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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Peer Review Response Document November 29, 2011
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
12
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Table 1: Response to Individual Peer Review Comments
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
13
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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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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
16
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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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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
18
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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
20
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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
21
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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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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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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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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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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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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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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
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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
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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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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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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
33
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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
34
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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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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
valueused 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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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
40
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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
41
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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
42
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Table 1: Response to Individual Peer Review Comments
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
43
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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
44
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Table 1: Response to Individual Peer Review Comments
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
45
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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
50
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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
51
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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
53
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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
54
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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
55
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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
57
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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
58
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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
59
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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
60
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T
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
61
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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
62
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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
63
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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
64
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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
65
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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
66
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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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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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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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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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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.
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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
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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
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'---- 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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Specific
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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)
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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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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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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
96
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Table 1: Response to Individual Peer Review Comments
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
97
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Table 1: Response to Individual Peer Review Comments
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
98
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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
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
99
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November 29, 2011
Table 1: Response to Individual Peer Review Comments
T
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, HiTorฎforelecgtric, 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, PowerPhaseฎ75 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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November 29, 2011
Table 1: Response to Individual Peer Review Comments
T
Specific
e Question Assump
Comment
Completeness
433
Ricardo, Future Engine Friction AssessmentResponse 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 NOxstrategies 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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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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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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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
-------
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.
-------
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
-------
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;
-------
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.
-------
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).
-------
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).
-------
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.
-------
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.
-------
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
Mซ
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.
-------
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.
-------
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
-------
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
Mซ
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
-------
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
-------
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
Mซ
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
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197
63
64
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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
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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
Mซ
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.
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Verbatim Peer Reviewer Comments in Response to
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Inputs and
Specific
Assumption/Topic
Comment
Excerpt
Review
Round
Reviewer
Comment
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
Inputs and
Parameters
21
22
23
24
25
26
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1
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
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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
Inputs and
Parameters
Inputs and
Parameters
27
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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
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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, HiTorฎ 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, PowerPhaseฎ75 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 Er* 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?
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Verbatim Peer Reviewer Comments in Response to
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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
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1
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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.
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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
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36
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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?
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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
Simulation
methodology
Specific
Assumption/Topic
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
McBroom
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.
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Verbatim Peer Reviewer Comments in Response to
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Charge Question
Topic
Specific
Assumption/Topic
Comment
Excerpt
Review
Round
Reviewer
Comment
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Warm-up
methodology
(Section 6.3.1)
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McBroom
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
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Comment
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Round
Reviewer
Comment
vehicle config.
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
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Simulation
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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.
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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
Comment
Excerpt
Mn
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Reviewer
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).
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Verbatim Peer Reviewer Comments in Response to
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Charge Question
Topic
Specific
Assumption/Topic
Comment
Excerpt
Review
Round
Reviewer
Comment
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
Simulation
methodology
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Sawyer
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.
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Verbatim Peer Reviewer Comments in Response to
Charge Questions
Charge Question
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
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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?
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Verbatim Peer Reviewer Comments in Response to
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Charge Question
Topic
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
Mซ
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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).
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Verbatim Peer Reviewer Comments in Response to
Charge Questions
Charge Question
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
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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
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Comment
Excerpt
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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
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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
Charge Questions
Charge Question
Topic
Results
Results
Results
Results
Results
Results
Results
Results
Results
Specific
Assumption/Topic
Comment
Excerpt
Mn
44
45
46
109
110
111
113
117
416
Review
Round
1
1
1
1
1
1
1
1
2
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
-------
Verbatim Peer Reviewer Comments in Response to
Charge Questions
Charge Question
Topic
Results
Results
Results
Results
Results
Specific
Assumption/Topic
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
-------
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
-------
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
Mซ
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
-------
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
-------
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
-------
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
-------
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
Mซ
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
Mซ
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
Charge Question
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
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
Mซ
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
Mซ
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
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Topic
Specific
Assumption/Topic
Comment
Excerpt
Review
Round
Reviewer
Comment
scaling laws are used.
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
53
54
149
150
151
152
153
154
155
156
157
158
1
1
1
1
1
1
1
1
1
1
1
1
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
Charge Questions
Charge Question
Topic
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
Recommendations
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.
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Charge Quest on Specfc Comment R
%. . . .. . . Excerpt 0 . Reviewer Comment
Recommendations
Recommendations
Recommendations
Recommendations
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.
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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.
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Topic
Other Comments
Other Comments
Other Comments
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.
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Other Comments
Other Comments
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.
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Verbatim Peer Reviewer Comments in Response to
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Topic
Other Comments
Other Comments
Other Comments
Other Comments
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.
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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
Other Comments
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
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Review
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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
Charge Question
Topic
Other Comments
Other Comments
Other Comments
Other Comments
Other Comments
Other Comments
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
Mซ
59
275
276
277
278
279
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1
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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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Verbatim Peer Reviewer Comments in Response to
Charge Questions
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
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1
1
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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 4Qป?rBIH|
1
c
[ป: . :.,
., ,
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
>;pป-ปซl ; 141 MI
F;> 3 IS. 2M4 Pnnj macdr
W: A'ซซ PJ"^> Mac-, re a AC Drr< Eitrcy
I
i
1:3
i:>
3
'
* *
"
2C33
Figure 34: Eiซclrlc 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).
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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
Assanis, 4
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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
Assanis, 5
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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
Assanis, 7
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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.
Assanis, 8
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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
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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.
Assanis, 11
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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.
Assanis, 12
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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
-------
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
-------
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
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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"
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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
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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
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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.)
Assanis, 39
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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
ป 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
ซ Society of Automotive Engineers Outstanding Younger Member - South Texas
Section 1 994-95
ซ R & D Magazine 2004 R&D 100 Award for RAPTOR software (for the 100 most
significant innovations)
and '99
Personal
ซ 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.
-------
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
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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
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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
-------
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.
W. R. Wade
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
5/15/2011
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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
5/15/2011
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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)
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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).
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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.
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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.
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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.
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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.
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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.
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0 1000 2000 3000 4000 6000 6000
EngtneSp^ad jn/mln]
Figure 19: BSFC oฅer 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
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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
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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.
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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* EwartciVrtซrPump Mattilrw 5 l; TcondKlonlnj Drt ซErrcuncy
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.
21
W. R. Wade
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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
W. R. Wade
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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
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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).
-------
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.
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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.
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.
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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.
(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
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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
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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.)
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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)
-------
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, HiTorฎfor 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, PowerPhaseฎ75 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 AssessmentResponse 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.
-------
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 NOxstrategies 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.
-------
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
-------
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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E-1
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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
6 April 2011
Ricardo, Inc. Page 2
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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.
6 April 2011
Ricardo, Inc. Page 3
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
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
6 April 2011 Ricardo, Inc. Page 4
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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
6 April 2011 Ricardo, Inc. Page 5
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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
6 April 2011
Ricardo, Inc. Page 6
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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
6 April 2011
Ricardo, Inc. Page 7
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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.
6 April 2011 Ricardo, Inc. Page 8
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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
emissionsemphasizing 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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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 vehicles. The
following section, 4.2, Engine Configurations, describes the complete engine technology
packages that combine these technologies.
4.1.1 Advanced Valvetrains
Several advances in valvetrain technology are expected to be available in the study timeframe.
These technologies are expected to apply to engines across the whole set of vehicle classes
examined in the study.
Advanced valvetrain systems improve fuel consumption and GHG emissions mainly by
improving engine breathing, thereby reducing pumping losses in the engine. The pumping loss
mitigation provides larger benefits at part-load operation, such as during urban driving.
Advanced valvetrains also support engine downsizing, which provides fuel consumption benefits
across the complete engine operating map. Lastly, they can be used to support faster
aftertreatment warm-up through varied timing, leading to additional, synergistic gains if the
faster aftertreatment warm-up creates a benefit to tailpipe-out NOX emissions that can be traded
off to improve GHG emissions.
Two advanced valvetrain options, cam-profile switching and digital valve actuation, were
included in the study and are discussed below.
4.1.1.1 Cam-Profile Switching Valvetrain
Cam-profile switching (CPS) systems use a hydraulically-actuated mechanical system to select
between two or three cam profiles. CPS systems, such as the Honda VTEC, Mitsubishi MIVEC,
Porsche VarioCam, and Audi Valvelift, have been developed by a number of Japanese and
European manufacturers. CPS systems can be designed to improve low-speed torque or to
improve fuel economy by reducing pumping losses at light load. CPS systems are applicable in
all LDV classes. The benefit to GHG emissions is expected in part-load operation, and will
therefore provide a larger benefit in city driving than in highway driving.
