(1) Inputs and Parameters. Please comment on the adequacy of numerical inputs to the model
as represented by default values, fixed values, and user-specifiable parameters. Examples might
include: engine technology selection, battery SOC swing, accessory load assumptions, etc.)
Please comment on any caveats or limitations that these inputs and parameters would affect the
final results.

A. Baseline vehicle subsystem models/maps

      - The development of baseline vehicle models with comparison of the model
      results to available 2010 EPA fuel economy test data was appropriate.

            - The models/maps for the subsystems used in these vehicle models
            were not provided in the report so that their adequacy could not be
            assessed.

            - Including these baseline models in the report would assist in assessing
            the development process as well as the adequacy of the new technology
            subsystem models/maps, which was not possible in this peer review.

            Recommendation:  Since the baseline vehicles modeled were 2010
            production vehicles, the models/maps for the subsystems used in
            these vehicle models should be included  in the report before it is
            released.

      - A major omission was that a baseline model  of a hybrid vehicle, which is
      significantly more complex than the baseline vehicle, was not developed and
      compared to available EPA fuel economy test data for production hybrid vehicles.

            Recommendation:  A baseline model of a hybrid vehicle should be
            developed and compared to 2010 EPA fuel economy test data for
            production hybrid vehicles.

B. Engine technology selection

      - The engine technologies selected for this study, listed in Table 5.1 (page 22),
      are appropriate, but are not all-inclusive of possible future engine technologies.

            - Setting the minimum per-cylinder volume at 0.225L and the minimum
            number of cylinders at 3 is appropriate.  However, achieving customer
            acceptable NVH with 3 cylinder engines continues to be problematic.

            Issue: The description of the derivation of all of the engine
            models/maps was insufficient.
                                                                    W. R. Wade
                                                                      5/15/2011

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            Issue:  The technology "package definitions" precluded an
            examination of the individual effects of a variety of technologies
            such as a single stage turbocharger vs. series-sequential
            turbochargers.

            Issue: There are many engine technologies that have potential for
            reduced GHG emissions that were not included in this study, such
            as:
            •   Single stage turbocharged engines
            •   Diesel hybrids
            •   Biofueled spark ignition and diesel engines
            •   Natural gas fueled engines
            •   Other alternative fuel engines
            •   Charge depleting PHEV and EV

      -  The feasibility of the following assumptions for the engines modeled should be
      re-examined as indicated below.

            -  None of the Stoichiometric Dl Turbo engines listed as references by
            Ricardo limited  the turbine inlet temperature to a value as low as the 950C
            limit in the Ricardo model (Ref 1, 2, 3). Reducing the turbine inlet
            temperature to reach this limit is expected to result in BMEP levels below
            the assumed 25-30 bar level in the model (which were obtained in  the
            referenced engine with a turbine  inlet temperature of 1025C).

            -  Turbocharger delays of the magnitude assumed in the model will result
            in significant driveability issues for engines that are downsized
            approximately 50%.  Although Ricardo assumed a turbocharger delay of
            approximately 1.5 seconds, the comparable delay published for a
            research engine was significantly longer at 2.5 seconds (Ref 3).

Transmission technology selection

      -  The transmission technologies selected for this study, listed in Table 5.3 (page
      23) are appropriate.

            -  The forecast that current 4-6 speed automatic transmissions will  have 7-
            8  speeds by 2020-2025 is appropriate for all except the smallest and/or
            low cost vehicles (page 19).

            -  The report mentions that the transmissions include dry sump, improved
            component efficiency, improved kinematic design, super finish, and
            advanced driveline lubricants (page 22).

            Recommendation:  The detailed assumptions showing how the
            benefits of dry sump, improved component efficiency, improved


                                      3                             W.  R. Wade
                                                                    5/15/2011

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            kinematic design, super finish, and advanced driveline lubricants
            were added to the transmission maps should be added to the report
            before it is released.

C. Hybrid technology selection

      -  The hybrid technologies selected for this study, listed in Table 5.2 (page 22)
      are appropriate.

            Issue: The adequacy of the P2 Parallel and PS Power Split Hybrid
            systems cannot be determined without having, at a minimum,
            schematics and operational characteristics of the each system
            together with comparisons with today's hybrid systems.

      -  Although not contained in the report, the teleconference call with Jeff Cherry
      (EPA) on May 5, 2011 revealed that 90% of the deceleration kinetic energy
      would be recovered.
            Kinetic energy recovery is limited by the following:
               •   Maintaining high generator efficiency over the range of speeds and
                  resistive torques encountered during deceleration
               •   Limitations on the rate at which energy can be stored in the battery
               •   Losses in the power electronics
               •   Some energy is lost when energy is withdrawn from the battery for
                  delivery to the motor.
               •   Inefficiencies in the motor at the speeds and torques required.
            The inefficiencies of each of these four subsystems are in series and are
            compounded.  If each subsystem had 90% efficiency, the kinetic energy
            recovery efficiency would be only 66%.

            Issue: Capturing 90% of the deceleration kinetic energy is a
            significantly goal. The technology to be used to achieve this goal
            needs to be explained and appropriate references added to the
            report.

D. Actual models/maps for subsystems (engine, transmission, hybrid system,
accessories, final drive, tires and vehicle)

      -  None of the subsystem models/maps were provided for review so comments
      on their adequacy are not possible.

            Issue: Insufficient reasons are presented to justify why the
            models/maps for subsystems are not provided in the report,
            especially when one of the goals of the report was to provide
            transparency (per Jeff Cherry, May 5, 2011 teleconference and Item 5,
            below).
                                                                   W. R. Wade
                                                                     5/15/2011

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            Recommendation: Subsystem models/map should be added to this
            report and another peer review conducted to assess their adequacy
            before this report is released.

            Recommendation: To establish the adequacy of the subsystem
            models/maps, derivation details should be provided.

E.  Accessory load assumptions

      - The accessory selections listed in Table 5-2 (page 22) appear to be adequate
      except for the following issue:

            Issue: Belt driven air conditioning for the stop-start powertrain
            configuration is not acceptable for driver comfort. Electrically driven
            air conditioning is required for the stop-start powertrain
            configuration to provide driver comfort for extended idle periods.

      - Input values

            - Alternator efficiency was increased from the current level of 55% to 70%
            to reflect "an improved efficiency design" (page 26 and 27).

            Comment: Justification for the increase in alternator efficiency from
            55% to 70% should be added to the report with references provided.
            Alternator efficiency as a function of speed and load may be more
            appropriate than a constant value.

      - Accessory power requirements were not provided, such as shown in Figure 3-3
      of Reference 4, for example.

            Recommendation: Both mechanically driven and electrically driven
            accessory power requirements should be clearly provided in the
            report.

F.  Battery SOC swing and  SOC

      - Although not contained in the report, an email from Jeff Cherry (EPA) on May
      5, 2011 revealed that the SOC swing was 30% SOC to 70% SOC or 40% total,
      which appears to be appropriate.

      - Achieving neutral SOC  (neither net accumulation or depletion) for hybrid
      vehicle simulations is appropriate (page 30).
                                                                 W. R. Wade
                                                                   5/15/2011

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G. DOE ranges
      - The following DOE ranges for Baseline and Conventional Stop-Start (page 23)
      appear to be appropriate, with the exception of Engine Displacement, as
      discussed below.
Parameter
Engine Displacement
Final Drive Ratio
Rolling Resistance
Aerodynamic Drag
Mass
DoE Range (%)
50 125
75 125
70 100
70 100
60 120
      Since the default for the Stoichiometric Dl Turbo engine appears to be greater
      than 50% reduction in displacement (Standard Car baseline of 2.4L is reduced to
      1.04L for the Stoichiometric Dl Turbo (page 46)), the opportunity should be
      provided to start with a displacment near the baseline engine (2.4L) and
      progressively decrease it to approximatly 50% (1.04L).  This would require an
      Engine Displacement upper range of over 200%.  The model should also have
      the capabilty of increasing the boost pressure as the displacement is reduced.

      - The following DOE ranges for P2 and PS hybrid vehicles (page 24) appear to
      be appropriate:
Parameter
Engine Displacement
Final Drive Ratio
Rolling Resistance
Aerodynamic Drag
Mass
Electric Machine Size
DoE Rs
P2 Hybrid
50 150
75 125
70 100
70 100
60 120
50 300
nge (%)
Powers plit
50 125
75 125
70 100
70 100
60 120
50 150
H. Other inputs
      - The Design Space Query within the Data Visualization Tool allows the user to
      set a continuous range of variables within the design space range. Although this
      capability is useful for parametric studies, the following risks are incurred with
      some of the variables.

            - The sliders for "Eng. Eff" and "Driveline Eff." would allow the user to
            arbitrarily change engine efficiency or driveline efficiency uniformly over
            the map without having a technical basis for such changes.

            - The slider for weight would allow the user to add hybrid or diesel
            engines with signficant weight increases without incurring any vehicle
            weight increase.
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                                                                       5/15/2011

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Recommendation:  A default weight increase/decrease should be
added for each technology. If weight reductions are to be studied,
then the user should have to input a specific design change, with the
appropriate weight reduction built into the model, rather that having
an arbitrary slider for weight.
                                                     W. R. Wade
                                                       5/15/2011

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(2) Simulation methodology. Please comment on the validity and applicability of the
methodologies used in simulating these technologies with respect to the entire vehicle. Please
comment on any apparent unstated or implicit assumptions and related caveats or limitations.
Does the model handle synergistic affects of applying various technologies together?

Concern: Methodologies used in simulating the subsystems and the overall
vehicles were not provided, so that the validity and applicability of these
methodologies cannot be assessed.

A. Major deficiencies in the report

      - An overall schematic and description of the powertrain and vehicle models and
      the associated subsystem models/maps were not provided.  Only vague
      descriptions were included in the text of the report.

      - Technical descriptions of how the subsystems and vehicle models/maps for the
      baseline vehicles were developed were not provided.

      - Most importantly, only non-technical descriptions of how each of the advanced
      technology subsystem models/maps was developed were provided.

      - Descriptions of the algorithms used for engine control,  transmission control,
      hybrid system control, and accessory control were not provided.

      - Descriptions of how synergistic effects were handled were not provided.

B. Baseline vehicle  model validation results

Ricardo developed baseline vehicle simulations for 2010 vehicles for which EPA fuel
economy data were  available (page 30).  "For the 2010 baseline vehicles, the engine
fueling maps and related parameters were developed for each specific baseline
exemplar vehicle." (page 25). Even though these are production vehicles, the models
and maps used were not described (including whether they were derived from actual
measurements or models) and they were not provided in the report so that their
appropriateness could not be assessed.

Table 7.1 shows the calculated vs.  EPA test data for the baseline vehicle fuel economy
performance. This table should include percentage variation of the model calculations
vs. the test data.  The agreement of the model with the test data is within 11 %, but this
is a larger error than some of the incremental changes shown in Appendix 3.  A closer
agreement would have been expected.

      Recommendation: A closer examination of the reasons for the up to 11%
      discrepancies between the models and baseline vehicles' EPA fuel
      economy test data should be undertaken so that the  models could be
      refined to provide better agreement.


                                       8                            W. R. Wade
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C. Transmission optimization

A transmission shift optimization strategy is presented in the report and the results are
shown in Figure 6.1 (page 28). This figure shows very frequent shifting, especially for
4th, 5th and 6th gears.

      Issue: Optimized shift strategies of the type used by Ricardo have been
      previously evaluated and found to provide customer complaints of "shift
      busyness". Customers  are likely to reject such a shift strategy.

D. Vehicle model issues

Although the report described the major powertrain subsystems included in the vehicle
models (page 24), a description of the vehicle model was not provided.

      Issue: A description of how aerodynamic losses, tire rolling losses and
      weight are handled in the model was not provided.

E. Additional discussion of deficiencies is contained in Section 6, Other Comments.
                                                                    W. R. Wade
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(3) Results. Please comment on the validity and applicability of the results to the light-duty
vehicle fleet in the 2020-2025 timeframe. Please comment on any apparent unstated or implicit
assumptions that may affect the results, and on any related caveats or limitations.

A. Overview of results

The results from this work could be useful in evaluating possible GHG emission
reductions in the 2020-2025 timeframe if the issues throughout this peer review were
addressed and the recommendations in Item 5 (below) were implemented.  However,
even if the foregoing deficiencies were  resolved, the foregoing caveat that there are
numerous technologies that have potential for reduced GHG emissions that were not
included in this study must be recognized (see  Item 1B, above).

B. Sample runs of CSM

In the review process, several sample runs of the Complex Systems Model (CSM) for
the Standard Car (Toyota Camry) were made and the results are shown in the attached
chart (at the end of this peer review)  and summarized below.

- Baseline engine with AT6-2010 to Stoichiometric Dl Turbo, Stop-Start, AT8-2020
      •   38.7% improvement in M-H mpg
      •   Reference 3 identified a 25-30% improvement in mpg for a 50% downsized,
         Dl, Turbo engine.
      •   The remaining 9-14% potentially could be explained by stop-start and the
         change from AT6-2010 to AT8-2020  (although the details of the systems and
         the models used would be needed to make this assessment).

- AT8-2020 to DCT
      •   3.3% improvement in M-H  mpg
      •   This improvement appears reasonable.

- Stoichiometric Dl Turbo with Stop-Start to P2 Hybrid
      •   18.2% improvement in M-H mpg
      •   This improvement appears reasonable.

- Stoichiometric Dl Turbo with Stop-Start to PS Hybrid
      •   11.1% improvement in M-H mpg
      •   A detailed explanation of the differences in the improvements between the P2
         and PS hybrids should be provided in the report, especially  considering that
         the P2 hybrid has better fuel  economy and uses a 70% smaller electric motor
         (24 vs. 80 kW).

- Stoichiometric Dl Turbo PS Hybrid to Naturally Aspirated Atkinson CPS Hybrid
      •   Loss of 2.3% M-H mpg (From Stoichiometric Dl Turbo PS Hybrid)
                                      10                           W. R. Wade
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      •   The details of the Naturally Aspirated Atkinson CPS Hybrid should be
         provided to explain the nearly equal fuel economy to the Stoichiometric Dl
         Turbo PS Hybrid.

- Stoichiometric Dl Turbo PS Hybrid to Naturally Aspirated Atkinson DVA Hybrid
      •   2.1% M-H mpg improvement in M-H mpg (From Stoichiometric Dl Turbo PS
         Hybrid)
      •   The details of the Naturally Aspirated Atkinson DVA Hybrid should be
         provided to explain the nearly equal fuel economy to the Stoichiometric Dl
         Turbo PS Hybrid

C. Issue with CSM

      Issue:  The technology "package definitions" (page 22 and 23) precluded
      an examination of the individual effects of a variety of technologies.

      Some examples where the model did not allow a build up of comparison cases
      are:
      •   Baseline engine with AT-2010 to AT-2020 to DCT
      •   Baseline engine without stop-start to with/stop-start

D. Other issues:

•  The Advanced Diesel does not appear to be modeled for the Standard Car and
   Small MPV (page 46 and 47), yet no reason was provided.

•  The P2 and PS hybrid system  was not modeled for the LHDT (page 47), yet no
   reason was provided.

•  When the baseline cases were run  in the Complex Systems Model, incorrect values
   of displacement and architecture were shown in the output.
      o  As an example shown on the attached chart (copied from the output of the
         CSM), the baseline for the Standard Car with a 2.4L engine shows a
         displacement of 1.04L
      o  For the same example,  the architecture  is shown as "conventional SS",
         whereas the baseline was understood to not have the stop-start feature (page
         22, Table 5-2).
                                     11                            W.R. Wade
                                                                    5/15/2011

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(4) Completeness. Please comment on whether the report adequately describes the entire
process used in the modeling work from input selection to results.

Concern: This report has significant deficiencies in its description of the entire
process used in the modeling work.  Many of these deficiencies have been
previously discussed, but are listed here for completeness.

•  An overall schematic and description of the  powertrain and vehicle models and the
   associated subsystem models/maps were not provided. Only vague descriptions
   were included in the text of the report.

•  Technical descriptions of how the subsystems and vehicle models/maps for the
   baseline vehicles were developed were not  provided.

•  None of the overall or subsystem models/maps were provided for review so
   comments on their adequacy are not possible.

•  Most importantly, only minimal descriptions were provided of how each of the
   advanced technology subsystem models/maps was developed.

•  Descriptions of the algorithms used for engine control, transmission control, hybrid
   system control, and accessory control were  not provided.

•  Descriptions of how synergistic effects were handled were not provided.

There are many engine technologies that have potential for reduced GHG
emissions that were not included in this study, such as:
•  Single stage turbocharged engines
•  Diesel hybrids
•  Biofueled spark ignition and diesel engines
•  Natural gas fueled engines
•  Other alternative fuel engines
•  Charge depleting PHEV and EV

Additional discussion of completeness is contained in  Item 6, Other Comments.
                                      12                            W. R. Wade
                                                                     5/15/2011

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(5) Recommendations. Please comment on the overall adequacy of the report for predicting the
effectiveness of these technologies, and on any improvements that might reasonably be adopted
by the authors for improvement. Please note that the authors intend the report to be open to the
community and transparent in the assumptions made and the methods of simulation. Therefore
recommendations for clearly defined improvements that would utilize publicly available
information would be preferred over those that would make use of proprietary information.

This report needs major enhancements to reach the stated goal of being open and
transparent in the assumptions made and the methods of simulation.
Recommendations to rectify the deficiencies in these areas are provided in the previous
four items.

A. Overall recommendations

Overall Recommendation: Provide all vehicle and powertrain models/maps and
subsystem models/maps used in the analysis in the report so that they can be
critically reviewed.

Overall Recommendation: Expand the technology "package definitions" to
enable evaluation of the individual effects of a variety of technologies.

B. Specific recommendations for improvements

1.  Provide an overall schematic and description of the powertrain and vehicle models.
      a. Show all of the subsystem models/maps used in the overall model.
      b. Show the format of the information in each of the subsystem models
      (including input, subsystem model, output).

2.  Provide technical descriptions of how the subsystems and vehicle models/maps for
the baseline vehicles were developed.

3.  Provide overall system and subsystem models/maps in the report.

4.  Provide detailed technical descriptions of how each of the advanced technology
subsystem models/maps was developed.

5.  Provide descriptions of the algorithms used for engine control, transmission control,
hybrid system control, and accessory control.

6.  Provide detailed descriptions of how synergistic effects were handled.
                                       13                             W. R. Wade
                                                                       5/15/2011

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C. Additional recommendations shown in bold print throughout other sections of this
report are repeated below for completeness (in the order that they appear in the report).

Recommendation: Since the baseline vehicles modeled were 2010 production
vehicles, the models/maps for the subsystems used in these vehicle models
should be included in the report before it is released.

Recommendation: A baseline model of a hybrid vehicle should be developed and
compared to 2010 EPA fuel economy test data for production hybrid vehicles.

Recommendation: The detailed assumptions showing how the benefits of dry
sump, improved component efficiency, improved kinematic design, super finish,
and advanced driveline lubricants were added to the transmission maps should
be added to the report before it is released.

Recommendation: Subsystem models/map should be added to this report and
another peer review conducted to assess their adequacy before this report is
released.

Recommendation: To establish the adequacy of the subsystem models/maps,
derivation details should be provided.

Recommendation: Both mechanically driven and electrically driven accessory
power requirements should be clearly provided in the report.

Recommendation: A default weight increase/decrease should be added for each
technology.  If weight reductions are to be studied, then the user should have to
input a specific design change, with the appropriate weight reduction built into
the model, rather that having an arbitrary slider for weight.

Recommendation: A closer examination of the reasons for the up to 11%
discrepancies between the models and baseline vehicles' fuel  economy test data
should be undertaken so that the models could be refined to provide better
agreement.

D. There are numerous "Issues" identified throughout this peer review that need to be
addressed with specific resolution actions.
                                    14                           W. R. Wade
                                                                  5/15/2011

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(6) Other comments. Please provide your comments on report topics not otherwise captured by
the aforementioned charge questions.

Overview

The vehicle model and powertrain model were developed and implemented by Ricardo
in the MSC.EasyS software package. The model reacts to driver input to provide the
torque levels and wheel speeds required to drive a specified vehicle over specified
driving cycles. The overall model consists of subsystem models that determine key
component outputs such as torque, speeds, heat rejection, and efficiencies. Subsystem
models are expected to be required for the engine, accessories, transmission, hybrid
system (if included), final drive, tires and vehicle, although the report did not clearly
specify the individual subsystem models used.

A design of experiments (DOE) matrix was constructed and the vehicle models were
used to generate selected performance, fuel economy and GHG emission results over
the design space of the DOE matrix.  Response surface modeling (RSM) was
generated  in the form of neural networks. The output from each model simulation run
was used to develop the main output factors used in the fit of the RSM. The resulting
Complex Systems Model (CSM) provides a useful tool for viewing the results from this
analysis that included over 350,000 individual vehicle simulation cases.
Overall Issue:

The vehicle and powertrain models/maps and subsystem models/maps used in
the analysis were not provided in the report and could not be reviewed. In most
cases, the report stated that the models/maps were either proprietary to Ricardo
or at least elements were proprietary so that they could not be provided for
review.  Without having these models/maps and subsystem models/maps, their
adequacy and suitability cannot be assessed.

Overall Recommendation: Provide all vehicle and powertrain models/maps and
subsystem models/maps used in the analysis in the report so that they can be
critically reviewed.

Overall Issue:

The technology "package definitions" preclude an examination of the individual
effects of a variety of technologies.  For example, for the Stoichiometric Dl Turbo
engine, only the version with a series-sequential turbocharger could be evaluated
whereas a lower cost alternative with a single turbocharger could not be
evaluated.  Likewise, only the AT8-2020 transmission could be evaluated with the
Stoichiometric Dl  Turbo engine, while the substitution of the AT6-2010, as a lower
cost alternative, could not be evaluated.
                                     15                           W.R. Wade
                                                                    5/15/2011

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Overall Recommendation:  Expand the technology "package definitions" to
enable evaluation of the individual effects of a variety of technologies.
This section provides additional details regarding the overall issues and comments
made in the foregoing five items.

Engine Models

Engine models provided the torque curve, fueling map and other input parameters
(which were not specified in the report) (page 25).  Since the report stated that "The
fueling maps and other engine model parameters used in the study were based on
published data and Ricardo proprietary data" (page 26), their adequacy and suitability
could  not be assessed.

The report states that engines used in the model were developed using two main
methods (page 14).
   1.  The first method assumed that "reported performance of current research
      engines" would closely resemble production engines of the 2020-2025
      timeframe.
   2.  The second method began with current production engines and then a "pathway
      of technology improvements over the new 10-15 years that would lead to an
      appropriate engine configuration for the 2020-2025 timeframe" was applied.
Both of these approaches are reasonable if:
   1.  appropriate references are provided,
   2.  the reported performances for the research engines used are documented  in the
      report,
   3.  the technology improvements are documented in the report, and
   4.  the methodology of incorporating the improvements is fully documented.

The description of the derivation of the engine models in the report was, at best, vague,
as illustrated by the two examples below:

Example 1: Stoichiometric Dl Turbo
The current research engines of this configuration were reported to be the Sabre engine
developed by Lotus and the downsized concept engine developed by Mahle. Since the
engine modeled in the Ricardo report had a peak BMEP of 25-30 bar and used series-
sequential turbochargers, the Sabre engine is not applicable since it only had a peak
BMEP of 20 bar and used a single stage turbocharger (Refs 1 and 2).

On the other hand, the Mahle engine appeared to be directly applicable, since it had a
peak BMEP of 30 bar and used series-sequential turbocharging (Ref 3).  Since
Reference 3 provided the BSFC map for this engine, shown below, it is not clear why
the Ricardo report could not have shown this map,  or a map derived from this one, and
then described how it was derived and/or combined with other maps to provide the
model used in the report.


                                      16                            W. R. Wade
                                                                     5/15/2011

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   0  1000  2000  3000  4000 6000 6000
          EngtneSp^ad jn/mln]

 Figure 19: BSFC o¥er the engfna operating envelope,
 Cfl 8,7:1,
Example 2: Advanced Diesel
For the advanced diesel, the report provided the following description: "...the LHDT
engine torque curve and fueling maps were generated by starting with a 6.6L diesel
engine typical for this class and applying the benefits of improvements in pumping
losses or friction to the fueling map".  No description of the improvements in pumping
losses or friction reduction was provided and the variation of these improvements over
the speed and load map were not provided.  In addition, the baseline 6.6L engine map
was not provided, the 6.6L friction map was not provided and the methodology for
applying the improvements to the 6.6L engine map was not provided.

The report should explain whether the engine model is only a map of BSFC vs. speed
and load, or if the engine model includes details of the turbocharger, valve timing, and
control algorithms for parameters such as air/fuel ratio, spark/injection timing, EGR rate,
boost pressure, and valve timing.

Advanced valvetrains were included in many of the advanced engines (page 12).
However, the method for applying these advanced valvetrains to the engine maps was
not provided.  Also, no description  of the control strategy for these valvetrains was
provided.  The report did not provide a description of how the reduction of pumping
losses with an advanced valvetrain was applied to a downsized engine that already had
reduced pumping losses. Therefore, no assessment of how the model handled
synergies could be made.

In summary, the Ricardo report provided insufficient  descriptions of the derivation of the
maps used for all of the engines in this study, which  included:
•   Baseline
•   Stoichiometric Dl Turbo
•   Lean-Stoichiometric Switching
•   EGR Dl Turbo
•  Atkinson Cycle
•  Advanced Diesel
                                       17                            W. R. Wade
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Transmission Models

Similar to engine models, the description of the derivation of transmission models was
also vague. Using the automatic transmission model as an example, "For the 2020-
2025 timeframe, losses in automatic transmissions are expected to be about 20-33%
lower than in current automatic transmissions from the specific technologies described
below."  The specific technologies that could provide these reductions appeared to
include:
   •  Shift clutch technology - to improve thermal capacity of the shifting clutch to
      reduce plate count and lower clutch losses during  shifting.
   •  Improved kinematic design - no description of these improvements was
      provided.
   •  Dry sump - to reduce windage and churning losses.
   •  Efficient components - improvements in seals, bearings and clutches to reduce
      drag.
   •  Super finishing - improvements expected were not specified.
   •  Lubrication- new developments in base oils and additive packages, but
      improvements were not specified.

In addition to not specifying the improvements expected from these technologies, no
indication was provided of how these technologies were applied to the transmission
models. For example,
   •  The report stated that losses in automatic transmissions are expected to be
      about 20-33% lower than in current automatic transmissions (page 19).
      However, the baseline losses were not provided for reference and the means to
      achieve these reductions were not described.
   •  The report stated that energy losses in DCTs are expected to be 40-50% lower
      than in current automatic transmissions (page 19). The details of this reduction
      were not provided and references describing these reductions were not provided.
   •  Bearing and seal losses have a greater effect on efficiency at light loads than at
      heavy loads. The report did not describe how these losses were incorporated in
      the model.  In contrast to the lack of descriptions of details in the report,
      Reference 4, as an example, provided the following map of bearing losses in a
      transmission as a function of shaft diameter and speed. Similar details for the
      relevant aspects of the transmission models in this report would have been
      expected.
                                      18                            W.R. Wade
                                                                      5/15/2011

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In summary, the Ricardo report provided insufficient descriptions of the derivation of the
maps for the following transmissions:
   •  Advanced automatic
   •  Dry clutch DCT
   •  Wet clutch DCT
   •  P2 Parallel hybrid transmission
   •  PS Power Split hybrid transmission

In addition, the models for the automatic transmissions of the baseline vehicles were not
provided, so that their adequacy could not be assessed.