4.1.1.2 Digital Valve Actuation Valvetrain
Digital valve actuation (DVA) uses a mechanical, hydraulic, or electrical system to actuate the
valves independently of a camshaft. The full realization of DVA in the study timeframe will be a
camless DVA system, where there is no mechanical linkage between the engine crank and the
valves. The engine fueling maps with DVA were assumed to use camless DVA systems, such
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as electrohydraulic or electromagnetic systems. Electropneumatic systems are less mature
currently, but may yet be available late in the timeframe. An example DVA system in current
production is the Fiat MultiAir system, an electro-hydraulic system (Fiat, 2009) that still uses a
camshaft to provide the primary timing for the valve open and valve close events. The DVA
system could be implemented to provide flexibility, with valve event timing, valve lift profiles, or
both. As with the CPS systems, the main benefit in GHG emissions is a result of reducing
pumping losses at part-load operation.
4.1.2 Direct Injection Fuel Systems
Direct injection (Dl) fuel systems are the standard fuel injection system in use on current diesel
engines. One of the significant changes expected by the 2020-2025 timeframe is a continued
transition from port fuel injection (PFI) to Dl in SI engines as well. For SI engines with Dl, the
fuel is injected directly into the combustion cylinder before being ignited. Dl fuel systems inject
the fuel at a higher pressure than PFI injectors do, and allow the use of multiple injection events
to support advanced combustion control. SI engines with Dl were first introduced in Japan in
1996, and an increasing number of new SI engines now feature Dl.
Dl improves fuel economy because it facilitates a higher compression ratio in the engine, which
helps improve the engine's volumetric and thermal efficiency. Using Dl improves fuel
consumption across the full range of engine operation, including at part-load and high-load
conditions.
The program team projected that in the 2020-2025 timeframe, spray-guided Dl will be the
mainstream Dl technology in use, supplanting wall guided Dl. Spray-guided Dl offers the
capability to deliver a stratified chargewhere the fuel concentration decreases away from the
spark plugthat will facilitate lower GHG emissions through lean-burn operation.
For diesel engines, emissions requirements will cause the injection pressures to continue to
increase to the 2000-2400 bar injection pressure range. These very high injection pressures
support better combustion and reduced engine-out emissions. In addition, multiple injection
events will be used to better control the onset and progress of the combustion event in the
cylinder.
4.1.3 Boosting System
Using devices to boost the engine's intake pressure will increase the torque and power available
from a given engine displacement. By increasing the boost pressure while decreasing engine
displacement, the power level is maintained while reducing pumping work in the engine through
shifting engine operation to higher-load operating points.
The advanced engines in the 2020-2025 timeframe are expected to have advanced boosting
systems to increase the pressure of the intake charge. Various boosting approaches are
possible, such as superchargers, turbochargers, and electric motor-driven compressors and
turbines. The appropriate technology for 2020-2025 will need to provide cost-effective
improvement in performance and efficiency while mitigating turbo lag.
Turbocharged engines in the 2020-2025 timeframe are expected to have an advanced boost
strategy that mitigates turbo lag while providing a smooth acceleration feel.
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The advanced engines with boost systems were assumed to have two-stage series sequential
turbocharger systems. Turbocharging means that there is some risk of the vehicle performance
being affected by turbo lag, a delay in the torque rise that results from the dynamics of the gas
flow through the engine. Turbo lag is most significant during hard acceleration events, especially
when the engine starts at or near its idle speed and load. Mitigating turbo lag means carefully
choosing the capacities of the high pressure and low pressure compressors and turbines and
connecting pipes to provide acceptable steady-state torque across the engine speed range and
an acceptable transient rate of torque rise, often expressed as the time required to reach 85% of
maximum torque at a given engine speed. Modeling turbo-lag effects is described in Section
6.3, below.
4.1.4 Other Engine Technologies
Other engine technologies incorporated into the future engines were further improvements in
engine friction leading to a global reduction in engine fuel consumption. This friction reduction is
expected to result from a combination of technology advances, including piston ringpack, bore
finish, lower-viscosity crankcase lubricants, low-friction coatings, valvetrain components, and
bearing technology. The details of these improvements in engine friction were not explicitly
itemized in this study, and were instead treated as a global engine friction reduction.
Another approach is to optimize the overall engine design, for example, by combining engine
components to reduce mass and thermal inertia, giving an improved package and faster warm-
up. Ancillary systems may also be electrified to remove the front engine accessory drive (FEAD)
and allow variable accessory performance independent of engine speed. (See, for example,
Section 4.5.2, Electric Power Assisted Steering.) The combination of components, such as the
exhaust manifold and cylinder head design, should improve the response time for turbocharging
and aftertreatment warm-up. Electrification of FEAD components, such as the electrical coolant
pump, oil pump, or AC compressor, reduces parasitic losses on the engine and allows
accessory operation to be optimized for the operating point independently of the engine.
4.2 Engine Configurations
Several engine configurations were defined using combinations of the advanced engine
technologies described in Section 4.1 based on an assessment of what would be in mainstream
use in the 2020-2025 timeframe. Five main types of engines were used in the study, and are
described in this section.
The engines considered for the 2020-2025 timeframe were developed using two main methods.
The first method, used with the boosted SI engines, was to review the reported performance of
current research engines, and assume that these current research engines would closely
resemble the production engines of the 2020-2025 timeframe. With this approach, current
research engines would be refined to meet production standards, including manufacturability,
cost, and durability. The second method, used with the Atkinson and diesel engines, was to
begin with current production engines and determine a pathway of technology improvements
over the next 10-15 years that would lead to an appropriate engine configuration for the 2020-
2025 timeframe. With both methods, current trends in engine design and development were
extrapolated to obtain an advanced concept performance for the 2020-2025 timeframe that
should be achievable in production volumes.
The combinations of technologies encompassed in each advanced engine concept provide
benefits to the fueling map, or values of brake-specific fuel consumption (BSFC) over the
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operating speed and load ranges of each engine. For these future engines, the BSFC is
improved by up to 10%. Many of the engine concepts have low BSFC values over large zones
of the engine operating map, with the best BSFC point often at part-load conditions when at
lower speeds.
4.2.1 Stoichiometric Dl Turbo
The basic advanced engine configuration is the Stoichiometric Dl Turbo SI engine. This
advanced engine assumes continued use of a Stoichiometric air-fuel ratio for simplified
aftertreatment using a three-way catalyst. The engine modeled has a peak brake mean effective
pressure (BMEP) of 25-30 bar, which supports significant downsizing compared to current 2010
engines. This high BMEP level is reached through a combination of engine technologies,
including advanced valve actuation, such as CPS; spray-guided Dl; and advanced boost
systems, such as series-sequential turbochargers (see Sections 4.1.1, 4.1.2, and 4.1.3,
respectively).
Current research engines of this configuration have been developed by several groups. One
example is the Sabre engine described by Coltman, et al. (2008) and by Turner, et al. (2009).
MAHLE have also developed a Stoichiometric Dl Turbo SI engine, described by Lumsden, et al.
(2009).
The future engine configuration was assumed to use a cooled exhaust manifold to keep the
turbine inlet temperatures below 950ฐC over the full operating range of the engine to mitigate
the need for upgraded materials in the exhaust manifold and turbine to accommodate higher
exhaust gas temperatures. This design change allows the engine to operate with a
Stoichiometric air-fuel ratio over the complete operating map, even at high-speed, high-load
operating conditions, which significantly improves the fuel consumption in this part of the
operating map.
4.2.2 Lean-Stoichiometric Switching
-s
The Lean-Stoichiometric Dl Turbo SI engine configuration is similar in all respects to the
Stoichiometric Dl Turbo engine described above in Section 4.2.1, except that it uses a fuel-lean
air-fuel ratio at moderate speeds and loads, such as those seen on the FTP75 cycle.
Elsewhere, such as on the US06 cycle, the engine switches to Stoichiometric operation to avoid
exceeding the lean aftertreatment temperature limits. This mixed-mode operation allows the
engine to take advantage of the efficiency benefits of lean operation while mitigating the
technical challenges associated with lean-burn emissions control.
Fuel lean operation improves fuel consumption by increasing the relative charge volume per unit
of fuel burned. Nevertheless, lean operation leads to significant increases in engine-out nitrogen
oxides (NOX) compared to Stoichiometric operation, and therefore requires additional emissions
control systems to remove NOX from net oxidizing exhaust gas, such as a lean NOX trap (LNT)
or a urea-based selective catalytic reduction (SCR) system. The program team raised concerns
about the effectiveness of these NOX removal systems at the high temperatures and exhaust
gas flow rates, or space velocities, easily reached by SI engines at high engine speed or load,
and also about catalyst durability under hot and oxidizing conditions over the vehicle life. These
concerns suggest that meeting criteria pollutant levels over a drive cycle such as the US06
could be challenging to the expected end of life, but advances would be made over the
intervening years to make such systems production feasible.