Hybrid Technologies Models

Key elements of a hybrid system include: electric machines (motor-generator), power
electronics, and a high-voltage battery. Only the following vague description of the
models for these subsystems was provided: "For each of these systems, current state
of the art technologies were adapted to an advanced 2020-2025 version of the systems,
such as by lowering internal resistance in the battery pack to represent 2010
chemistries under development and decreasing losses in the electric machine and
power electronics to represent continued improvements in technology and
implementation" (page 29).  This vague description did not provide adequate details to
assess the adequacy of these models.  For example, specific values for internal
resistance with references should be provided together with  an illustration of how this
was incorporated in the model of the battery.

In contrast, as an example, Reference 6 provided a detailed motor efficiency map,
shown below, as well as efficiency maps of other key components of the Prius hybrid
vehicle.  Similar maps for all hybrid subsystems would be expected in this report.
         Fi; 3.1-8.!K4 ?TVE: ant5-1 tf&cttocv •r:-ot JUT amp.

In addition, "a Ricardo proprietary methodology was used to identify the best possible
fuel consumption for a given hybrid powertrain configuration over the drive cycles of
interest." (page 29), which precluded an assessment of its suitability.

No mention was provided of how the cooling system for the hybrid system was
modeled.
                                       19                            W. R. Wade
                                                                       5/15/2011

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Accessory Models

None of the accessory models were not provided for review, so their adequacy and
suitability cannot be assessed.

The accessory loads vs. engine speed for the conventional belt driven accessories were
apparently removed from the engine when electric accessories were applied.  However,
the conventional accessory loads as well as the alternator loads/battery loads for the
electric accessories were not provided.

In contrast, as an example, Reference 4 provided the following map of an electric water
pump and AC compressor drive efficiency. Similar maps for all accessory models
would be expected in this report.
        Ele:tn: Artei PJ-^S Mtcnre a AC Dft* Ettoxy. S
  L
            .
  njureS* EwartciVrt«rPump Mattilrw 5 l; TcondKlonlnj Drt «Errcuncy
Boosting Systems

The report states that "various boosting approaches are possible, such as
superchargers, turbochargers, and electric motor-driven compressors and turbines."
(page 13). However, elsewhere the report states "series-sequential turbochargers" will
be used on the Stoichiometric Dl Turbo engine (page 15).

It is not clear in the report how the series-sequential turbocharger was selected from the
variety of boosting devices that were introduced. Models for the turbochargers with
compressor and turbine efficiency maps were not provided, so the appropriateness of
these model cannot be assessed.

      Comment: The model should include a single turbocharger system with
      less extreme downsizing as advocated by the Sabre Engine (References 1
      and 2) as a lower cost alternative to series-sequential turbochargers.
                                      20
W. R. Wade
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Stoichiometric Dl Turbo Engine
The table below compares several attributes of the Ricardo Stoichiometric Dl Turbo
Engine with the Mahle Turbocharged, Dl Concept Engine.
Feature
Downsizing
BMEP
Turbo Response
Turbine Inlet
Temperature
NEDCfuel
economy
Ricardo
Stoichiometric Dl
Turbo Engine
57% (for Std Car)
25-30 bar
1.5 second time
constant
950C
Not available
Mahle
Turbocharged, Dl
Concept Engine
SAE 2009-01 -1503
50%
30 bar
2.5 second time
constant
(estimated from 4
second total
response time)
1025C
25 - 30% better
that NA baseline
Key content of the Mahle Turbocharged, Dl Concept Engine:
- Two turbochargers in series
- Charge air cooler
- Dual variable valve timing
- High energy ignition coils
- Fabricated, sodium cooled valves
- EGR cooler

Reference 3  describing the Mahle concept engine stated that lowest fuel consumption
that usually occurs around 2000 rpm had moved out to 4000 rpm for the series-
sequential turbocharged engine.

      Issue: The Ricardo report did not discuss the concern that the lowest fuel
      consumption in a series-sequential turbocharged engine had moved out to
      4000 rpm, rather than the usual 2000 rpm and did not discuss how this
      concern was handled.

The foregoing table indicates several significant issues:

1.  The turbine inlet temperature of the Mahle engine is significantly higher than the limit
assumed for the Ricardo engine (1025C vs. 950C).  Reducing the turbine inlet
temperature  is expected to result in lower BMEP levels where the temperature is
limited.
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W. R. Wade
  5/15/2011

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2.  The turbocharger response time for the Mahle engine is 2.5 seconds, whereas
Ricardo assumed a time constant of 1.5 seconds.  Such turbocharger delays are
expected to result in significant driveability issues for engines that are downsized
approximately 50%.

The table below compares several attributes of the Ricardo Stoichiometric Dl Turbo
Engine with the Lotus Sabre Engine.
Feature
Downsizing
BMEP
Turbine Inlet
Temperature
Fuel RON
Ricardo
Stoichiometric Dl
Turbo Engine
57% (for Std Car)
25 - 30 bar
950C
87 PON
(Pump Octane
Number)
Lotus Sabre Engine
SAE 2008-01 -01 38
32%
20.1 bar
980C
1050C (common)
and desired
95 RON
Est 91 PON
The paper on the Sabre engine (Reference 2) indicates that operation at lower turbine
inlet temperatures results in a reduction in BMEP.  However, the turbine inlet
temperature for the Sabre engine is still 40C above Ricardo's assumption.

Reference 2 indicates that the Sabre engine with a single stage turbocharger provides
an attractive alternative to extreme downsizing with series-sequential turbochargers.

Cooled Exhaust Manifold

The Ricardo report states, "The future engine configuration was assumed to use a
cooled exhaust manifold  to keep the turbine inlet temperature below 950C..."  No
explanation was provided of how the limit on turbine inlet temperature would affect
boost pressure and power.

Warm-Up Methodology

"Ricardo used company proprietary data to develop an engine warm-up profile" which
was used to increase the fueling requirements during the cold start portion of the FTP75
drive cycle (page 26).  Since this data was proprietary, no assessment of its
appropriateness can be made.

Elsewhere the report states, "A  bag 1 correction factor is applied to the simulated "hot"
fuel economy result of the vehicles to approximate warm-up conditions..."  The
correction factor reduces the fuel economy results of the FTP75 bag 1 portion of the
drive cycle by 20% on the current baseline vehicles and  10% on 2020-2025 vehicles
                                      22
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that take advantage of fast warm-up technologies" (page 29). No references or data are
cited to support this significant reduction in correction factor.

      Issue:  No explanation was provided to clarify when the "engine warm-up
      profile" is used and when the "correction factor" is used.  Therefore, the
      appropriateness of the warm-up methodology cannot be assessed.

Lean-Stoichiometric Switching Engine

The report states that this engine will use a lean NOx trap or a urea-based SCR system
(page 15). The use of fuel as a reducing agent was also suggested in the report (page
16).  However, the fuel economy penalty associated with regenerating the NOx trap or
the reducing agent for the SCR system was not provided.

Engine Scaling

The report states, "The BSFC of the scaled engine map is ...adjusted by a factor that
accounts for the change in heat loss that comes with decreasing the cylinder volume,
and thereby increasing the surface to volume ratio for the cylinder" (page 26). This is a
directionally correct correction.  However, specific values for the correction should be
provided, together with references to the data and methodology used to derive the
values used.

      Issue:  The report states, "...downsizing the engine directly scales the
      delivered torque, ..." (page 26). However, since there will be increased heat
      loss from the smaller displacement cylinder, the torque would be expected
      to be less than the directly scaled values for the same fueling rate.
                                     23                            W. R. Wade
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References (Used for this Review that are also listed in the Report)

References used to establish the basis for the Stoichiometric Dl Turbo engine
assumptions (page 15 of the report):
1.  Coltman, et al. (2008), "Project Sabre:  A Close-Spaced Direct Injection 3-Cylinder
   Engine with Synergistic Technologies to Achieve Low C02 Output", SAE Paper
   2008-01-0138
2.  Turner, et al. (2009), 'Sabre: A Cost-Effective Engine Technology Combination for
   High Efficiency, High Performance and Low C02 Emissions", IMechE conference
   proceedings
3.  Lumsden, et al. (2009), "Development of a Turbocharged Direct Injection
   Downsizing Demonstrator Engine", SAE Paper 2009-01-1503

Reference that summarizes the 2008 study by Perrin Quarles Associates (PQA) that
provided the 2010 baseline cases for five LDV classes (Page 30 of the report):
4.  PQA and Ricardo (2008), "A Study of Potential Effectiveness of Carbon Dioxide
   Reducing Vehicle Technologies"

References containing supporting information for the hybrid powertrains:
5.  Hellenbroich, et al. (2009), "FEV's New Parallel Hybrid Transmission with Single Dry
   Clutch and Electric Torque Support"
6.  Staunton, et al. (2006), "Evaluation of 2004 Toyota Prius Hybrid Electric Drive
   System", ORNL technical report TM-2006/423
                                      24                            W. R. Wade
                                                                      5/15/2011

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                                                 Sample Output From Complex System Model (CSM)
                                                                         5/4/2011
                                            Relative Percentage Differences Were Added by W.  R. Wade
                     FTP      HWFET   US06     Combined 10-60 mph  Displacement FDR      Rolling R.  Aero      Weight  Eng.Eff.   Hybrid    Class
CONVENTIONAL SS

Base
 (Baseline)

Stoich Dl Turbo
AT8-2020 to DCT
HYBRIDS
P2 w/Stoich Dl Turbo
  30.0      43.5      29.1
34.9
  44.5      54.2      32.5      48.4
48.2%    24.6%    11.7%     38.7%

  46.3      55.3      33.7      50.0
4.21%    1.93%    3.51%     3.28%
  61.6      56.3      36.6      59.1
 (Rel to Conv SS SCT)    32.96%    1.80%     8.89%    18.23%
PS w/Stoich Dl Turbo
  57.5      53.3      36.4      55.5
 (Rel to Conv SS DCT)    24.00%    -3.50%     8.24%    11.11%
PS w/Atkinson CPS
  55.1      53.2      38.1      54.3
 (Rel to Stoich Dl Turbo)    -4.08%    -0.18%    4.61%    -2.29%

PS w/Atkinson DVA          58.3      54.8      38.7       56.7
 (Rel to Stoich Dl Turbo)     1.5%     2.7%     6.1%      2.1%
80
.o
          8.5
          8.6
          8.6
          9.2
          8.5
                                        8.5
1.04      3.23   0.00822     0.69   3625
           1.04      3.23   0.00822      0.69    3625
           1.04      3.23   0.00822      0.69    3625
          0.83      3.23   0.00822      0.69    3625
          0.83      3.23   0.00822      0.69    3625
           2.4      3.23   0.00822      0.69    3625
                       2.4      3.23   0.00822      0.69    3625
   Standard Car (Toyota Camry)


   Standard Car (Toyota Camry)


   Standard Car (Toyota Camry)




24 Standard Car (Toyota Camry)


80 Standard Car (Toyota Camry)


80 Standard Car (Toyota Camry)


80 Standard Car (Toyota Camry)

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C-1

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 Peer review of the report, "Computer Simulation of Light-Duty Vehicle Technologies for
            Greenhouse Gas Emission Reduction in the 2020-2025 Timeframe"
                               Report by:Scott McBroom
                                 Date of Report: 8/17/1
Charge to Peer Reviewers:
       As EPA and NHTSA develop programs to reduce greenhouse gas (GHG) emissions and
increase fuel economy of light-duty highway vehicles, there is a need to evaluate the
effectiveness of technologies necessary to bring about such improvements.  Some potential
technology paths that manufacturers might pursue to meet future standards may include
advanced engines, hybrid electric systems, mass reduction, along with additional road load
reductions and accessory improvements.

       Ricardo Inc. has developed simulation models including many of these technologies with
the inputs, modeling techniques, and results described in the Ricardo Inc.  document that you
have been provided dated March 10, 2011.

       EPA is seeking the reviewers' expert opinion on the inputs, methodologies, and results
described in this document and their applicability in the 2020-2025 timeframe.  The Ricardo Inc.
report is provided for review.  We ask that each reviewer comment on all  aspects of the Ricardo
Inc. report.  Findings of this peer review may be used toward validation and improvement of the
report and to inform EPA and NHTSA staff on potential use of the report for predicting the
effectiveness of these technologies. No independent data analysis will be required for this
review.

       Reviewers are asked to orient their comments toward  the five (5) general areas listed
below. Reviewers are expected to identify additional topics or depart from these general areas as
necessary to best apply their particular set of expertise toward review of the report.

       Comments should be sufficiently clear and detailed to allow readers familiar with the
report to thoroughly understand their relevance  to the material provided for review. EPA
requests that the reviewers not release the peer review materials or their comments until Ricardo
Inc. makes its report and supporting documentation public. EPA will notify the reviewers when
this occurs.

       Below you will find a template for your comments. You are encouraged to use this
template to facilitate the compilation  of the peer review comments, but do not feel  constrained by
the format.  You are free to revise as needed; this is just a starting point.

       If a reviewer has questions about what is required in order to complete this  review or
needs additional background material, please contact Susan Elaine at ICF International
(SBlaine@icfi.com or 703-225-2471). If a reviewer has any questions about the EPA peer review
process itself, please contact Ms. Ruth Schenk in EPA's Quality Office, National Vehicle and
Fuel Emissions Laboratory by phone (734-214-4017) or through e-mail (schenk.ruth@epa.gov).