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Therefore, the engine switches to stoichiometric operation when the exhaust temperature
crosses a threshold above which the NOX removal system catalysts would suffer accelerated
degradation. At high load conditions, the exhaust emissions are treated using typical three-way
catalysts. The engine therefore performs exactly like the Stoichiometric Dl Turbo engine at
higher load, but has improved BSFC at lower load because it switches to lean operation. A
modest fuel consumption penalty is applied over each drive cycle to account for the use of fuel
or other reducing agent to remove NOX during lean operation.
4.2.3 EGR Dl Turbo
The EGR Dl Turbo engine is also similar to the Stoichiometric Dl Turbo Engine described in
Section 4.2.1, except that it uses cooled external exhaust gas recirculation (EGR) to manage in-
cylinder combustion and exhaust temperatures. The recirculated exhaust gas dilutes the air and
fuel charge in the cylinder, thereby moderating the temperature during combustion and allowing
operation without enrichment over the complete operating map. Additionally, the EGR reduces
the need for throttling at low-load operation, reducing engine pumping losses.
Dual high-pressure and low-pressure EGR loops were assumed for this engine configuration,
which will require additional components such as EGR valves and a heat exchanger (EGR
cooler) to manage the EGR flow and temperature. EGR allows a modest overall improvement in
fuel consumption across the complete operating map compared to the Stoichiometric Dl Turbo
engine.
4.2.4 Atkinson Cycle
The Atkinson cycle is characterized by leaving the intake valves open during the start of the
compression stroke, which lowers the effective compression ratio of the engine back to that of
the normal SI engine, but allows for a larger effective expansion ratio. This change in engine
operation improves fuel consumption, but penalizes torque availability at lower engine speeds.
For this reason, Atkinson cycle engines are typically used only in hybrid vehicle applications,
where the electric machine can be used to provide extra torque during launch or other hard
acceleration events.
Separate Atkinson cycle engine fueling maps were developed for the 2020-2025 timeframe with
both CPS and DVA valvetrains. These engines are only used with the P2 parallel and Input
Powersplit hybrid powertrains described in Section 4.3. The torque curve and fueling map thus
generated also reflect so-called downspeeding, or a lower overall operating speed range, which
yields further fuel consumption benefits by reducing frictional losses in the engine.
4.2.5 Advanced Diesel
The advanced diesel engines for the 2020-2025 timeframe were developed by starting with
existing production engines and identifying technology advances that would lead to further
improvements in fuel consumption. These technologies include many of the ones discussed in
Section 4.1, as applied to diesel engines.
This approach led to different maps being developed for each of the vehicle classes that had
diesel engines available: the Small Car, Full Size Car, Large MPV, LOT, and LHDT. For
example, the LHDT engine torque curve and fueling maps were generated by starting with a
6.6 L diesel engine typical for this class and applying the benefits of improvements in pumping
losses or friction to the fueling map. Engine displacements for the advanced diesels were
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chosen based on the current torque and power levels available from these engines, the
expected future requirements, and the effects of applying advanced technologies to support
further downsizing, for example. Current diesel engines for LDVs already use advanced
variable-geometry boost systems and high-pressure common-rail direct injection for better
torque response and specific power. Improvements in these areas are therefore expected to be
incremental, by contrast with the more extensive changes to SI engine architectures described
above. For example, the peak BMEP of the advanced diesels is in the 17-23 bar range, which
is noticeably lower than that expected for the advanced SI engines. This difference is, however,
consistent with Ricardo's expectation of the pace and direction of technology development for
diesel engines that comply with the expected emissions requirements defined in the study's
ground rules defined in Section 3.2.
4.3 Hybrid Technologies
The selection of hybrid technology for a vehicle is complex, with an engineering trade-off
between fuel consumption benefit and system complexity and cost. As hybrid vehicle market
share continues to grow, consumers will have a range of choices.
A wide range of hybrid configurations were considered in the initial part of the program, with the
program studying three main approaches: micro hybrid (stop-start), P2 parallel, and Input
Powersplit. For this study, it was assumed that the hybrid powertrain configurations will be
studied in all but the LHDT vehicle class.
4.3.1 Micro Hybrid: Stop-Start
The most basic hybridization method shuts off the engine during idle periods, and typically uses
an enhanced starter motor and limited use of driver comfort features during engine off, such as
the radio and some heat but not air conditioning. This approach reduces fuel use over city drive
cycles by minimizing idling, but provides no benefit for highway driving or when air conditioning
is requested.
The stop-start, micro hybrid approach is the lowest-cost hybrid system, and can be implemented
relatively quickly on most vehicles on the market today. Stop-start systems are already in
production and the technology is maturing. Further development will lead to increased user
acceptance, for example, through transparent integration with low impact on vehicle
performance or noise, vibration, and harshness (NVH).
The program team has assumed that by the 2020-2025 timeframe, all vehicles with an
otherwise conventional powertrain will have stop-start functionality implemented. For the vehicle
models in this study, the starter motor does not provide motive power, but is capable of
recovering enough energy to offset accessory loads.
4.3.2 P2 Parallel Hybrid
The P2 Parallel Hybrid powertrain places an electric machine on the transmission input,
downstream of the engine clutch. This system allows stop-start, electrical launch, launch assist,
and regenerative braking functionality. The clutch also allows the engine to be decoupled from
the rear of the driveline, allowing pure electric propulsion, or electric vehicle (EV) mode
operation. This wide application of electrical power in a variety of vehicle operating conditions
facilitates downsizing the engine from that in the comparable conventional vehicle.
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This hybrid powertrain is expected to significantly reduce GHG emissions, especially during city
driving. Highway driving fuel consumption is expected to improve because the electric machine
in the P2 hybrid allows for a smaller, more efficient internal combustion engine to be used. This
smaller engine, however, may limit vehicle performance in situations requiring continuous
engine power, such as a sustained hill climb.
P2 Parallel hybrids are in limited production currently, including such vehicles as the Hyundai
Sonata, the Porsche Cayenne, and the Volkswagen Touareg. Prototypes have also been built
by various companies using existing off-the-shelf components.
A P2 Parallel Hybrid system can be used with an automatic transmission, automated manual
transmission (AMT), continuously variable transmission (CVT), or dual clutch transmission
(DCT). Hellenbroich and Rosenburg (2009) describe a P2 variant with AMT, for example. For
this program, the P2 Parallel Hybrid powertrain was modeled using the DCT, which has fixed
gear ratios and no torque converter.
4.3.3 Input Powersplit
The simplest Powersplit hybrid configuration replaces the vehicle's transmission with a single
planetary gearset and two electrical machines connected to the planetary gearset. The
planetary gearset splits engine power between the mechanical path and the electrical path to
achieve a continuously variable transmission. In some Input Powersplit configurations, a second
planetary gearset is used to speed up one of the electrical machines; however, the CVT
functionality is still retained. The Toyota Prius and the Ford Hybrid Escape are two examples of
Input Powersplit hybrid vehicles currently sold in the United States.
With the appropriate electric accessories, the Input Powersplit system allows for EV mode
operation, as well as stop-start operation, electric launch, launch assist, and regenerative
braking. In addition, the system allows for engine downsizing to help reduce fuel consumption,
even though the smaller engine may limit vehicle performance in situations requiring continuous
engine power, such as a sustained hill climb. The Powersplit system provides significant
improvements in fuel consumption in city driving. During highway cycles, the benefits of
regenerative braking and engine start-stop are reduced, however, the CVT feature of the engine
helps during the highway cycle as the engine is kept at an efficient operating point.
4.4 Transmission Technologies
The U.S. vehicle market is currently dominated by automatic transmissions, with a development
emphasis on increasing the launch-assist device efficiency and on increasing the number of
gear ratios to allow the engine to operate more frequently in regions of high efficiency.
Nevertheless, dual clutch transmissions (DCT) are expected to be adopted over the next 10 to
15 years because of their potential to further improve fuel economy and maintain drivability.
CVTs tend to have higher friction than DCTs and provide a different driving experience than
stepped transmissions. CVTs were not included in the scope of this study, even though they are
a current production technology.
The development of DCT technology is expected to be implemented in the U.S. based on
experience with European and Japanese applications. Some vehicles with DCTs are entering
volume production, such as the Ford Fiesta, Ford Focus, and VW Passat. Automatic
transmissions also continue to be developed and refined, with new technologies being
implemented in luxury vehicles and cascading down to other vehicle classes. Given that 94% of
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current U.S. transmissions are automatics, efficiency improvements that mitigate GHG
emissions are expected to come from the following:
Increased gear count from 4-6 currently to 7 or 8 by 2020-2025
Improved kinematic design
Component efficiency improvement or alternative technologies
Launch devices
Dry sump technology
The various base transmission technologies are described, followed by launch device options,
and, finally, other technologies expected to improve transmission efficiency. The effects of these
various technologies on transmission efficiency were incorporated into the models.
4.4.1 Automatic Transmission
The automatic transmission is hydraulically operated, and uses a fluid coupling or torque
converter and a set of gearsets to provide a range of gear ratios. Viscous losses in the torque
converter decrease the efficiency of the automatic transmission. For the study timeframe, it was
assumed that eight-speed automatic transmissions will be in common use, as this supports
more efficient operation. The Small Car is an exception, and was assumed to only have enough
package space to support a six-speed transmission. For the 2020-2025 timeframe, losses in
advanced automatic transmissions are expected to be about 20-33% lower than in current
automatic transmissions from the specific technologies described below. Additional benefits will
be realized by having more gear ratios available to help maintain the engine near its best
operating condition.
4.4.2 Dual Clutch Transmission (DCT)
The DCT has two separate gearsets operating in tandem, one with even gears and the other
with odd. As the gear changes, one clutch engages as the other disengages, thereby reducing
torque interrupt and improving shift quality, making it more like an automatic transmission. The
DCT, however, does not require a torque converter which improves its efficiency compared to
an automatic transmission, and may use either wet or dry type launch clutches. For the 2020-
2025 timeframe, energy losses in both wet clutch and dry clutch DCTs are expected to be 40-
50% lower than in current automatic transmissions. Additional benefits will be realized by having
more gear ratios available to help keep the engine near its best operating condition.
4.4.3 Launch Device: Wet Clutch
A wet clutch provides torque transmission during operation by means of friction action between
surfaces wetted by a lubricant. The lubricant is required for cooling during gear shifts when the
clutch is slipping in larger LDV classes. As a secondary lubrication system is needed for the
actuation requirements, wet clutch systems are expected to be heavier, cost more, and be less
efficient than dry clutch systems.
By the 2020-2025 timeframe, wet clutch DCTs are expected to develop into so-called damp
clutch DCTs, since it approaches the efficiency of a dry clutch with the longevity and higher
torque capacity of a wet clutch. In damp clutch DCTs, a limited spray is applied to cool the
clutch materials. A damp clutch requires a lubrication system but is more efficient due to
improved control, leading to reduced windage and churning losses.
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4.4.4 Launch Device: Dry Clutch Advancements
The standard dry clutch requires advanced materials to dissipate heat and prevent slipping. The
thermal load resulting from engagement prevents dry clutches from being used in high torque
and heavy duty cycle applications, even though they are more efficient since they significantly
reduce parasitic shear fluid losses and do not require an additional lubrication system. The GHG
emissions benefit of a dry clutch over a wet clutch should be realized at launch and during
transient driving, thus primarily for city driving. Advancements in materials or electric assist
could enable this technology to be used in larger LDVs and more severe duty cycles by the
study timeframe, but is generally assumed to be prevalent in the smaller vehicle classes.
4.4.5 Launch Device: Multi-Damper Torque Converter
Dampers added to the torque converter enable a lower lockup speed, therefore decreasing the
more fuel-intensive period of hydrodynamic power transfer. Multi-damper systems provide
earlier torque converter clutch engagement; however, drivability and limited ratio coverage have
limited the deployment of this technology to date. The technology must be integrated during
transmission design. The GHG emissions benefit should come from reduced slippage and
smoother shifting.
4.4.6 Shifting Clutch Technology
Shift clutch technology improves the thermal capacity of the shifting clutch to reduce plate count
and lower clutch losses during shifting. Reducing the number of plates for the shifting process
and reducing the hydraulic cooling requirements will increase the overall transmission efficiency
for similar drivability characteristics. Technology deployment has been limited by industry
prioritization of drivability over shift efficiency, especially since shift events are a very small
portion of typical driving. The technology will be best suited to smaller vehicle segments
because of reduced drivability expectationsthis technology may not be suitable for higher
torque applications.
4.
mproved Kinematic Design
Improved kinematic design uses analysis to improve the design for efficiency by selecting the
kinematic relationships that optimize the part operational speeds and torques. Large
improvements in efficiency have been noted for clean sheet designs for six-speed and eight-
speed transmissions. This approach will provide a GHG emissions benefit across all vehicle
classes and operating conditions.
4.4.8 Dry Sump
A dry sump lubrication system provides benefits by keeping the rotating members out of oil,
which reduces losses due to windage and churning. This approach will provide a GHG
emissions benefit across all vehicle classes, with the best benefits at higher speeds.
4.4.9 Efficient Components
A continuous improvement in seals, bearings and clutches all aimed at reducing drag in the
system should provide GHG emissions benefits without compromising transmission
performance.
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4.4.10 Super Finishing
This technology approach chemically treats internal gearbox parts for improved surface finish.
The improved surface finish reduces drag which increases efficiency.
4.4.11 Lubrication
New developments in base oils and additive packages will reduce oil viscosity while maintaining
temperature requirements, thereby improving transmission efficiency.
4.5 Vehicle Technologies
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.
Technologies considered include mass reduction through use of advanced materials with a
higher strength to mass ratio and through consolidation and optimization of components and
systems. Aerodynamic drag is expected to see improvements through adoption of both passive
and active aerodynamic features on vehicles in the 2020-2025 timeframe. Continued
improvement in tire design is expected to reduce rolling resistance and thereby provide a benefit
to fuel consumption.
In addition, vehicle accessory systems such as the cooling pumps and power steering systems
are expected to become electrified by the 2020-2025 timeframe. These electrified accessories
should reduce the power required to keep them active, which will also improve fuel
consumption, and are described in greater detail below.
4.5.1 Intelligent Cooling Systems
Intelligent cooling systems use an electric coolant pump to circulate engine coolant, removing
the power required for this pump from the FEAD. Removing the coolant pump from the FEAD
also enables independent pump speed control. Rather than running at a fixed multiple of the
engine speed, the coolant pump can spin at the appropriate speed for the current cooling
requirements. Standard cooling systems are sized to provide cooling at maximum load and
ambient conditions, but most vehicles only rarely operate under these extreme conditions.
Intelligent cooling also enables quicker warm-up of the engine by controlling coolant flow. This
reduces engine friction by increasing engine temperature during the warm up process.
Ricardo estimates this technology will lower fuel consumption over the FTP cycle. BMW is
implementing this technology on their twin-turbo 3-L inline-6 cylinder engine, introduced in 2007
in their 335i model. This technology is projected to be readily available by the 2020-2025
timeframe.
4.5.2 Electric Power Assisted Steering
Electric Power Assisted Steering (EPAS) uses either rack or column-drive electric motors to
assist driver effort instead of a hydraulic power assist system. EPAS replaces the engine-driven
hydraulic pump, hydraulic hoses, fluid reservoir, fluid, and hydraulic rack. The efficiency of this
system is a result of reduced FEAD losses and improved energy management that comes from
decoupling the load from the engine. This technology is currently available for small and
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medium sized passenger vehicles, and it is likely that this will be commercially available for
LDVs up to the LOT class by the 2020-2025 timeframe. This technology is required for vehicles
with any electrical launch or EV mobility, so that the vehicle can be steered during EV mode.
5. TECHNOLOGY BUNDLES AND SIMULATION MATRICES
The program team and external stakeholders bundled the technologies described in Section 4,
"Technology Review and Selection," into a set of technology packages to be evaluated in the
seven LDV classes described in Section 2.2, "Ground Rules for Study". These LDV classes are
Small Car, Standard Car, Small MPV, Full Size Car, Large MPV, LOT, and LHDT.
5.1 Technology Options Considered
Definitions of the hybrid powertrain, engine, and transmission technology options are presented
in Tables 5.1-5.4. The engine technologies are defined in Table 5.1; hybrids, in Table 5.2; and
transmissions, in Table 5.3. Many of the engines in Table 5.1 use some measure of internal
EGR, but for this table "Yes" means significant EGR flow through an external EGR system. All
of the advanced transmissions in Table 5.3 include the technologies described in Section 4.4,
including dry sump, improved component efficiency, improved kinematic design, super finish,
and advanced driveline lubricants.
Table 5.1: Engine technology package definition.
Engine
2010 Baseline
Stolen D I Turbo
Lean-Stoich Dl Turbo
EGR Dl Turbo
Atkinson
Diesel
Air
System
NA
Boost
Boost
Boost
NA
Boost
Fuel
Injection
PFI
Dl
Dl
Dl
Dl
Dl
EGR
No
No
No
Yes
No
Yes
Valvetrain
CPS DVA
No
Yes
Yes
No
Yes
Yes
No
No
No
No
Yes
No
Table 5.2: Hybrid technology package definition.