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Scott McBroom
Charge Questions:

(1) Inputs and Parameters. Please comment on the adequacy of numerical inputs to the model
as represented by default values, fixed values, and user-specifiable parameters.  Examples might
include: engine technology selection, battery SOC swing, accessory load assumptions, etc.)
Please comment on any caveats or limitations that these inputs and parameters would affect the
final results.

Battery Model: Overall the battery model is sound; however, I don't understand why cold
modeling is included.  The FTP testing doesn't include cold testing therefore only 25C and up
should be included and the battery is consistent at those temps.

Engine Model:
I see data on the HEDGE engine technology but no mention of it in the list of engine
technologies unless it's the high EGR DI gasoline engine.

Engine Model:
The trend in engine technology is forced induction (engine downsizing). I think the selection of
turbo only is too limiting. I anticipate variable speed supercharging and other combination of
forced induction. I think the study would do well to include this.

Rgen Alternator:
Ricardo states - 70% efficient alternator; however, alternator efficiency is a function of temp,
speed and load. 70% is probably the best, but it's highly unlikely that it will operate there for the
duration of the conditions.

Diesel Engine Fuel Maps:
The presentation shows the technologies to be deployed, but doesn't discuss how the 2020 bsfc
maps were arrived at. It might be helpful to also use the same method for comparison that the
authors used to show LBDI vs EGR

Diesel Technology:
Curious about the author's comment regarding supercharging, "advances to avoid variable
speed". Why not variable speed?

Curious about why no discussion of advanced materials in engines to achieve improvements.

EBDI Engine:
Couldn't find fuel economy benefit discussion in presentation. Should be done as  gasoline or
energy equivalent. I know CO2 is proportional, but....
Future Developments in Engine Friction -
I think it would be worthwhile to point out that there are technologies that are more driven by
increased durability rather than fuel economy but they could play off one another. Engine
friction reduction is one of those areas.

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Scott McBroom
(2) Simulation methodology.  Please comment on the validity and applicability of the
methodologies used in simulating these technologies with respect to the entire vehicle. Please
comment on any apparent unstated or implicit assumptions and related caveats or limitations.
Does the model handle synergistic affects of applying various technologies together?

Transmission Model:
Ricardo describes an approach that asserts that using an average efficiency value vs a 3D
efficiency map yields insignificant differences over the CAFE drive cycles, but offers no results
to validate the claim.

Transmission Model:
Ricardo offers no discussion of how inertial changes are managed during shifts. This may have
greatest impact on the shift strategies where the transmission shifts to put the engine at the best
bsfc for the given load.

Hybrid:
I don't see any effort to model  motor/inverter temperature effects. One would expect significant
degradation of motor capability as things heat up during normal operation.

Regen Alternator:
Alternator model is too simplistic. On average the efficiency is too high as identified and it's
unrealistic to assume that the battery will be able to accept 100% of the charge.

EHVA:
The paper addresses the potential of the technology nicely.  Since it was published in 2003 has
any more recent work been done to address the durability and issues brought up in the
conclusions?

Accessories:
I don't see any discussion on the treatment of accessories. I believe from my review of the
previous material, that the authors assume that all accessories will be electric. I think that engine
driven accessories will play a key role in 2020.

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Scott McBroom
(3) Results. Please comment on the validity and applicability of the results to the light-duty
vehicle fleet in the 2020-2025 timeframe. Please comment on any apparent unstated or implicit
assumptions that may affect the results, and on any related caveats or limitations.

Motor Efficiency Maps
I am having trouble believing that motor efficiency will stay above 90% once temperature effects
are accounted for. It also seems to me that these numbers don't include the inverter even though
the authors say that it does. The UQM maps seem more reasonable. As stated in a previous
comment, I believe that the cost reductions needed for motors will drop their efficiencies in the
future.

After reading the papers and presentations I come to the assumption that the papers were used to
guide the selection of technology, but it's not clear which maps were generated from model and
which maps were generated in the test cell. It's evident that there is a heavy concentration on
engine technology and the fidelity of the engine models, which is appropriate. I have a slight
concern about the impression I'm left with; that there is not much attention to the interaction  of
systems effects. This is most likely because of cost and availability of data. I would like to see
the EPA articulate a process for looking at system interactions, continuous improvement and
model compatibility. For example if the study were to run over several years the researches
should feel confident comparing a result generated with the models in 2013 to modeling results
generated today.

-------
Scott McBroom
(4) Completeness. Please comment on whether the report adequately describes the entire
process used in the modeling work from input selection to results.

Hybrid:
Ricardo asserts that electric machine design activities of the future will most like concentrate
around cost reductions; however I see machine efficiency dropping in order to meet cost
reductions. Therefore I think it premature to assume that efficiency will stay the same and cost
will drop.

-------
Scott McBroom
(5) Recommendations. Please comment on the overall adequacy of the report for predicting the
effectiveness of these technologies, and on any improvements that might reasonably be adopted
by the authors for improvement.  Please note that the authors intend the report to be open to the
community and transparent in the assumptions made and the methods of simulation. Therefore
recommendations for clearly defined improvements that would utilize publicly available
information would be preferred over those that would make use of proprietary information.
(6) Other comments. Please provide your comments on report topics not otherwise captured by
the aforementioned charge questions.

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                       PEER REVIEW:
       Computer Simulation of Light-Duty Vehicle
Technology for Greenhouse Gas Emission Reduction in
              the 2020-2025 Timeframe
                     Review Conducted for:

                        U.S. EPA
                     Review Conducted By:

                    Shawn Midlam-Mohler
                        Review Period:

                      4/28/2011-5/16/2011

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Contents




   Executive Summary	3




   Simulation Methodology	4




     Vehicle Model	5




     Engine Models	5




     Aftertreatment/Emissions Solutions	7




       Advanced Valvetrains	7




       Direct Injection Fuel Systems	8




       Boosting Systems	8




       Engine Downsizing	8




       Warm-Up Methodology	9




       Accessory Models	9




       Engine Technology "Stack-Up"	10




     Baseline Hybrid Models	11




       Hybrid Control Strategy	11




       Electric Traction Components	12




       HEV Battery Model	12




     Transmissions	13




   Data Analysis Tool	13




   Conclusions	14
Shawn Midlam-Mohler - Peer Review                                           Page 2

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Executive Summary
   For  the  purpose of  describing the modeling approach  used in the forecasting  of the
performance of future technologies, the report reviewed is inadequate. In virtually every area,
the report lacks sufficient information to answer the charge questions provided for the reviewer.
It is entirely possible that the approach used is satisfactory for the intended purpose. However,
given the information provided for the review, it is not possible for this reviewer to make any
statement regarding the suitability of this approach.  Some brief comments on each of the five
charge questions are provided below:
   Inputs and Parameters - From a high level, it is clear what the inputs to the design space
tool are, which are listed in tables 8.1  and 8.2.  At the next level down (i.e. the vehicle and
subsystem models) there is no comprehensive handling of inputs in  parameters in the  report.
Some models are partially fleshed out in this area but most are lacking. By way of example, the
engine models are described as maps which are "defined by their torque curve, fueling map, and
other input parameters" where "other input parameters" are never defined.
    Simulation  Methodology - The vehicle model is reported as  "a complete, physics-based
vehicle  and powertrain system model"  - which it is not.  The modeling approach used relies
heavily  on maps and empirically determined data which is decidedly not physics-based.  This
nomenclature issue aside, the model is not described in sufficient detail in the report to make an
assessment in this  area.   An excellent example of this is the  electric traction drives and HEV
energy storage system for which the report mentions no  details,  even qualitative ones,  on the
structure of the models.
   Results - The  third charge questions deals with the validity  and the  applicability  of the
resulting prediction.   The  difficulty in this task is  that it  is an  extrapolation from present
technology that uses an extrapolation method (i.e. the model) and a set of inputs to the model
(i.e. future powertrain data.)  Since it is not possible to validate the results against vehicles and
technology that  do not exist,  one  can  only  ensure that the model and  the  model inputs are
appropriate for the task.   Because of the lack of transparency in the model and inputs  it is
difficult to make any claims regarding the results.  In trying to validate results,  one example is
cited in the body of the report that shows the baseline engine getting superior HWFET and US06
Shawn Midlam-Mohler - Peer Review                                              Page 3

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fuel economy than all of the other non-HEV powertrains with other factors being the same - this
leaves some skepticism regarding the results.
    Completeness -  Based on the above,  it is  clear that this reviewer feels the report is
inadequate at describing the entire  process of modeling work from input  selection to results.
There was not a single subsystem that was documented at the level desired. It is understood that,
in some cases,  there  are things of  a proprietary nature that must be concealed.   As a trivial
example,  the frontal area of the vehicle classes does not seem to be anywhere in the report or
data analysis tool.  This is one parameter amongst hundreds excluding the real details of the
models (i.e. equations or block diagrams),  methods used to generate engine maps, details on
control laws, etc.   On the topic  of proprietary data,  there are many ways of obscuring  data
sufficiently that can demonstrate  a key point (i.e. simulation accuracy) without compromising
confidentiality of data - this should not be a major barrier to providing some insight into the
inner working of the simulator.
    Recommendations - Given the  low level of detail given in the report, it does seem that the
strategy used is consistent with the goal of the work and what others in the field are doing.  That
being said, the report is inadequate in nearly every respect at documenting model inputs, model
parameters,  modeling methodology, and the  sources and techniques  used to  develop the
technology performance data. Given the need for transparency in this effort, this reviewer  feels
that the detail in the report is wholly inadequate to document the process used. The organization
responsible for the modeling has  expertise  in  this area it is certainly possible  that the
methodology is sound, however, given just the information in the report there is simply no way
for an external reviewer to make this conclusion.
    Because of the lack of hard  information to answer the charge  questions, this  peer review
evolved mainly into a suggested list of details that should be brought forward in order to allow
the charge questions to be answered properly.  With this information, it is  hoped that a person
with expertise in the appropriate areas will be able comment on the work more fully.


Simulation Methodology
    The simulation methodology is  generally not described in the report in sufficient detail to
assess the validity and accuracy of the approach.   The models and approach are described

Shawn Midlam-Mohler - Peer Review                                              Page 4

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qualitatively; however, this is insufficient to truly evaluate the ability of the modeling approach
to perform the  desired function.   The following subsections address  specific issues with the
models, inputs, and parameters and suggest possible corrective actions to address these issues.
Vehicle Model
   The vehicle  model is described as "a complete, physics-based vehicle and powertrain system
model"  developed in the MSC.EasyS™  simulation environment.    This  description  is not
particularly helpful in defining the type of model as portions of the model are clearly not physics
based, such as the various empirical maps used or sub-models like the warm-up model which is
by necessity an  empirical model due to the  complexity of the warm-up process compared to the
expected level of fidelity of the model.  It is assumed that a standard longitudinal model accounts
for rolling losses, aero losses, and grade is used to model the forces acting on the vehicle.  Input
parameters for the vehicle model are not described.  The baseline vehicle platforms are listed,
however, the  relevant loss coefficients are not  provided (rolling  resistance, drag coefficient,
inertia.)
Suggested Corrective Action:
   1.  List the dynamic equation describing the longitudinal motion of the vehicle
          a.  NOT ADDRESSED IN SUPPLEMNTAL MATERIAL REVIEWED
   2.  List all parameters used for each vehicle class for simulation
          a.  NOT ADDRESSED IN SUPPLEMNTAL MATERIAL REVIEWED

Engine Models
       The engine model is the most important element in successfully modeling the capability
of future vehicles, since it is the responsible for the largest loss of energy. It is also one of the
most difficult aspect to predict since it involves  many  complicated processes (i.e. combustion,
compressible  flow) which must be considered in parallel with emissions compliance (i.e.  in-
cylinder formation, catalytic reduction.) Because of this, this sub-model must be viewed with
extreme scrutiny in order to ensure quality outputs from the model.
       The engine models are "defined by their torque curve, fueling map, and other input
parameters."  This implies that the maps are  static representations of fuel consumption  versus
torque, engine speed, and other unknown input  parameters.  Generally speaking, representing
engine performance in this fashion is consistent with typical practice for this class of modeling.
Shawn Midlam-Mohler - Peer Review                                             Page 5

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This comment deals only with the representation of the engine performance in simulation, the
generation of the data contained within the map is much more challenging.
       The report outlines two methods were used to produce engine models.  The first method
was used for boosted engines and relied upon published data on advanced concept engines which
would represent production engines in the 2020-2025 timeframe.  The second method was used
with Atkinson and diesel engines and somehow extrapolated from current production engines to
the 2020-2025 time  frame.   The description of  both of these methods in the report is
unsatisfactory.  It also fails to address how the various technologies are used to build up to a
single engine  map  for a specific powertrain.   Validation, to the extent possible with future
technologies, is also lacking in this area.
       This reviewer took some time to look  at the data via the tool provided.  One table is
shown in Figure 1 which shows some unexpected results. The results are for a small car with the
dry clutch transmission and it shows the baseline engine having superior fuel economy over all
other non-hybrid powertrain options.  This is unexpected behavior and, since there is minimal
transparency in the model, it cannot be investigated any further.
Engines
Baseline
Stoich_DI_Turbo
Lean_DI_Turbo
EGR_DI_Turbo
Atkinson CPS
Atkinson_DVA
FTP
42.1
46.3
48.3
48.2
44.5
45.5
HWFET
62.5
55.3
56.4
57.6
59.0
57.1
US06
37.0
33.7
33.9
35.2
35.4
34.5
   Figure 1: Simulation Results Different Engines for Small Car with 8Dry_DCT and all other Parameters Constant
Suggested Corrective Action:
   1.  Provide fuel and efficiency map data for all engines used in simulation
   2.  Describe what the "other inputs" are to the engine maps
   3.  Provide specific references of which published data was used to predict performance of
       the future engines. Some references are given, however, it is not clear how exactly these
       references are used.
   4.  Wherever possible, provide validation against data on similar technologies
   5.  Describe in detail the approach  used  to "stack up" technologies for a given powertrain
       recipe
Shawn Midlam-Mohler - Peer Review
Page 6