Function
Engine idle-off
Launch assist
Regeneration
EV mode
CVT (Electronic)
Power steering
Engine coolant pump
Air conditioning
Brake
Powertrain Configuration
2010 Baseline Stop-Start P2 Parallel Powersplit
No Yes Yes Yes
No No Yes Yes
No No Yes Yes
No No Yes Yes
No No No Yes
Belt Electrical Electrical Electrical
Belt Belt Electrical Electrical
Belt Belt Electrical Electrical
Standard Standard Blended Blended
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Table 5.3: Transmission technology package definition.
Transmission
Baseline Automatic
Advanced Automatic
Dry clutch DCT
Wet clutch DCT
Launch Device
Torque Converter
Multidamper Control
None
None
Clutch
Hydraulic
Hydraulic
Advanced Dry
Advanced Damp
5.2 Vehicle configurations and technology combinations
Vehicles were assessed using three basic powertrain configurations: conventional stop-start, P2
hybrid, and Input Powersplit hybrid. Each vehicle class considered in the study was modeled
with a set of technology options, as shown in Tables 5.4 and 5.5. Each of the 2020 engines
marked for a given vehicle class in Table 5.4 was paired with each of the advanced
transmissions marked for the same vehicle class.
Table 5.4: Baseline and Conventional Stop-Start vehicle simulation matrix.
Vehicle Class
Small Car
Standard Car
Small MPV
Full Size Car
Large MPV
LOT
LHDT
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
Table 5.5: P2 and Input Powersplit hybrid simulation matrix.
Vehicle Class
Small Car
Standard Car
Small MPV
Full Size Car
Large MPV
LOT
LHDT
Hybrid Architecture
i
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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
6. VEHICLE MODEL
Vehicle models were developed to explore the complete design space defined by the
technologies, vehicle classes, and powertrain architectures included for the 2020-2025
timeframe. The modeling process started by developing baseline models to compare against
data for current (2010) vehicles. A detailed comparison between baseline model results and
vehicle test data were used to validate the models.
6.1 Baseline Conventional Vehicle Models
For each of the seven LDV classes considered in this project, vehicle models were developed
for a 2010 baseline case. Each LDV class was assigned a representative vehicle for the
purposes of establishing a baseline against known vehicle data.
A complete, physics-based vehicle and powertrain system model was developed and
implemented in MSC.EasyS. MSC.EasyS is a commercially available software package
widely used in industry for vehicle system analysis, which models the physics in the vehicle
powertrain during a drive cycle. Torque reactions are simulated from the engine through the
transmission and driveline to the wheels. The model reacts to simulated driver inputs to the
accelerator or brake pedals, thus enabling the actual vehicle acceleration to be determined
based on a realistic control strategy. The model is divided into a number of subsystem models.
Within each subsystem the model determines key component outputs such as torque, speeds,
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and heat rejection, and from these outputs, appropriate subsystem efficiencies can
calculated or reviewed as part of a quality audit.
be
The seven vehicle classes considered in this study are shown in Table 6.1, along with the
baseline vehicles for each class. Each of the baseline exemplar vehicle models had vehicle-
specific vehicle, engine, and transmission model parameters. The models were exercised over
the FTP75 and HWFET fuel economy drive cycles, and the results compared with the EPA
Vehicle Certification Database (Test Car List) fuel economy data for each of the baseline
exemplar vehicles.
Table 6.1: Vehicle classes and baseline exemplar vehicles.
Vehicle Class
Baseline Exemplar
Small car
Standard car
Small MPV
Full sized car
Large MPV
LOT
LHDT
Toyota Yaris
Toyota Camry
Saturn Vue
Chrysler 300
Dodge Grand Caravan
Ford F150
Chevy Silverado 3500HD
6.2 Baseline Hybrid Vehicle Models
For each hybrid technology, Ricardo developed a baseline model to calibrate the hybrid control
strategy and vehicle, engine, and driveline parameters. As with the conventional vehicles
described in Section 6.1, a full physical model of each baseline hybrid exemplar vehicle was
developed and implemented in MSC.EasyS. The hybrid control algorithms are also
implemented in the respective MSC.EasyS models.
The vehicles were modeled using published information from various sources and Ricardo
proprietary data. Each of the baseline exemplar hybrid vehicle models had vehicle-specific
vehicle, engine, and transmission model parameters. The exemplar hybrid vehicles are listed in
Table 6.2, along with the exemplar used to confirm the DCT powertrain.
Table 6.2: Advanced powertrain configurations and baseline exemplar vehicles.
Powertrain Configuration Exemplars
DCT (conventional)
P2 Hybrid
Input Powersplit
Audi A3 / VW Passat
Hyundai Sonata Hybrid
Ford Escape Hybrid
6.3 Engine Models
The engines considered in the design space are defined by their torque curve, fueling map, and
other input parameters. For the 2010 baseline vehicles, the engine fueling maps and related
parameters were developed for each specific baseline exemplar vehicle. For the engines used
in the 2020-2025 vehicles, reference engine models were developed and scaled to each of the
LDV classes.
As described in Section 4.2, the program used two methods to develop the engine models for
the 2020-2025 timeframe. The first was to look at the reported performance of current research
engines, and assume that these current research engines would closely resemble the
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production engines of the 2020-2025 timeframe. With this method, current research engines
would be refined to meet production standards, including manufacturability, cost, and durability.
The second method was to begin with current production engines and determine a pathway of
technology improvements over the next 10-15 years that would lead to an appropriate engine
configuration for the 2020-2025 timeframe.
The fueling maps and other engine model parameters used in the study were based on
published data and Ricardo proprietary data. These initial maps were developed into a map
reflecting the effects on overall engine performance of the combination of the future
technologies considered. Each proposed map was reviewed and approved by EPA and the
Advisory Committee. This process was repeated for each of the engine technologies included in
the simulation matrix, as shown in Tables 5.4 and 5.5 for conventional stop-start and hybrid
powertrain configurations, respectively.
Engine downsizing effects were captured by changing the engine displacement in the given
vehicle. This approach assumes that the downsized engines have the same brake mean
effective pressure (BMEP), which scales the engine's delivered torque by the engine swept
volume, or displacement. The BSFC of the scaled engine map is also 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 of the cylinder. The minimum number of cylinders
in an engine was set to three, and the minimum per-cylinder volume, to 0.225 liters. These
constraints established the minimum engine displacement in the design space to 0.675 liters.
Engine efficiency is therefore assumed to be a function of engine speed and BMEP, with
specific fueling rates (mass per unit time) calculated from the torque. Thus, downsizing the
engine directly scales the delivered torque, and the fueling map is adjusted accordingly. The
engine speed range was held constant over the engine displacement ranges of interest.
Turbo lag was represented in the model by applying a first order transfer function between the
driver power command and the supplied engine power at a given speed. This transfer function
was only used during the performance cycle, which is a hard acceleration from a full stop used
to assess vehicle acceleration performance. The transfer function approximates the torque rise
rate expected in the engines with turbocharger systems during vehicle launch. Adjusting the
time constant in the transfer function allowed the acceleration performance to see the effect of
turbo lag. A time constant of 1.5 seconds was selected to represent the expected delay in
torque rise on the advanced, boosted engines from the spool up of the turbine.
6.3.1 Warm-up Methodology
A consistent warm-up modeling methodology was developed for the study to account for the
benefits of an electrical water pump and of warm restart for the advanced vehicles. To account
for engine warm-up effects, Ricardo used company proprietary data to develop an engine warm-
up profile. This engine warm-up profile is used to increase the fueling requirements during the
cold start portion of the FTP75 drive cycle. This correction factor for increased fueling
requirements is applied to the fuel flow calculated during the warm-up period in the FTP75 drive
cycle.
6.3.2 Accessories Models
Parasitic loads from the alternator were assumed constant over the drive cycles and were
included in the engine model. Alternator efficiency was assumed to be 55% for baseline vehicle
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simulations and 70% for the high efficiency alternator in all of the advanced technology package
simulations to represent future alternator design improvements.
Power-assisted steering (PAS) systemsfull electric or electric hydraulicwere modeled as
being independent of engine speed and were included in the engine model for each baseline
vehicle. The EPAS systems assumed no engine parasitic loads on the EPA drive cycles and
acceleration performance cycles, which require no steering input. All advanced package
simulations included the benefit of EPAS. The LHDT and LOT classes used electric hydraulic
PAS, whereas the five smaller vehicle classes used full electric PAS.
The LOT and LHDT models also include engine parasitic losses due to a belt-driven engine
cooling fan. The other vehicles were assumed to have electric radiator fans, with the load being
drive cycle dependent and added to the vehicle's base electrical load.