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Aftertreatment/Emissions Solutions
       Based on the report, it seems that emissions solutions are assumed to be available for all
powertrain technology packages selected.  The report discusses this in some qualitative detail in
section  4.2.2 with respect to lean-stoichiometric switching.   This discussion  is  somewhat
incomplete, in that the way it is written it assumes operating at stoichiometry lowers exhaust gas
temperature.  In reality, switching from lean to stoichiometric  operation at constant load results
in higher  exhaust gas temperatures.  Despite this factual inconsistency, it is indeed generally
better to operate a temperature sensitive catalyst hot and stoichiometric or rich rather than hot
and lean - so the concept of lean-stoich switching is valid even  if the explanation provided is not.
Even without this factual  inconsistency, some additional discussion of aftertreatment systems
would be of benefit given that lean-burn gasoline engines are at present a well-known technology
for many years that is still  problematic with respect to emissions control. A separate issue is the
topic of fuel enrichment for  exhaust  temperature management  which will have an  important
impact on emissions  and,  if emissions are  excessive, reduce the peak torque available from an
engine.
Suggested Corrective Action:
    1.  Provide better evidence that powertrain packages have credible paths to meet emissions
       standards
   2.  Provide evidence that fuel enrichment strategies are consistent with emissions regulations

Ail  Mi' ed Valve I rn m s
       Two types of advanced valvetrains were included in the study, cam-profile switching and
digital valve actuation.  Both of these technologies  are aimed at reducing pumping losses at part-
load.   The  impact  of these  technologies is  difficult to predict using  simplified  modeling
techniques and  typically require consideration of compressible flow and a 1-D analysis at  a
minimum. Even with an appropriate fidelity model, these systems require significant amounts of
optimization in  order to determine the best possible performance across the torque-speed plane
of the engine. It is unclear how these systems were used to generate accurate engine maps given
the level of detail provided in the report.
Suggested Corrective Action:
Shawn Midlam-Mohler - Peer Review                                             Page 7

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    1.  Describe how variable valve timing technologies were applied to the base engine maps
    2.  Describe the process of determining the extent of the efficiency improvement
    3.  Describe  how  optimal  valve  timing  was determined  across the variety of engines
       simulated
Direct              Systems
       Because of the availability of research  and production data in this area, it is expected that
performance from this technology was used to predict performance rather than any type of
modeling approach. That being said, the report does not describe where or how this data might
have been used to develop the fuel consumption map of the engines simulated  nor what  data
sources were used.

Suggested Corrective Action:
    1.  Cite sources of data used to predict DI performance
    2.  Describe how this data was used to develop the future engine performance maps
    3.  Provide validation of modeling techniques used


       Boosting was applied to many of the  different  powertrain packages simulated.  Beyond
stating what maximum BMEP that was achievable, very little is mentioned in how the efficiency
of the boosted engines were determined. Among other factors, boosting often creates a need for
spark retard which costs efficiency if compression ratio is fixed.  These complex issues are tied
to combustion which is inherently difficulty to  model.  This aspect of the engine model is not
well documented in the report.
Suggested Corrective Action:
    1.  Describe the process of arriving at the boosted engine maps
    2.  Describe how factors like knock are addressed in the creation of these maps


       Engine scaling is  used  extensively in the report.  Basic scaling based on brake mean
effective pressure is common in modeling at  this level of fidelity,  thus,  this does not need any
special description.  However, the report mentions some means of modeling the  increased
Shawn Midlam-Mohler - Peer Review                                             Page 8

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relative heat loss with small displacement engines which is not a standard technique.  The model
or process used to account for this effect should be explicitly described given that engine size is
one of the key parameters in the design space.
Suggested Corrective Action:
    1.  Properly document the process of scaling engines
   2.  Validate the process used to scale engines


   The report describes a 20% factor applied to bag 1 of the FTP-75 for baseline vehicles and a
10% factor applied to the advanced vehicles.   The motivation for these factors is described
qualitatively  and  is valid,  as  many organizations are currently  investigating  strategies  to
selectively heat powertrain components to combat friction effects. However, the values for these
factors that were  selected are not backed up with any data or citation.  It is suspicious that the
two values cited are such round numbers - the data from which these numbers are derived should
be cited.  Because of the  complexity of this phenomenon, some type of empirical  model is
justified. The model described in the report is not sufficiently validated to judge its suitability.
Suggested Corrective Action:
       1.  Cite sources of data for 10% and 20% factors applied to the cold bag fuel  economy
          data
       2.  Cite and/or validate the modeling approach used

Accessory
       The accessory model is divided into electrical and mechanical loads. The electrical sub-
model assumes alternator efficiency's of 55% and 70% for the  baseline and advanced vehicles
respectively.   Given the required simplicity of the model,  a simple  model like this is likely
acceptable, however, there is no  source described for the alternator efficiencies.   The  base
electrical load of the vehicle is mentioned  briefly, however, no numerical values are given for
each vehicle class or any type of model described.
       The electrical system also includes an  advanced alternator  control which  allows for
increased  alternator usage during decelerations for kinetic energy recovery.   The control
description given is valid but simplistic,  but seems to fit the expected level of accuracy required
for the purpose. There is an  issue regarding with the approach  for modeling the battery during
Shawn Midlam-Mohler - Peer Review                                              Page 9

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this process.  When charging the battery at the stated level of 200 amps, the charging efficiency
of the battery will be relatively poor. During removal of the energy later, there will once again
be an efficiency penalty. There is no description of a low-voltage battery model in the report nor
any explicit reference to such charge/discharge efficiencies.  Additionally, an arbitrary limit of a
200 amp alternator is defined for all vehicle classes - it is unlikely that a future small car and a
future light heavy duty truck will have an alternator with the same rating.
       On  the mechanical  side, it is  assumed  that "required accessories"  (e.g. engine water
pump,  engine oil  pump)  are included  in the  engine  maps.  The mechanical loading of a
mechanical fan is mentioned but no description of the model which, at a minimum, should be
adjusted based on engine speed and engine power.
Suggested Corrective Action:
       1.  Cite and/or validate the alternator efficiency values of 55% and 70%
       2.  Account for charge/discharge  losses  in the advanced  alternator control  and/or
          describe the 12V battery model used for the simulation
       3.  Describe, cite, and validate the accessory fan model used in the simulation
       4.  Justify the use of a 200 Amp advanced alternator across all of the vehicle platforms.
                   "Stack-Up"
       There are a host of different technologies superimposed to create the future powertrain
technologies.  There is not a clear process described on how this technology "stack-up" is
achieved.  For instance,  an advanced engine technology may allow for greatly improved BMEP.
Greatly improved BMEP often comes at the expense of knock limits which are difficult to model
even with sophisticated modeling techniques.   In this simulation,  many layers of powertrain
technology are being compounded upon each other which will not simply sum up to the best
benefits of all of the technologies - there are simply too many  interactions.  At  the level of
modeling described, which are maps which are altered in various unspecified ways; it is not clear
how the technology stack-up is captured.
Suggested Corrective Action:
    1.  Describe in greater detail  the  approach used  to model technology  stack-up  on  the
       advanced vehicles
   2.  Provide some form of validation that this  approach is justified

Shawn Midlam-Mohler - Peer Review                                             Page 10

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Baseline Hybrid Models
The following subsections deal with issues related to the hybrid component models.
Hybrid Control Strategy
      Hybrid vehicles are particularly challenging to model because of the extra components
which allow multiple torque sources, and thus, require some form of torque management strategy
(i.e.  a  supervisory control.)  The report briefly describes  a proprietary supervisory  control
strategy that is used to optimize the control strategy for the FTP, HWFET, and US06 drive cycle.
The  strategy claims to  provide the "lowest possible fuel consumption"  which seems to be
somewhat of an exaggeration - this implies optimality which is quite a burden to achieve and
verify for such a complicated problem.  The strategy also is reported to be "SOC neutral over a
drive cycle" which is also difficult to achieve in practice in a forward looking model. Once can
get SOC  with a certain window, however, short of knowing the future or simply not using the
battery - it is impossible to develop a totally SOC neutral  control strategy.
      Another factor that must be considered is that a hybrid strategy that achieves maximum
fuel  efficiency on FTP, HWFET, and US06  does not  consider many other relevant  factors.
Performance metrics like 0-60 time  and drivability metrics often suffer in practice.  In  today's
hybrids, the number of  stop-start  events is sometimes  limited from the optimum number for
efficiency because of  the emissions concerns.   Because of these factors and others, a strategy
achieving optimal efficiency may be higher than what can be achieved in practice.
      Without even basic details on  the hybrid control strategy, it is simply not possible to
evaluate this aspect of the work. Because of the batch simulations with varying component sizes
and characteristics, this problem is  not trivial.  Supervisory control strategies used in practice and
in the literature require  intimate knowledge of the efficiency characteristics and performance
characteristics of all  of the  components (engine,  electric motors/inverters,  hydraulic braking
system, and energy storage system) to develop control  algorithms.  This concern is amplified by
the lack of validation of the hybrid vehicle model against a known production vehicle.  It is
unclear how a "one-size  fits all" control strategy can be truly be perform near optimal over such
widely varying vehicle platforms.

Shawn Midlam-Mohler  - Peer Review                                            Page 11

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       A  last comment  is that there  is  no validation of  the  HEV model against current
production vehicles.  At  a minimum, the  Toyota Prius has  been dissected sufficiently in the
public domain to conduct  a validation of this class of hybrid electric vehicle.
Suggested Corrective Action:
    1.  Better describe  the hybrid  control strategy and validate  against a current production
       baseline vehicle
    2.  Validate that the HEV control algorithm performs equally well on all vehicle classes
    3.  Validate that other vehicle performance metrics, like emissions and acceleration, are not
       adversely impacted by an algorithm that focuses solely on fuel economy.  The emission
       side of things will challenge to validate with this level of model, however,  some kind of
       assurance should be made to these factors which are currently not addressed at all.
Electric Traction Components
       The model  of electric traction components is not discussed in any detail, as the  only
mention in the report is that current technology systems were altered by "decreasing losses in the
electric machine and power electronics." Given the importance of the electric motor and inverter
system in hybrids this is not acceptable.
Suggested Corrective Action:
    1.  Describe the method used to model electric traction components
    2.  Provide  validation/basis  for the  process used to generate future technology versions of
       these components
    3.  Describe the technique used to scale these components

HEV
       Battery models for HEVs are necessary to adequately model the performance of an HEV.
The report provides no substantive description of the battery pack model, other  than that the
model was developed by "lowering internal  resistance in the  battery  pack to represent 2010
chemistries under development." Battery pack size is also not a currently a factor in the model -
this has a impact of charge and discharge efficiency of the battery pack.
Suggested Corrective Action:
    1.  Describe the method used to model the HEV battery

Shawn Midlam-Mohler -  Peer Review                                             Page 12

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   2.  Provide validation/basis for the process used to generate future technology versions of the
       battery
   3.  Describe the technique used to scale the HEV battery

Transmissions
       This peer  reviewer  is not as well-practiced  in transmissions as in other areas in  this
review. Because  of this, a  more limited review was conducted of this aspect of the report.  As
with the other areas of the report, the general  concern in this  area is the inadequacy of
documentation of the modeling  approach and validation.  Generically, the same issues noted
above are applicable here:
   1.  Cite data sources used in modeling
   2.  Validate models wherever possible
   3.  Fully describe transmission models/maps and processes used to generate them
   4.  Fully describe clutch/torque converter models/maps and processes used to generate them
   5.  Fully describe the process used to generate shift maps and the operation of the shift
       controller
   6.  Fully describe the lockup  controller (i.e. how soon can it enter lockup after shifting?)
   7.  Fully describe the process for modeling torque holes during shifting
   8.  Fully describe the model used for the final drive (i.e. inputs/structure/outputs)


Data Analysis Tool
       The vehicle simulator is used to generate several  thousand simulations using a DOE
technique.  This data is then fit with a neural-network-based response surface model in which the
"goal was to achieve low residuals while not over-fitting the data." This response surface model
then becomes the method  from  which vehicle design performance is estimated in the data
analysis tool. In this case, the response surface model is nothing more than a multi-dimensional
black-box curve fit.  There  was no error analysis given in the report regarding this crucial step.
By way  of example, the vehicle simulator could provide near perfect predictions of future
vehicle performance; however, a bad response surface fit could corrupt all of the results.
Shawn Midlam-Mohler - Peer Review                                            Page 13

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Suggested Corrective Action:
                                                              r\
    1.  Provide error metrics  for the neural network RSMs (i.e.  R ,  min absolute error, max
       absolute error, error histograms, error standard deviation, etc.) before combining the fit
       and validation data sets
    2.  Provide the  error metrics described above for the RSMs after  combining the fit and
       validation data sets
    3.  Provide validation that the data analysis tool correctly uses the RSM to predict results
       very close to the source data (i.e. demonstrate the GUI software behaves as expected)
Conclusions
   As outlined in the executive summary, it was not possible to answer the charge questions
provided for this peer review due to lack of completeness in the report.  Thus, this report was
aimed at providing feedback on what information would be helpful to allow a reviewer to truly
evaluate the spirit of the charge questions. With the above in mind, the following conclusions are
made.
   The modeling approach describe in the report could be appropriate for the simulation task
required  and is generally consistent with approaches used by other groups in this field.  The
conclusions from the report could very well be sound; however, there is insufficient information
and validation provided in  the report to determine if this is the case. The technique used to
analyze the mass simulation runs could also be sound, although  the  accuracy of the  response
surface model is not cited in the report.
   These issues are summarized in the following key areas:
       1.  The  process of arriving at the performance of the future technologies is  not  well
          described
       2.  The majority of models are only described qualitatively making it hard or impossible
          to judge the soundness of the model
       3.  Some of  the  qualitative descriptions of the  models  indicate  that models do not
          consider some important factors
       4.  Because of the qualitative nature of the model descriptions, there is a major lack of
          transparency in the inputs and parameters in the models