Current production cars have begun incorporating advanced alternator control to capture
braking energy through electrical power generation. This is done by running the alternator near
or at full capacity to apply more load on the engine when the driver demands vehicle
deceleration. It is believed that this feature will be widespread in the near future and, hence, the
study captures it by incorporating this function into the Conventional Stop-Start model. For 2020
vehicle configurations, the alternator efficiency was increased to 70% to reflect an improved
efficiency design. The advanced alternator control strategy monitors vehicle brake events and
captures braking energy when available. The control strategy also limits the maximum power
capture to 2800 Watts based on the assumption that the advanced alternator is limited to 200
Amps at 14 Volts charging. By integrating power, energy is accumulated from every brake event
and when there is available "stored" brake energy, the control strategy switches the parasitic
draw from the engine to the battery until the accrued energy is consumed, at which point the
load switches back to the engine. For the five smaller LDV classes, both the fan and base
electrical loads are included in the advanced charging system as electric fans are employed.
The system will only benefit the two truck classes, LOT and LHDT, in terms of base electrical
load as these vehicle classes use mechanical fans.
6.4 Transmission Models
Efficiencies for each gear ratio were calculated based on data from several transmission and
final drive gear tests. Different efficiency curves were mapped for planetary, automatics, and
dual-clutch, with the DCT efficiency modified depending on whether a dry or wet clutch is used.
Hydraulic pumping losses were included in the efficiency calculations. Transmission efficiencies
were calculated to represent the average of the leading edge for today's industry and not one
particular manufacturer's design. Advanced automatic transmission designs are projected to
reduce losses by 20-33% from current automatic transmissions. In addition, the advanced
automatic transmissions use advanced torque converters, described in Section 6.5, below. Wet
clutch DCT efficiencies are also projected to approach current dry clutch DCT efficiencies.
In anticipation of future technology packages, it is expected that some advanced level of
transmission shift optimization will be implemented in year 2020-2025 vehicles. For the 2020-
2025 Conventional Stop-Start architecture, an advanced transmission option was implemented
to determine the most favorable gear for a given driver input and vehicle road load. This
approach takes the place of predefined calibration shift maps based on throttle and vehicle
speed. These strategies presently cause significant implications for drivability and hence affect
consumer acceptability. Nevertheless, it was assumed that by 2020, manufacturers will develop
a means of yielding the fuel economy benefit without adversely affecting acceptability.
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The advanced transmission shift optimization strategy attempts to keep the engine operating
near its most efficient point for a given power demand. In this way, the new shift controller
emulates a traditional CVT by selecting the best gear ratio for fuel economy at a given required
vehicle power level. Gear efficiency of the desired gear is also taken into account. More often
than not, the optimal gear ratio will be between two of the fixed ratios, and the shift optimizer will
decide when to shift up or down based on a tunable shift setting. This will enable the shift
optimizer to make proper shift decisions based on the type of vehicle and the desired
aggressiveness of the shift pattern. To protect against operating conditions out of normal range,
several key parameters were identified, such as maximum engine speed, minimum lugging
speed, and minimum delay between shifts. For automatic transmissions, the torque converter is
also controlled by the shift optimizer, with full lockup only achievable when the transmission is
not in 1st gear. During development of this strategy, it was noted that fuel economy benefits of
up to 5% can be obtained when compared to traditional shift maps. Figure 6.1 shows a
comparison between the shift optimizer strategy and a CVT.
4.5
4
3.5
3
2.5
CD
0.5
200
400
CVT
600
300
1000
1200
1400
Time [s]
DCT (shift optimizer)
Figure 6.1: Comparison of CVT and optimized DCT gear ratios over drive cycle.
6.5 Torque Converter Models
Torque converter characteristics curves for torque ratio and K-factor were generated using
typical industry standards for efficiency. Each vehicle's torque converter characteristics for
torque ratio and K-factor were tailored for the application based on Ricardo experience. Impeller
and turbine rotational inertias are also input to the model and were estimated based upon
Ricardo experience. Vehicle simulations with advanced automatic transmissions include a slight
improvement in torque converter efficiency.
A lockup clutch model was used with all torque converters and was of sufficient capacity to
prevent clutch slip during all simulation conditions. Lockup was allowed in 3rd and 4th gears with
the 4-speed automatics; 3rd, 4th, and 5th gears with the 5-speed automatics; and 4th, 5th, and 6th
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gears with the 6-speed automatics. During light throttle conditions a minimum engine operating
speed of 1400 rpm for 13 engines, 1300 rpm for 14 engines, 1200 rpm for V6 engines, and 1100
rpm for V8 engines with the converter clutch locked was considered in developing the baseline
lock/unlock maps. The advanced automatic transmission applications allow torque converter
lockup in any gear except first gear.
6.6 Final Drive Differential Model
Baseline final drive ratios were taken from published information and driveline efficiencies and
spin losses were estimated based upon Ricardo experience for typical industry differentials. The
spin losses of the 4-wheel-drive LOT and LHDT front axle and transfer case were included in
the model to capture the fuel economy and performance of the 4-wheel-drive powertrain
operating in 2-wheel-drive mode. This approach is similar to the EPA procedure for emissions
and fuel economy certification testing.
6.7 Driver Model
The vehicle model is forward facing and has a model for the driver. The driver model applies the
throttle or brake pedal as needed to meet the required speed defined by the vehicle drive cycle
within the allowed legislative error. This allows the modeling of the actual vehicle response to
meet the target drive cycle.
The driver model contains the drive cycle time/velocity trace, controls for the throttle and brake
functions and maintains vehicle speed to the desired set point. Vehicle simulations for fuel
economy were conducted over the EPA FTP75 (city), HWFET (highway) and US06 drive cycles.
The FTP75 cycle consists of three "bags" for a total of 11.041 miles on the conventional
vehicles and an additional bag 4 on hybrid vehicles for a total of 14.9 miles. A ten minute
engine-off soak is performed between bags 2 and 3 (after 1372 seconds of testing). A bag 1
correction factor is applied to the simulated "hot" fuel economy result of the vehicles to
approximate warm-up conditions of increased friction and sub-optimal combustion. 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.
6.8 Hybrid Models
The hybrid models include all of the conventional vehicle components with the addition (or
replacement) of components for electric motor-generators, high voltage battery, high voltage
battery controller/bus, transmission, regenerative braking and hybrid supervisory controller. Of
these, the critical systems for the model were the electric machines (motor-generators), power
electronics, and high-voltage battery system. For each of these systems, current, state of the art
technologies were adapted to an advanced, 2020-2025 version of the system, 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.
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: FTP,
HWFET, and US06. The methodology used the drive cycle profile to identify the features of a
control strategy that provide the lowest possible fuel consumption over the drive cycle. The
result of this assessment enabled the development of an optimized control system. The
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simulation results using the hybrid controller were compared against the best case scenario
from the methodology to ensure that the hybrid controller in the models is obtaining the most out
of the hybrid powertrain.
A key feature of the hybrid controller is that it used a hybrid load following and load averaging
strategy to help keep the engine on or near its line of best efficiency on the engine operating
map, with some accommodation for the efficiency of the overall powertrain. During low-load
conditions, the engine can be made to work harder and more efficiently and to store the excess
energy in the battery. In other cases, the energy in the battery can be used to provide launch
assist or EV mode driving. All hybrid vehicle simulations were SOC neutral over the drive cycle,
so that there is no net accumulation or net depletion of energy in the battery; thus, fuel
consumption is an accurate measure of the effectiveness of technologies.
7. MODEL VALIDATION RESULTS
Before executing the DoE simulation matrix, the vehicle models described in Section 6 were
validated. Baseline vehicles were modeled, and the simulation results compared against
publicly available data on vehicle performance, including acceleration times and fuel economy.
Details of the model validation process and results are presented below. In addition, nominal
runs were prepared for each major powertrain type to provide a reference point for the input
parameters against which to compare the full design space explored in the DoE simulation
matrix.
7.1 Baseline Conventional Vehicle Models
Vehicle models were developed for a 2010 baseline case for each of the seven LDV classes.
Each LDV class was assigned a representative vehicle for the purposes of establishing a
baseline against known vehicle data. Ricardo leveraged the peer-reviewed baseline models
from its 2008 study with Perrin Quarles Associates (PQA, now part of SRA) for the five LDV
classes from Standard Car through LOT to provide the 2010 baseline case, and to build new
baseline models for the Small Car and LHDT classes. The 2010 baseline vehicles use six-
speed automatic transmissions and the engines with comparable displacement and peak torque
to the exemplar vehicles listed in Table 6.1.
Vehicle performance simulation results are shown in Table 7.1, below, comparing the raw fuel
economy results in the EPA Test Car List (EPA, 2010) against the calculated results. The
results were considered acceptably close. In addition to the fuel economy tests, the launch
performance was also assessed for each of the exemplar vehicles, with particular attention paid
to the 0-60 mph acceleration time, as this is readily available for validation. 0-60 mph
acceleration times for the exemplar models were within a few tenths of a second of published
times for each vehicle.