Shawn Midlam-Mohler - Peer Review                                             Page 14

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       5.  Where precise value(s) are given for parameters in the model, the report generally
          does not cite the source of the value(s) or provide validation of the particular value
       6.  Validation of the model  and sub-models is not satisfactory (It is acknowledged that
          many of these technologies do not exist, but the parameters and structure of the model
          have to be based on something.)
Shawn Midlam-Mohler - Peer Review                                            Page 15

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Supplemental Review
       After the main review, some supplemental information was provided for further review.
Comments on this material are found below and are organized by the title of the file reviewed.
General Comments
       The supplemental review material provided some answers to questions posed above, but
in general, did  not provide the level of detail  necessary to ensure  a thorough review of the
process.  The conclusion of this reviewer remains similar as on the original review, which is that
there were no serious flaws found in the work, however, there were enough omissions that it is
not possible to accurately judge if the predictions made are accurate. The biggest concern in
this work is the lack of validation and/or citation of where data and models are coming from.
There are numerous maps that are presented in the follow-up material, however,  these maps had
to have originated from  some process (which needs  documented)  and should be  compared
against some kind of validation.  Despite the lack of documentation provided, the work is
generally that of a project team that is competent in this field of study.
Cold Start Correction Methodology
       The correction used to adjust fuel economy for cold start is described in this presentation.
The method is based on two pieces of information:
   1.   A set of three tests from a single vehicle's instantaneous fuel multiplication correction
       factor
   2.   A piece of EPA data which shows a fleet-wide average for 2007 of the instantaneous fuel
       multiplication correction factor
       The instantaneous fuel  multiplication  correction factor  is not  described  in  the
presentation, however, it is assumed to be the sum of the "short term fuel trim"  and "long term
fuel trim."  If this  is the case, then this value doesn't correlate to increased fuel consumption, but
rather,  to errors in the injector characterizations, fuel property  assumptions, and air estimation
algorithm in the engine controller.   The engine controller is  going  to maintain stoichiometry
based on oxygen sensor measurements, these trim values are the simply the  feedback correction
values required to do this based on the feedforward algorithm in the ECU. By way of example, I
could alter the fuel tables of an ECU by 15% which would cause the feedback control system to

Shawn Midlam-Mohler - Peer Review                                            Page 16

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correct by an opposite 15%.  This would not change the fuel consumption of the vehicle once the
control system has corrected it, which would happen in seconds.
       I don't disagree necessarily with the magnitude of the outcomes, since they are based
mostly on EPA bag fuel economy data. If I am correct in my understanding of the correction
factor then the method is not valid.
Alternator Regen Shift Optimizer

Alternator
       The  alternator  regeneration  strategy  is  not well  documented.    The  key  system
specifications, such as max alternator output and efficiency, are listed as assumptions without a
data source for validation.  The  efficiency of the battery is not mentioned  in this nor other
presentations that this reviewer has read - battery efficiency for a lead  acid battery at high
currents is poor, this would have  an impact on the recovery  of energy.  Strategies like this are
disruptive to drivability and this issue is not discussed in the presentation.
Shift Optimizer
       Shifting strategy impacts efficiency, performance, and drivability.  Manufacturers are
aware of this and balance all three when calibrating shift maps.  Changing baseline shift maps to
improve efficiency will  have an impact on the other metrics which are also important to the
vehicle. Additionally, it is not clear how the optimized shift strategy was developed, what the
shift strategy is, or how it will be  applied to the range of transmissions in the study.  It is stated
that is optimizes BSFC, however,  there are other constraints that must  be applied in addition to
this.

Battery Warm up 1, Battery Warm up 2

The battery model described has the following possible problems:
    1.  The  model is relatively simple - but could potentially work for the application  and
       generally is consistent with the fidelity  of the rest of the model.
   2.  The model references ambient temperature for heat rejection. Most HEVs pull in cabin
       air rather than outside air for cooling, thus, this will cause modeling error.

Shawn Midlam-Mohler - Peer Review                                            Page 17

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    3.  Adjusting the  Mbat x Cpbat term by  200% is a red flag that  something might  be
       fundamentally  wrong with either the model formulation or the data used in the model.
       There should be minimal errors in the mass estimation of the pack  and the specific heats
       of battery modules can be found in the literature or through testing.
    4.  The method of handling battery packs of different classes of vehicles is not described, nor
       are the actual parameters for these different models disclosed.

Turbo Lag
       The data and methods used in modeling turbo lag are appropriate and there is sufficient
explanation and data to support the model.
Future Friction Assessment
       The provided presentation does not describe how engine friction projections to 2020 are
made or how they are modeled.  It provides some data from 1995 to 2005, however, it does not
provide any useful insight into how this information is used.
Scaling Methodology Review
       With one exception, the scaling methodology appears to be sound given the information
provided in the  presentation. The curve used to  adjust BSFC with displacement ratio is not
supported with  data or any citation of where it originated.  The motivation for this correction
seems valid, however, it needs to be supported with data.

SI Engine Maps and Diesel Engine Maps
       The baseline engine map data is shown in a series of figures and references are provided
for the specific vehicle that the map is for. It is assumed that this indicates that this data has been
measured experimentally. If this is the case, then this is well documented.
       For the 2020 engine maps, there is insufficient detail in this presentation on how the maps
were generated.  Getting accurate  simulation requires careful validation of the  model as well as
the data in the model - these engine maps are not sufficiently well documented  for me to make a
judgment on their suitability for the overall goal of the simulator. I am well aware that these
future engines do not  exist, but  there had to be some process of generating these engine maps.
Without more information on this process it is simply not possible to comment on their accuracy.

Shawn Midlam-Mohler - Peer Review                                            Page 18

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BSFC Map Comparisons
       I reviewed this but do not have any substantive comments.  All of the figures compare
pseudo-virtual engines  with other pseudo-virtual engines.   A comparison  back to  a known,
experimentally validated engine current engine would have been more useful for me as it would
allow one to  see the magnitude of improvements that were assumed for the 2020 engines and
where on the map these improvements were made.
Input Data Review
       The documentation on the Diesel engine  maps was helpful; however, it did not discuss
how the  2020 engine  maps were developed.   This is critical for having confidence in the
predictions made for the Diesel powertrains in 2020.
       The shift  strategy is discussed qualitatively; however, it is not described in enough detail
to understand exactly how it is accomplished.  Shift schedules are shown, however, no validation
is shown that  would indicate that these shift schedules are optimal as claimed.
       The torque  converter models are  standard models,  thus, the provided documentation is
adequate.
Hybrid Controls Presentations
       Several hybrid controls presentations were provided,  however, it was difficult to piece
together what information superseded the other since they were provided out of context. There
were several  good  slides showing dynamic programming results of different control  scenarios,
however, it is assumed that this was not used for the  mass simulation  since it would be
computationally impractical.  Thus, I expected to see some results comparing the offline control
results to the  actual control used  in the vehicle simulation, however,  this was not found.  The
major concern in this area is developing a control strategy that is near optimal for a wide variety
of hybrid architectures as well as architectures with varying component types  and sizes. Without
further validation in this area it is not clear that the hybrid results are valid since the control has
such an important role in this.
Shawn Midlam-Mohler - Peer Review                                            Page 19

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                  Review of supplemental materials
                          to the report
COMPUTER SIMULATION OF LIGHT-DUTY VEHICLE TECHNOLOGIES
         FOR GREENHOUSE GAS EMISSION REDUCTION
                 IN THE 2020-2025 TIMEFRAME
                         18 August 2011
                          Prepared for

                        ICF International
               Environmental Science & Policy Division
                   Contracts Management Group
             9300 Lee Highway, Fairfax, VA 22031-1207 USA
                      Robert F. Sawyer, PhD
                                    Partner

                  SAWYER ASSOCIATES
                               PO Box 6256
           Incline Village, NV 89450-6256 USA
                         Phone 1-510-305-6602
             email: rsawyer@sawyerassociates.us

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OVERVIEW

Reviewers of the report, Computer simulation of light-duty vehicle technologies for greenhouse
gas emission reduction in the 2020-2025 timeframe, 6 April 2011, prepared by Ricardo, Inc.
requested documentation of data used in the computer simulation. Of particular interest were the
engine maps and other performance information incorporated in the model. Ricardo provided 44
documents that included proprietary engine maps, proprietary Ricardo reports, technical papers
from the open literature, responses to USEPA questions, and other materials.
REVIEW
For each document, its title, a brief description of the nature of the material contained, and
comments on the nature of the material follows:

1) Ricardo, Action Item Response, 16 Feb 10,15 p. (proprietary)

A response to an EPA inquiry, this document deals with engine maps, engine map comparisons,
engine map plots, transmissions, batteries, motor and generator efficiency maps.

Comment: Ricardo responses and data selection seem reasonable.
2) Ricardo, Baseline Camry with Alternator Regen and Shift Optimizer Development of
Optimized Shifting Strategy Light Duty Vehicle Complex Systems Simulation EPA Contract
No. EP-W-07-064, work assignment 2-2, 15 Apr 10,10 p. (proprietary)

This document provides data on effectiveness of shift optimizer, including alternator regen, over
the FTP and HWFET.

Comment: Seems reasonable, improvements are greater on FTP than HWFET.
3) Carlson, R., et al., Argonne National Laboratory, On-Road Evaluation of Advanced
Hybrid Electric Vehicles over a Wide Range of Ambient Temperatures EVS23 — Paper #275,
15 p.

Paper reports on-road and dynamometer testing of two hybrid vehicles at cold (-14 degC) and
hot (33 decC) conditions. Fuel economy increases with temperature (except for highest
temperatures with the system which does not limit battery temperature).

Comment: Paper provides data showing importance of temperature on hybrid vehicle fuel
economy. These data are used by Ricardo to validate their battery warm up model, see next

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document.
4) Ricardo, Hybrid Battery Warm Up Model Validation - Update, Light Duty Vehicle
Complex Systems Simulation ,EPA Contract No. EP-W-07-064, work assignment 2-2,15
Mar 10, 5 p. (proprietary)

This report presents a simple battery heat transfer model for battery warm up and compares with
Argonne National Laboratory of the previous document.

Comment: Model produces adequate prediction of battery temperature.
5) Ricardo, BSFCMap Commparisons, LBDI vs EGR Boost & DVAfor STDI, OBDI, & EGR
Boost, Light Duty Vehicle Complex Systems Simulation, EPA Contract No. EP-W=07=064,
work assignment 2-2, 24 Feb 10, 20 p. (proprietary)

Comparison of engine technologies in terms of maps of percent difference in bsfc in bmep vs
rpm space allows visualization

Comment: Straight forward data analysis, presumably as requested by USEPA. Should aid in
understanding technology performance differences.
6) Mischker, K. and Denger, D., Requirements of a Fully Variable Valvetrain and
implementation using the Electro-Hydraulic Valve Control System EHVS, 24th International
Vienna Engine Symposium 2003,17 p.

This paper describes an electro-hydraulic valve system (EVHS) and limited data on reduction in
bsfc.

Comment: This would seem to be of limited quantitative value since technology is well advanced
beyond 2003.
7) Ricardo, Engine and Battery Warm-Up Methodology, Light Duty Vehicle Complex Systems
Simularion, 17 Feb 10,16 p. (proprietary)

Document reviews engine and battery warm-up strategies and provides a simple model.

Comment: The approach to battery warm-up is uncertain. Points to importance of test cycle (FTP
for fuel economy compliance versus test for EPA label versus real-world).
8) Ricardo, Response to EPA Questions on the Diesel Engine Fuel Maps, Supplemental
Graphs for Word Document, 16 Feb 10, lip. (proprietary)

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Document presents proposed diesel engine maps for MY2020+ vehicles.

Comment: Anticipated technologies are listed but how the maps were generated is not described.
Maps seem reasonable.
9) Ricardo, Assessment of Technology Options, Technologies related to Diesel Engines, 23
Nov 09,17 p.

Overview predicts continuation of low uptake in the U.S. LDA and LDT markets. Review deals
with various engine technologies to improve efficiency. Individual improvements 2 emissions.

Comment: It is not clear if comparison of EBDI and diesel is a equal technology level.
11) Ricardo, Hybrid Controls Follow-up, 10 Sep 11, 3 p. (proprietary)

Report discussed motor/general efficiency map used for 2020 technology. Projected efficiencies
peak at 95% but most P2 hybrid application if below 90% efficiency.

Comment: I am not qualified to assess if the projected motor/generator efficiencies are
appropriate for 2020-2025 as reported, but they seem low for 15 years in the future.
12) UOM, HiTor®for elecgtric, hybrid electric, and fuel cell powered vehicles, 18 Aug
09, based on test data map, 5 p.

Describes power electronics for motor generator control, including an efficiency map for
combined controller and motor based on test data.

Comment: Efficiency maps seem reasonable.

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13) Odvarka, E., et al., Electgric motor-generator for a hybrid electric vehicle,
Engineering Mechanics, 16,131-139, 2009, 9 p.

Describes electrical machine options of hybrid electric vehicles. Includes efficiency maps
for four technologies.

Comment: Data are of general interest, but date from 2003.
14) UOM, PowerPhase®75 for electric, hybrid electric, and fuel cell powered vehicles,
not dated, 6 p.

Described power electronics of vehicle electric power.