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Table 7.1: Baseline vehicle fuel economy performance.
Vehicle Class
Small car
Standard car
Small MPV
Full sized car
Large MPV
LOT
LHDT
Baseline Exemplars
Toyota Yaris
Toyota Camry
Saturn Vue
Chrysler 300
Dodge Grand Caravan
Ford F1 50
Chevy Silverado
3500HD (diesel)
EPA Test
FTP75
38
27
24
21
20
16
List Fuel
HWFET
50
42
37
34
32
23
Econ (mpg)
US06
32
26
23
21
21
13
Calculated
FTP75
40
30
24
24
22
16
16
Raw Fuel
HWFET
49
44
34
36
31
26
19
Econ (mpg)
US06
30
29
24
24
21
15
12
7.2 Nominal Runs
Once the models were developed and validated, a series of nominal runs were prepared to
assess the accuracy and robustness of the model. The nominal conditions are the reference
point for the design space explored by the DoE simulation.
For the conventional vehicles, the nominal condition was calculated using the same vehicle
parameter values, such as for mass and aerodynamic drag, as the 2010 baseline vehicles. The
advanced engine size was adjusted to match the baseline 0-60 mph acceleration time. For the
hybrids, the engine size was reduced 20% from the corresponding conventional nominal size,
and the electric machine sized to again match the baseline 0-60 mph acceleration time.
The full table of nominal runs results for the conventional stop/start, P2 hybrid, and Input
Powersplit hybrid vehicle combinations is in Appendix 3. These summary results and the rest of
the simulation output data were used to assess the quality of the simulation results before
executing the DoE simulation matrix, for example, by assessing power flows to and from the
battery over the drive cycle.
8. COMPLEX SYSTEMS MODEL (CSM) VALIDATION
CSM is an objective, scientific approach for evaluating several potential options or
configurations for benefits relative to each other and to a baseline. For this program, the CSM
methodology was used to define the design space for LDVs in the 2020-2025 timeframe, and
then to effectively evaluate LDV performance over this large design space.
8.1 Evaluation of Design Space
The purpose of the DoE simulation matrix is to efficiently explore the potential design space for
LDVs in the 2020-2025 timeframe. The simulation matrix was designed to generate selected
performance results, such as fuel consumption or acceleration times, over selected drive cycles.
The DoE approach allows an efficient exploration of the design space while limiting the number
of runs needed to survey the design space.
For each discrete combination of vehicle class, powertrain architecture, engine, and
transmission in the design space, the continuous input variables were varied over the ranges
shown in Tables 8.1 and 8.2 for the conventional and hybrid powertrains, respectively. In the
analysis, continuous input variables are evaluated using a combination of the design corner
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points in a two-level full factorial design and design points within the space based on a Latin
hypercube sampling methodology. Note that vehicle mass is considered independently of the
combination of discrete technologies; for example, switching from an automatic transmission to
a DCT does not automatically adjust the vehicle mass in the simulation.
Table 8.1: Continuous input parameter sweep ranges with conventional powertrain.
Parameter
Engine Displacement
Final Drive Ratio
Rolling Resistance
Aerodynamic Drag
Mass
DoE Range (%)
50 125
75 125
70 100
70 100
60 120
Table 8.2: Continuous input variable sweep ranges for P2 and Powersplit hybrid
powertrains.
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
Latin hypercube sampling is a statistical method originally developed by McKay et a/. (1979),
used to generate a set of parameter values over a multidimensional parameter space. 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.
The vehicle simulations were run in batches and the results were collected and processed.
Vehicle fuel economy and performance metrics were recorded as well as diagnostic variables
such as the total number of gear shifts and the distance traveled during the drive cycle. The
data were reviewed using a data mining tool and outliers were analyzed, and, as necessary,
debugged and re-run. This approach allowed issues to be detected and diagnosed very quickly
within a large amount of data. Once the data were reviewed and approved, response surface
models were generated.
8.2 Response Surface Modeling
RSM were generated in the form of neural networks. The goal was to achieve low residuals
while not over-fitting the data. Initially, 66% of the data were used for fitting the model while the
remainder was used to validate the response surface model's prediction performance. Once a
good fit was found, all the data was used to populate the RSM. Each neural network fit contains
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all of the continuous and discrete variables used in the study for a given transmission. One
Neural Network fit per transmission was generated to improve the quality of the fits.
9. RESULTS
The key project results consist of the raw data sets obtained from over 350,000 individual
vehicle simulation cases, the Data Visualization Tool developed to query the response surfaces
based upon the raw data sets, and this report describing these results. These results are
discussed below.
9.1 Basic Results of Simulation
Each of the simulation cases generated data at 10 Hz which allowed evaluation of the
performance of a specific vehicle configuration in the design space over each of the drive
cycles. These results include parameters such as vehicle speed, calculated engine power, and
instantaneous fueling rate. The detailed data from each simulation run were distilled into the
main output factors of interest, such as acceleration time and fuel economy, used in the
parametric fit of the RSM.
For this study, the main output factors include raw fuel economy and GHG emissions over each
of the drive cycles studied and also performance metrics, such as 0-60 mph acceleration times.
The complete list of output factors is listed in Appendix 2.
9.2 Design Space Query
The Design Space Query within the Data Visualization Tool allows the user to assess a specific
vehicle configuration in the design space by selecting a platform, engine, and transmission and
setting the continuous variables within the design space range. The generated performance
results are reported in a table that is exportable to Excel. The user can assess multiple vehicle
configurations and compare them in Excel. The tool table also allows the user to apply
spreadsheet formulas for quick, on-the-side computation. An example of the Design Space
Query is shown in Figure 9.1.
9.3 Exploration of the Design Space
A more comprehensive survey of the design space can be conducted using the Design Space
Analysis in the Data Visualization Tool, which allows the user to assess the performance of
multiple vehicle configurations from a significant portion of the design space simultaneously.
Each design is generated by first selecting a vehicle platform, engine, and transmission, and
then ranges for the continuous input variables. Figure 9.2 shows the screen where the design
space analysis is set up. For each of the continuous variables, values are generated using a
Monte Carlo analysis from a uniform distribution over the range selected. These data are stored,
and may be exported or plotted.
Once generated, the design points are stored and may be plotted to visualize the tradeoff
analysis of the design space. By carefully building a design and varying the parameters, the
user can gain an understanding of the effect of each technology and the interactions between
technologies. Figures 9.3-9.5 show examples of plots that compare two design space analyses.
In these cases, the red points are for a Full Size Car with advanced diesel engine and dry-clutch
DCT, whereas the blue points are for a Full Size Car with stoichiometric Dl turbo engine and
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automatic transmission. The black point is the 2010 baseline value. For these examples, the
engine displacement was varied from 50% to 125% of nominal, or 0.71 to 1.8 L displacement for
the stoichiometric Dl turbo engine and 1.4 to 3.6 L for the diesel, and the vehicle mass, from
70% to 100% of nominal, or 2800 to 4000 kg.
The example in Figure 9.6 compares various configurations of the Standard Car, all with the
EGR Dl Turbo engine but with different powertrains. The two Conventional Stop-Start cases
have the advanced eight-speed automatic and dry-clutch DCT, shown in blue and gray,
respectively. The Powersplit hybrid is shown in green, and the P2 Hybrid, in red. Again, the
black point is the 2010 baseline value.
;tem Toe
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File Help
DATA QUERY
PLOT EFFICENT FRONTIER
VEHICLES AND TECHNOLOGIES SELECTION
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Figure 9.1: Design Space Query screen in Data Visualization Tool.
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^v DATA QUERY i ( ANALYSIS SET UP . R.OT EFFICENT FRONTIER
MONTE CARLO POINTS GENERATION SET UP:
Choose Vehicle Class JTruck (Ford F150)
Select Technologies:
Name of Design: :SDU_P2
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Figure 9.2: Design Space Analysis screen in Data Visualization Tool.
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65
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Displacement Scaling ()
Figure 9.3: Full Size Car Design Space Analysis example. Black point is 2010 baseline;
red points are for advanced diesel and dry-clutch DCT; blue points, Stoichiometric Dl
Turbo with advanced automatic transmission.
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450
425
400
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350
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
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Figure 9.6: Standard Car design space analysis example comparing powertrains with
EGR Dl Turbo engine. Blue points are with advanced automatic; gray, dry-clutch DCT;
green, Powersplit; and red, P2 Hybrid. Black point is 2010 baseline.
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ฎ^ DATA QUBIY I ฃ ANALYSIS SET UP I v PLOT I EFFICENT FRONTIER
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0-60 mph Acceleration Time (s)
Figure 9.7: Efficient Frontier screen of Data Visualization Tool with example plot.