Comment: Similar to earlier brochure on power electronics, including efficiency map.


15) Ricardo, Future Engine Friction Assessment—Response to Action Item Question SI
Engine #4,18 Feb 11,4 p. (proprietary)

Projects continued reduction in engine friction, 2010-2020.

Comment: Data provide confirm projection.


16) Ricardo, Revised Follow-up Answers to 8 April 2010 Meeting with EPA and Ricardo,
19 Apr 10, 8 p. (proprietary)

Presents fueling maps for several technologies.

Comment: Adds to documentation of engine map data.


17) Alger, T., Southwest Research Institute, Examples of HEDGE Engines, 2009,4 p.

Presents engine map for a 2.4 L 14 High-Efficiency Dilute Gasoline Engine (HEDGE] engine
and compares with TC GDI engine, diesel engine.

Comment: Adds to documentation of engine map data.


18) Ricardo, Hybrid Controls Peer Review, 18 Feb 10, 31 p. (proprietary)

Review of hybrid control technologies for various architectures.  Review of battery operation in
cold weather.

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Comment: Thorough description of technologies and their operation characteristics. Battery
discussion covers similar material to an earlier paper.
19) Ricardo, Hybrids Control Strategy, 6 Aug 10, 41 p. (proprietary)

Discusses development of control strategies for P2 and Power Split hybrids.

Comment: includes efficiency maps and substantial technical detail including vehicle mass
effect.


20) Ricardo, Simulation Input Data Review,  4 Feb 10,14 p. (proprietary)

Described hybrid architectures with emphasis on machine-inverter combine efficiencies,
including efficiency maps.

Comment: More data, seems reasonable.


21) Ricardo, Assessment of Technology Options,  18 Nov 09,14 p. (proprietary)

Assessment of hybrid technologies using evaluation template.

Comment: Treats a range of hybrid technologies, including series hydraulic, giving projections
of CC>2 reduction benefits.


22) Ricardo, Simulation Input Data Review, 2 Feb 10, 30 p. (proprietary)

Document review modeling parameters for vehicle performance simulations, including engine
efficiency maps for a range of engine and transmission technologies.

Comment: This is the kind of data that we requested. Includes shift strategies. Seems reasonable
and well-documented.
23) Trapp, C., et al., Lean boost and NOx—strategies to control nitrogen oxide emissions, (no
date), 23 p.

Technical paper that describes lean burn direct injection (LBDI) engines, SCRNOX control, and
more. Includes some emission control cost data.

Comment: Not clear how this related to Ricardo's model development for EPA.

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24) Trapp, C., et al., NOx emission control options for the Lean Boos downsized gasoline
engine, (2 Feb 07), 34 p.

Paper compares lean NOxtrap and selective catalytic reduction technologies. Includes some
engine map data for NOX emissions. Includes cost data for aftertreatment.

Comment: Good academic paper with useful data. Not clear what or how Ricardo used.
25) Trap, C., et al., NOX emission control options for the lean boost downsized gasoline
engine, (2 Feb 07), 27 p.

Paper review international emissions regulation and technologies to meet.

Comment: This paper contains some of the same information as the preceding two. Simulated
date presented, again for SCR and LNT technologies.
26) Ricardo, Lean/Stoichiometric switching load for 2020 Hybrid Boost Concept, (no date), 2
P-

Presents space velocity and fuel maps.

Comment: Relevance not clear.


27) Ricardo, Proposed Lean/Stoichiometric switching load for hybrid boost concept, 29 Apr
10,1 p.

Identifies proposed lean zone operating region on engine map.

Comment: relevance not clear.


28) Lymburner, J.A., et al., Fuel consumption andNOx Trade-offs on a Port-Fuel-Injected
SI Gasoline Engine Equipped with a Lean NOX Trap, 4 Aug 09, 20 p.

This technical paper examines the trade-off between NOX control and CC>2 emissions.

Comment: Good work but relevance not clear.


29) Lotus(?), (from Kapus, P.E. et al., May 2007), Comparison to  other downsized engines

This one figure is a partial engine map with context vague.

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Comment: Significance is not clear.
30) Turner, J.W.G., et al., Sabre: a cost-effective engine technology combination of high
efficiency, high performance and low CO2 emissions, Low Carbon Vehicles, May 09, IMechE
Proceedings, 14 p.

This paper describes a technology for reducing COS emissions in a downsized engine. The Sabre
engine is a collaboration between Lotus Engineering and Continental Automotive Systems.

Comment: Limited performance data provided.
31) Ricardo, Conventional Automatic Nominal Results, 16 Mar 10,17 p. (proprietary)

This presentation includes mileage versus 0-60 mph time maps for a range of vehicles (light duty
to large truck). Also presented are comparisons of fuel economy for different regulatory test
cycles and technologies.

Comment: Significance not clear.
32) Ricardo, Report on light-duty vehicle technology package optimization, 4 Dec 09, 32 p.

This is a progress report on Ricardo's modeling work for the EPA. A range of engine
technologies, hybrid technologies, transmission, and vehicle technologies are described.

Comment: A comprehensive list of near term technologies are included. The report is incomplete
and optimization apparent is not included here.
33) Ricardo, Revised follow-up answers for hybrid action items, 23 Jun 10,16 p.
(proprietary)

This report answers questions on electric drive train efficiency, battery characteristics, and
available braking energy, and more.

Comment: Interesting data, but implication not clear.
34) Ricardo, Response to questions regarding the generation of the dieselfuel maps for fuel
efficiency simulation, 16 Feb 10,10 p. (proprietary)

Paper answers a series of EPA questions on how the diesel fuel maps were generated.

Comment: This is relevant information and provides a convincing description of the technical

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basis for the diesel fuel maps.


35) Ricardo, Scaling Methodology Review, 19 Jan 10, 9 p.

This document explains the scaling methodology used in the EASY5 vehicle model.

Comment: This description in clear and useful.


36) Ricardo, SCR as an Enablerfor Low CO2 Gasoline Applications, no date, 35 p.

This presentation describes technology and implementation for exhaust NOX reduction for lean
burn gasoline engines.

Comment: Comprehensive discussion of technology, but if and how inconcorporated in the
model not clear.


37) Ricardo, Simulation Input Data Review, 18 Mar 10,17 p. (proprietary)

This document reviews the engine maps used in the model. Includes are examples of the baseline
maps plus modifications associated with a range of technologies. Data apply to all 7 vehicle
classes.

Comment: This is the documentation that was missing in the earlier review material. Looks
reasonable and is reassuring.


38) Ricardo, Assessment of Technology Options, 19 Nov 09, 22 p. (confidential)

This document reviews and rates a range of spark-ignition adaptable technologies to reduce CC>2
emissions. Biofuels are included.

Comment: An interesting compendium but some previously reported.
39) Shimizu, R., et al., Analysis of a Lean Burn Combustion Concept for Hybrid Vehicles,
2009,13 p.

A technical paper, this document describes early (1984) and more recent Toyota lean burn
engines.

Comment: Interesting technical description but no clear if or how used in the Ricardo model.

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40) Takoaka, T., et al., Toyota, Super high efficient gasoline engine for Toyota hybrid system,
(no date), 16 p.

This paper describes the hybrid system, 1C engine interaction that allows increased 1C engine
efficiency.

Comment: Of general interest but application to the model not clear.
41) Ricardo, Assessment of Technology Options, Technologies related to Transmission and
Driveline, 19 Nov 09, 21 p.

This document described transmission technologies, including timing of their introduction.

Comment: Seems reasonable.
42) Ricardo, Transient Performance of Advanced Turbocharged Engines, 15 Sep 10,19 p.
(proprietary)

This report reviews expected advances in boosting technologies and anticipated effects on
vehicle performance.

Comment: Interesting information but how it impacts model is not clear.
43) Kapus, P., Potential of VVA Systems for Improvement of CO2 Pollutant Emission and
Performance of Combustion Engines, 30 Nov 2006, 9 p.

This is a technical paper describing variable valve actuation approaches and performance effects.

Comment: Useful general technical information.
44) Ricardo, Assessment of Technology Options, Technologies related to Vehicle-level
Systems, 24 Nov 09,16 p.

This review of vehicle technologies that can improve vehicle efficiencies provides a basic
description and information on expected levels of CC>2 reduction.

Comment: This is a clear description of anticipated improvements in vehicle technologies that
reduce load and fuel consumption.
                                          10

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CONCLUSIONS

Ricardo has provided material, which is stated to be the data incorporated in the computer
simulation. These data are consistent with the data expected to be the basis of the simulation. It is
impossible to establish a precise correspondence between the data and the model. The
performance data covered by the 44 separate documents seem reasonable and provide additional
assurance that the simulation is soundly based on measured performance. There is no reason to
doubt either the integrity or capability of Ricardo in their incorporation of appropriate data into
their simulation model.
                                           11

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           DRAFT PROJECT REPORT
   COMPUTER SIMULATION OF LIGHT-DUTY
        VEHICLE TECHNOLOGIES FOR
  GREENHOUSE GAS EMISSION REDUCTION
        IN THE 2020-2025 TIMEFRAME
Prepared for:      Office of Transportation and Air Quality
               U.S. Environmental Protection Agency
               2565 Plymouth Road
               Ann Arbor, Michigan 48105

Prepared by:      Ricardo, Inc.
               40000 Ricardo Drive
               Van Buren Twp., Michigan 48111

               Systems Research and Applications Corporation (SRA)
               652 Peter Jefferson Parkway, Suite 300
               Charlottesville, Virginia 22911
EPA Contract No.:
Work Assignment:
Ricardo Archive:
Date:
EP-W-07-064
2-2
RD.10/157405.6
6 April 2011
Client Confidential and Deliberative

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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
                     The following organizations contributed to this study:

                                         Ricardo,  Inc.
                    SRA International, Inc. (Perrin  Quarles Associates, Inc.)
                            U.S. Environmental Protection Agency
                                California Air Resources Board
                         International Council on Clean Transportation
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
       COMPUTER SIMULATION OF LIGHT-DUTY VEHICLE TECHNOLOGIES FOR
       GREENHOUSE GAS EMISSION REDUCTION IN THE 2020-2025 TIMEFRAME

                               EXECUTIVE SUMMARY

Ricardo, Inc. was subcontracted by SRA International,  Inc. (SRA), under contract to the United
States Environmental Protection Agency (EPA) to assess the effectiveness of future light duty
vehicle  (LDV) technologies on  future vehicle  performance  and  greenhouse  gas  (GHG)
emissions in the 2020-2025 timeframe. GHG emissions are a globally  important issue, and
EPA's Office of Transportation and Air Quality (OTAQ) has been chartered with examining the
GHG  emissions  reduction  potential of LDVs,  including passenger cars and light-duty trucks.
This program was performed between  October 2009 and March 2011.

The scope of this project was to execute an independent and objective analytical study of LDV
technologies likely  to  be  available within  the 2020-2025 timeframe, and to develop  a data
visualization tool to allow users to evaluate the effectiveness of LDV technology packages for
their potential to reduce GHG emissions and their effect on vehicle performance. This study
assessed the effectiveness of a broad range  of technologies, including powertrain architecture
(conventional and hybrid),  engine, transmission, and other vehicle attributes such as engine
displacement, final drive ratio, vehicle  weight,  and rolling resistance on seven light-duty vehicle
classes. The methodology used  in this program surveyed the broad design space using robust
physics-based modeling  tools and generated a computationally efficient response surface  to
enable extremely fast surveying of the design  space within a data visualization tool. During this
effort, quality assurance checks were  employed to  ensure that the simulation results were a
valid representation of the performance of the  vehicle. Through the use of the data visualization
tool, users can query the design space on a real time basis while capturing interactions between
technologies that may not be identified from individual simulations.

This report documents the work done on the program  "Computer  Simulation of Light  Duty
Vehicle Technologies for Greenhouse Gas Emission Reduction in the 2020-2025 Timeframe."
This work  has included  identifying  and  selecting  technologies for inclusion in  the study,
developing and validating baseline models, and developing the data visualization tool.
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                                TABLE OF CONTENTS
                                                                                PAGE
1.   INTRODUCTION	8
2.   OBJECTIVES	8
3.   BACKGROUND	9
  3.1    Study Background	9
  3.2    Ground Rules for Study	9
  3.3    Technology Package Selection Process	10
  3.4    Complex Systems Modeling Approach	..^^f^.	10
  3.5    Data Visualization Tool	11
4.   TECHNOLOGY REVIEW AND SELECTION	11
  4.1    Advanced Engine Technologies	12
    4.1.1    Advanced Valvetrains	12
    4.1.1.1  Cam-Profile Switching Valvetrain	12
    4.1.1.2  Digital Valve Actuation Valvetrain	12
    4.1.2    Direct Injection Fuel Systems	13
    4.1.3    Boosting System	13
    4.1.4    Other Engine Technologies	14
  4.2    Engine Configurations..^^	14
    4.2.1    Stoichiometric Dl Turbo	15
    4.2.2    Lean-Stoichiometric Switching	15
    4.2.3    EGRDI Turbo	16
    4.2.4    Atkinson Cycle	16
    4.2.5    Advanced Diesel	16
  4.3    Hybrid Technologies	17
    4.3.1    Micro Hybrid: Stop-Start	17
    4.3.2    P2 Parallel Hybrid	17
    4.3.3    Input Powersplit	18
  4.4    Transmission Technologies	18
    4.4.1    Automatic Transmission	19
    4.4.2    Dual Clutch Transmission (DCT)	19
    4.4.3    Launch Device: Wet Clutch	19
    4.4.4    Launch Device: Dry Clutch Advancements	20
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe

                           TABLE OF CONTENTS (CONT.)
                                                                              PAGE
    4.4.5    Launch Device: Multi-Damper Torque Converter	20
    4.4.6    Shifting Clutch Technology	20
    4.4.7    Improved Kinematic Design	20
    4.4.8    Dry Sump	20
    4.4.9    Efficient Components	20
    4.4.10   Super Finishing	21
    4.4.11   Lubrication	21
  4.5   Vehicle Technologies	21
    4.5.1    Intelligent Cooling Systems	^^f..	21
    4.5.2    Electric Power Assisted Steering	21
5.   TECHNOLOGY BUNDLES AND SIMULATION MATRICES	22
    5.1    Technology Options Considered	22
    5.2   Vehicle configurations and technology combinations	23
6.   VEHICLE MODEL	24
    6.1    Baseline Conventional Vehicle Models	24
    6.2   Baseline Hybrid Vehicle Models	25
    6.3   Engine Models	25
    6.3.1    Warm-up Methodology	26
    6.3.2    Accessories Models	26
    6.4   Transmission Models	27
    6.5   Torque Converter Models	28
    6.6   Final Drive Differential Model	29
    6.7   Driver Model	29
    6.8   Hybrid Models	29
7.   MODEL VALIDATION RESULTS	30
    7.1    Baseline Conventional Vehicle Models	30
    7.2   Nominal Runs	31
8.   COMPLEX SYSTEMS MODEL VALIDATION	31
    8.1    Evaluation of Design Space	31
    8.2   Response Surface Modeling	32
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
                           TABLE OF CONTENTS (CONT.)
                                                                             PAGE
9.   RESULTS	33
    9.1    Basic Results of Simulation	33
    9.2    Design Space Query	33
    9.3    Exploration of the Design Space	33
    9.4    Identification and Use of the Efficient Frontier	39
10. RECOMMENDATIONS FOR FURTHER WORK	39
11. CONCLUSIONS	40
12. REFERENCES	41
APPENDICES	42
Appendix 1: Abbreviations	.^^K.	42
Appendix 2: Output Factors for Study	it*.	43
Appendix 3: Nominal Runs Results	44
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
                                   LIST OF FIGURES

Figure 3.1: Technology package selection process	10
Figure 6.1: Comparison of CVT and optimized DCT gear ratios over drive cycle	28
Figure 9.1: Design Space Query screen in Data Visualization Tool	34
Figure 9.2: Design Space Analysis screen in Data Visualization Tool	35
Figure 9.3: Full Size Car Design Space Analysis example	36
Figure 9.4: Full Size Car Design Space Analysis example	37
Figure 9.5: Full Size Car Design Space Analysis example	37
Figure 9.6: Standard Car design space analysis example comparing powertrains with EGR Dl
          Turbo engine	38
Figure 9.7: Efficient Frontier screen of Data Visualization Tool with example plot	39



                                   LIST OF TABLES

Table 5.1: Engine technology package definition	22
Table 5.2: Hybrid technology package definition	22
Table 5.3: Transmission technology package definition. ...^A	23
Table 5.4: Baseline and Conventional Stop-Start vehicle simulation matrix	23
Table 5.5: P2 and Input Powersplit hybrid simulation matrix	24
Table 6.1: Vehicle classes and baseline exemplar vehicles	25
Table 6.2: Advanced powertrain configurations and  baseline exemplar vehicles	25
Table 7.1: Baseline vehicle fuel economy performance	31
Table 8.1: Continuous input parameter sweep ranges with conventional powertrain	32
Table 8.2: Continuous input variable sweep ranges  for P2 and Powersplit hybrid powertrains..32
Table A3.1: Nominal Runs Results	45
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
1. INTRODUCTION

Ricardo was subcontracted by SRA International (SRA), under contract to the United States
Environmental Protection Agency (EPA) to assess the effectiveness of future LDV technologies
on future vehicle  performance  and  GHG  emissions  in  the 2020-2025 timeframe.  GHG
emissions are a globally important issue, and EPA's Office of Transportation  and Air Quality
(OTAQ) has been  charged with  examining the  GHG emissions reduction  potential of LDVs,
including passenger cars and light-duty trucks.

SRA is an interdisciplinary environmental consulting firm specializing in environmental program
development and implementation support, with a major focus on air quality and GHG reduction
initiatives. In addition  to the SRA-Ricardo team working for EPA, other stakeholders for the
program  included the  International Council on Clean Transportation (ICCT) and the California
Air Resources Board (ARE). Representatives from each stakeholder,  together with EPA staff,
formed the Advisory Committee for this project

Ricardo,  Inc. is the U.S. division  of Ricardo pic., a global engineering consultancy with nearly
100 years of specialized engineering expertise and technical experience  in internal combustion
engines,  transmissions, and automotive vehicle development. This  program  was performed
between October 2009 and March 2011.
The scope of the program was to execute an independent and objective analytical study of LDV
technologies  likely  to  be available  in  the 2020-2025 timeframe,  and  to  develop a  data
visualization tool to  allow users  to evaluate the effectiveness of LDV technology packages for
their potential to reduce GHG emissions. An assessment of the effect of these technologies on
LDV cost was beyond the scope of this study.

This work was done in collaboration  with EPA and  its external  partners, and the approach
included the following activities:

   •   Extrapolate selected technologies to their expected performance and efficiency levels in
       the 2020-2025 timeframe.
   •   Conduct detailed simulation of the technologies over a large design space,  including a
       range of vehicle classes, powertrain  architectures, engine designs, and transmission
       designs, as  well  as  parameters  describing  these configurations, such  as engine
       displacement, final drive ratio, and vehicle rolling resistance.
   •   Interpolate the results over the design space  using  a  functional representation of the
       responses to the varied model input factors.
   •   Develop a  Data Visualization Tool to facilitate interrogation  of the simulation results over
       the design  space.
2. OBJECTIVES

The  goal  of this technical  program has  been to evaluate  objectively the effectiveness and
performance of a large LDV design space with powertrain technologies likely to be available in
the 2020-2025 timeframe,  and thereby assess the potential for GHG emissions reduction in
these future vehicles  while also understanding  the  effects  of these  technologies  on vehicle
performance.
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe


3.  BACKGROUND

   3.1  Study Background

EPA and other program stakeholders have a mutual interest in improving the environmental
performance  and  efficiency of cars, trucks, buses,  and transportation systems to protect and
improve public health, the environment,  and quality of life.  Additionally,  reduction of GHG
emissions—emphasizing   carbon  dioxide  (CO2)—is  an  increasing  priority   of  national
governments  and other policymakers worldwide.

The purpose  of this study is  to define and evaluate potential technologies that  may improve
GHG  emissions in LDVs in the 2020-2025 timeframe. These technologies  represent a mixture
of future mainstream technologies and some emerging technologies for the study timeframe.

   3.2  Ground Rules for Study
Several ground rules for the study were agreed at the beginning of the program to bound the
design space considered in the  study. These  ground rules identified content that should be
included in the study as well as content that should be excluded.
Some examples of the ground rules include the following items for the technology assessment:

   •   Seven vehicle classes will be included, as described below
   •   LDV technologies must have the potential to be commercially deployed in 2020-2025
   •   Vehicle sizes,  particularly footprint and  interior space,  for each  class will be  largely
       unchanged from 2010 to 2020-2025
   •   Hybrid vehicles will use an advanced hybrid control strategy, focusing on battery state of
       charge (SOC) management, but not at the expense of drivability
   •   Vehicles will use fuels that are equivalent to either 87 octane pump gasoline or 40
       cetane pump diesel
   •   2020-2025 vehicles  will meet future  California LEV  III  requirements for criteria
       pollutants, which are assumed to be equivalent to current SULEV II (or EPA Tier 2 Bin 2)
       levels

Likewise, the Advisory Committee  agreed that the  technology assessment for this program
should exclude the following:

   •   Charge-depleting powertrains, such as plug-in hybrid electric vehicles (PHEV) or battery
       electric vehicles (EV)
   •   Fuel cell power plants for fuel cell-electric vehicles (FCEV)
   •   Non-reciprocating internal combustion engines (ICE) or external combustion engines
   •   Manual transmissions and automated manual transmissions (AMT) with a single clutch
   •   Kinetic energy recovery systems (KERS) other than battery systems
   •   Intelligent  vehicle to vehicle  (V2V) and vehicle to  infrastructure  (V2I) optimization
       technology
   •   Bottoming cycles, such as organic Rankine cycles, for energy recovery
   •   Vehicle safety  systems or structures will not be explicitly modeled for vehicles. A full
       safety analysis of the technologies presented in this report is beyond the scope of this
       study
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
The seven vehicle classes considered in this study are the following, with a currently available
example vehicle given for each class:

   1.  Small (B-class) Car, such as the Toyota Yaris;
   2.  Standard (D-class) Car, such as the Toyota Camry;
   3.  Small Multi-Purpose Vehicle (MPV), such as the Saturn Vue;
   4.  Full Sized Car, such as the Chrysler 300;
   5.  Large MPV, such as the  Dodge Grand Caravan;
   6.  Light-Duty Truck (LOT), such as the Ford F150; and
   7.  Light Heavy-Duty Truck (LHDT), such as the GM HD3500.
   3.3 Technology Package Selection Process

The program team  used the process shown in Figure 3.1  to identify the technology options
described in Chapter 4 and downselect to the technology packages described in Chapter 5.
     Technology
     Identification
   Subject
    Matter
    Expert
Assessment
  Advisory
Committee
  Review &
Technology
Discussion
Technology
  Package
 Selection
                   Figure 3.1: Technology package selection process.


The program team first developed a comprehensive list of potential technologies that could be in
use on vehicles  in  the  study timeframe, 2020-2025.  These technologies were grouped by
subject area, such as transmissions, engines, or vehicle, and given to  Ricardo subject matter
experts (SMEs) for assessment and evaluation.  These SME  assessments were reviewed with
and discussed by the program's Advisory Committee. Technology options were assembled into
technology packages for use in the vehicle performance simulations.

   3.4 Complex Systems Modeling (CSM) Approach

Complex systems modeling (CSM)  is an objective, scientific approach that supports decision
making when there are a large number of factors  to consider that influence  the outcome, as with
LDV development for vehicle performance and GHG  emissions reduction. To be objective,
performance metrics were identified by the Advisory Committee; these metrics were outputs of
the vehicle performance simulation effort and characterize key vehicle  attributes. To be
scientific,  the performance simulations use a physics-based modeling approach for detailed
simulation of the vehicle.

The design of experiments (DoE)  approach surveys the design space in a way that extracts the
maximum information using  a limited  budget of  simulation runs. The purpose of the  DoE
simulation matrix was to efficiently explore a comprehensive potential  design space for LDVs in
the 2020-2025  timeframe.  The simulation matrix was  designed  to  generate selected
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performance results over the selected drive cycles, such as fuel consumption or acceleration
times.

A statistical analysis was used to correlate variations in the input factors to variations  in the
output  factors.  Because of  the complex  nature of the  LDV configurations and constituent
technology packages,  a neural network  approach was used  to  quantify the  relationships
between input and output factors over the design space explored in  the simulations. The result
of this  analysis  was a set of response surface models (RSM) that represent in simplified form
the complex relationships between the input and output factors in  the design space.

   3.5 Data Visualization Tool
The Data Visualization Tool allows the user to query the RSM and develop an understanding of
how various combinations of future technologies may affect GHG emissions and other vehicle
performance metrics. Vehicle configurations  with unacceptable performance, such as too-low
combined fuel economy or too-slow acceleration times, can be excluded from further study.

The Data Visualization Tool uses the RSM set generated by the Complex Systems approach to
represent the vehicle performance simulation results over the design space. These simulations
cover multiple variations of vehicle configuration, including several  combinations of advanced
powertrain and vehicle technologies in the seven LDV classes.

The tool samples vehicle configurations from a selected subset of the design space by using
Monte Carlo type capabilities to pick input parameter values from a uniform distribution. Defining
selected portions of the design space and plotting  the results visualizes  the effect of these
parameters  on  vehicle fuel economy and  performance,  allowing  trade  off analysis via
constraints setting to  be performed over a  wide  design space representing the  2020-2025
technologies as applied.
4. TECHNOLOGY REVIEW AND SELECTION

Following the process outlined above, a broad range of potential technologies were identified for
consideration in the study. These technologies were evaluated qualitatively against the following
criteria for further consideration:

   •   Potential of the technology to improve GHG emissions on a tank to wheels basis
   •   State  of  development  and  commercialization of the technology  in the  2020-2025
       timeframe
   •   Current (2010) maturity of the technology

Based on these criteria, a subset of the full list of technologies was selected for inclusion in the
study. These technologies are described in this chapter.

In the study timeframe of 2020-2025, spark-ignited (SI) engines are projected to continue to be
the dominant powertrain in the U.S. light-duty vehicle market, especially since the efficiency of
SI engines is expected to approach the efficiency of compression ignition (Cl, or diesel) engines
at the required 2020-2025 emissions levels.  Nevertheless, diesel  engines are expected to
contribute to future GHG emissions reduction, especially for the heavier vehicle classes. Thus,
diesel engine technologies were also considered in the study.
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The first two sections of this chapter therefore describe the technologies expected to appear in
these future engines and specific engine configurations, respectively. The other sections in this
chapter describe the transmission and driveline, vehicle,  and hybrid system technologies that
were  included  in  the  overall design  space  of  the  study.  The  implementation  of these
technologies in the vehicle performance models is described in Chapter 6, Vehicle Model.

   4.1 Advanced Engine Technologies

The primary challenge  for advanced engines in the 2020-2025 timeframe is  to reduce GHG
emissions and maintain performance without increasing  criteria pollutants. This challenge is
expected to be met through  a range of improvements, from the application of highly-efficient
downsized  engines through to detailed optimization of components and systems. This section
describes specific technologies or systems that are expected to be included in future  engines,
each  of which supports the  overall goal  of  reduced GHG emissions in future