9.4 Identification and Use of the Efficient Frontier
Part of assessing the selected regions of the design space is to find configurations that balance
efficiency and performance. The Data Visualization Tool identifies an Efficient Frontier, which is
the bound of the sampled design space that has the most desirable performance. The user
must first define a dataset using the Design Space Query, described in Section 9.2, above, and
select the Efficient Frontier tab in the Data Visualization Tool. An example of the Efficient
Frontier screen is shown in Figure 9.7. The Efficient Frontier is marked out in red. The user can
click on the data points along the frontier to discover the vehicle configurations that lie on the
frontier.
10. RECOMMENDATIONS FOR FURTHER WORK
Ricardo has the following recommendations for further work on this program:
More rigorous analysis and simulation of turbo lag effects in the advanced, boosted
engines through engine performance simulation tied in with the vehicle models.
Expansion of the design space to encompass additional drive cycles, such as the NEDC,
JC08, or the cold ambient FTP, to understand how the technology packages may apply
to other global regions.
Expansion of the design space to mix 2010 baseline engines and transmissions with the
advanced technologies to better understand the relative contributions of engine or
transmission technology to the performance of the advanced vehicles.
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Expansion of the design space to include engines with different technology packages,
such as a version of the Stoichiometric Dl Turbo engine that has a single, fixed cam
profile instead of using the CPS valvetrain.
Expansion of the design space to include additional technologies in one vehicle class to
improve understanding of additional technologies.
Expansion of the design space by sweeping battery capacity.
Conduct detailed study of simulation results to understand main and interaction effects
between technologies.
11. CONCLUSIONS
The following conclusions are supported by this project:
An independent, objective, and robust analytical study of effectiveness of selected LDV
technologies expected to be prevalent in the 2020-2025 timeframe, and their effects on
vehicle performance has been completed.
A comprehensive review process was completed to identify technologies likely to be
available in the 2020-2025 timeframe, and to estimate their future performance given
current trends and expected developments.
The vehicle performance models were based upon the underlying physics of the
technologies and have been validated with good result to available test data. Quality
assurance checks have been made throughout the study to ensure accuracy of the
trends in the results.
The Data Visualization Tool allows EPA and other external stakeholders to examine the
design space developed through the program's Complex Systems Modeling approach
and to assess trade-offs between various vehicle configurations and their performance.
The tool provides the necessary functionality to assess specific vehicle designs or more
comprehensively explore the design space.
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12. REFERENCES
Coltman, D., J.W.G. Turner, R. Curtis, D. Blake, B. Holland, R.J. 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.
Environmental Protection Agency, "Test Car List Data Files", available from
www.epa.gov/oms/tcldata.htm.
Fiat Powertrain Technologies, S.p.A., 2009, "MultiAir: The ultimate air management strategy".
http://www.fptmultiair.com/flash_multiair_eng/home.htm.
Hellenbroich, G., and V. Rosenburg, 2009, "FEV's new parallel hybrid transmission with single
dry clutch and electric torque support." Aachener Koolquium Fahrzeug- und Motorentechnik
200918:1209-1222.
Lumsden, G., D. OudeNijeweme, N. Fraser, and H. Blaxill, 2009, "Development of a
turbocharged direct injection downsizing demonstrator engine". SAE Paper 2009-01-1503.
McKay, M.D.; Beckman, R.J.; Conover, W.J., 1979, "A comparison of three methods for
selecting values of input variables in the analysis of output from a computer code".
Technometrics 21 (2): 239-245.
PQA and Ricardo, 2008, A Study of Potential Effectiveness of Carbon Dioxide Reducing Vehicle
Technologies.
Shaw, J.R., 2009, "Testimony to Joint EPA/NHTSA Hearing on Proposed Rulemaking to
Establish Light Duty Vehicle Greenhouse Gas Emissions Standards and Corporate Average
Fuel Economy Standards". Downloaded from www.autosteel.org and last accessed October 27,
2009.
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., R.J. 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.
USAMP, 2006, "Magnesium Vision 2020: A North American Automotive Strategic Vision for
Magnesium". January 11, 2006
"USLAB materials and processes". Downloaded from www.autosteel.org and last accessed
November 4, 2009.
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APPENDICES
Appendix 1: Abbreviations
AMI
ARE
BMEP
BSFC
CPS
CVT
DCT
Dl
DoE
DVA
EGR
EPA
EPAS
EV
FEAD
FIE
GHG
LHDT
ICCT
KERS
LOT
LDV
LEV
MPV
NOX
NVH
OEM
OTAQ
PAS
PFI
PHEV
PQA
RSM
SCR
SI
SME
SOC
SULEV
V2I
V2V
VA
Automated manual transmissions
California Air Resources Board
Brake mean effective pressure
Brake specific fuel consumption
Cam profile switching
Continuously variable transmission
Dual clutch transmission
Direct injection
Design of experiments
Digital valve actuation
Exhaust gas recirculation
United States Environmental Protection Agency
Electric power assisted steering
Electric vehicle
Front end accessory drive
Fuel injection equipment
Greenhouse gas
Light heavy-duty truck
International Council on Clean Transportation
Kinetic energy recovery system
Light-duty truck
Light-duty vehicle
Low emissions vehicle
Multi-purpose vehicle
Nitrogen oxides
Noise, vibration, and harshness
Original equipment manufacturer
Office of Transportation and Air Quality
Power assisted steering
Port fuel injection
Plug-in hybrid electric vehicle
Perrin Quarles Associates
Response surface model
Selective catalytic reduction
Spark ignited
Subject matter expert
State of charge
Super ultra low emissions vehicle
Vehicle to infrastructure
Vehicle to vehicle
Valve actuation
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Appendix 2: Output Factors for Study
Raw fuel economy in miles per U.S. gallon and GHG emissions in grams of CO2 per mile over
FTP75
HWFET
US06
HWFET and FTP combined
Acceleration performance metrics, including
0-10 mph acceleration time
0-30 mph acceleration time
0-50 mph acceleration time
0-60 mph acceleration time
0-70 mph acceleration time
30-50 mph acceleration time
50-70 mph acceleration time
Top speed at 5% grade
Top speed at 10% grade
Velocity at 1.3 sec
Velocity at 3.0 sec
Distance at 1.3 sec
Distance at 3.0 sec
Maximum grade at 70 mph at GCW
Maximum grade at 60 mph at GCVW (LOT and LHDT only)
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Appendix 3: Nominal Runs Results
The table lists the baseline (2010) vehicles first, followed by results by vehicle class. The P2
Hybrids have an electric machine size listed, and all use the OCT. There were no Conventional
Stop-Start nominal runs that used the OCT. For the Input Powersplit hybrids, only the traction
motor size is listed, as the generator size is a function of the engine and traction motor sizes.
Abbreviations
following:
Baseline
Stoich DIT
Lean DIT
EGR DIT
Adv Diesel
AtkCS
Atk DVA
AT6
ATS
DCT
PS
used exclusively in the following table of Nominal Runs Results include the
The 2010 baseline engine for the given vehicle class
Stoichiometric Dl Turbo engine
Lean-Stoichiometric Dl Turbo engine
EGR Dl Turbo engine
Advanced (2020) diesel
Atkinson cycle engine with CPS
Atkinson cycle engine with DVA
Six-speed automatic transmission (baseline or advanced, as appropriate)
Eight-speed automatic transmission (advanced only)
Dry or wet clutch DCT, per simulation matrix.
Powersplit planetary gearset
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
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Computer Simulation of LDV Technologies for GHG Emission Reduction in the 2020-2025 Timeframe
DISCLAIMER
Ricardo Inc., has taken all reasonable care in compiling the analyses and recommendations
provided in this report. However, the information contained in this report is based on information
and assumptions provided by the client or otherwise available to Ricardo, which, in all the
circumstances, is deemed correct on the date of writing. Ricardo does not assume any liability,
provide any warranty, or make any representation in respect of the accuracy of the information,
assumptions, and, consequently, the analyses and recommendations contained in this report.
The report has been compiled solely for the client's use.
Any results of analysis and calculation are intended to be part of subsequent decision-making
during design, development, and problem-solving stages. Although analysis may reduce the
effort required to validate a product through testing prior to production, such results shall not be
relied on as a validation in its own right.
Analysis and calculations which are intended to predict physical behaviors are inherently
theoretical in nature as they are subject to a range of assumptions and approximations. Physical
behaviors and the measurements of those behaviors may vary for a variety of factors, some
being outside the control of Ricardo or the capability of the predictive methodology used by
Ricardo. Therefore, where any such predictions are subsequently compared with measured
data or physical behavior, it is to be expected that differences will be apparent.
6 April 2011
Ricardo, Inc. Page 47
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