Peer Review of the Draft Report
"Modeling the Cost and Performance of
Lithium-Ion Batteries for Electric-Drive
Vehicles"
Revised Final Report
&EPA
United States
Environmental Protection
Agency
-------
Peer Review of the Draft Report
"Modeling the Cost and Performance of
Lithium-Ion Batteries for Electric-Drive
Vehicles"
Revised Final Report
Assessment and Standards Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
Prepared for EPA by
ICF International
EPA Contract No. EP-C-06-094
Work Assignment No. 4-05
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-12-021
August 2012
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Contents
Executive Summary 1
Introduction 2
The Peer Review Process 2
Peer Reviewer Comments in Response to Charge Questions 4
Summary of Peer Reviewer Comments 5
Technical Comments 5
Comments on Materials and Manufacturing 7
Comments on materials and component costs 7
Comments on manufacturing volumes and production levels 9
Comments on battery end-of-life and recycling 10
Comments about business and fiscal issues 10
Comments on the ANL Spreadsheet Tool 12
Appendix A: Charge to Peer Reviewers A-1
Appendix B. Reviewer Resumes B-1
Appendix C. Peer Reviewer Verbatim Comments Sorted by Charge Question and
Assumption/Topic C-1
Appendix D. Peer Reviewer Comments As Submitted D-1
ill March 31, 2011
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iv March 31, 2011
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Executive Summary
Under a contract with the U.S. Environmental Protection Agency (EPA), ICF International (ICF)
coordinated an external peer review of the Argonne National Laboratory (ANL) Draft Report
"Modeling the Cost and Performance of Lithium-Ion Batteries for Electric-Drive Vehicles." ICF
identified and selected a peer review panel of five subject matter experts and screened them for
conflicts of interest. The peer review charge for this review is presented in Appendix A, and the
peer reviewer resumes are provided in Appendix B. This report summarizes the reviewer
comments according to technical, manufacturing, and tool categories.
Throughout this report, care has been taken to summarize and distill comments without
editorializing them. The full reviewer comments are available in Appendix C, sorted by charge
question. Appendix D provides the reviewer comments in the form they were submitted.
The peer reviewer comments were quite detailed. Some high-level summary points from the
peer review include the following.
Assumptions - Reviewers agreed that most assumptions were reasonable but that they
should be verified, and the report should provide better clarification of options. Some
specific comments on assumptions addressed cell construction and format, thermal
management issues, battery electrode design, calculating component dimensions,
calculation of battery operation, battery design, and other technical assumptions. In
addressing thermal management issues, reviewers commented that the model should
have addressed liquid cooling in the design of the battery pack, either in place of or in
addition to the existing air cooling approach.
Materials and Manufacturing - Reviewers raised concern about the ways in which
material costs were represented in the battery costing model and that they may not take
into account the additional costs of proprietary materials. All reviewers were concerned
about the embedded or default values chosen by the model authors. In addition, there
was concern about the effect of demand on raw material costs as modeled.
Manufacturing Volumes and Production Levels - Reviewers noted some issues with
effect of production level on manufacturing and material costs and the handling of safety
and manufacturability in the model. Most reviewers felt that the general scaling methods
on manufacturing and material costs were not presented clearly in the report.
Business and Fiscal Issues - Reviewers noted concern about how depreciation, return
on investment, warranty costs, and research and development costs were handled in the
model. Reviewers disagreed on if the model over- or under-estimated certain cost
components.
ANL Spreadsheet Tool - All reviewers commented on the adequacy of user-specifiable
parameters and their allowable ranges. In addition, there was concern about how the
model handles baseline plant design and scaling. All reviewers provided suggestions on
how to make the model easier to use and more complete.
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Introduction
As 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 hybrid electric vehicles
(HEVs), plug-in hybrid electric vehicles (PHEVs), and electric vehicles (EVs). The cost of
batteries for these vehicles is a major component of their total incremental cost and is subject to
some uncertainty, particularly with respect to future scales of production and demand.
The U.S. Department of Energy (DOE) has funded a large number of research and scientific
programs to support the electrification of light duty vehicles for more than a decade. This has
included many programs to support advanced lithium-ion batteries for automotive applications.
Among the programs funded by DOE has been the development of a number of cost prediction
models, including a detailed, bottom-up costing model developed by ANL.
EPA has identified the ANL battery costing model as one potential tool for predicting future
battery costs to auto manufacturers. The model allows a user to design a lithium-ion battery
pack matched to user-specified power and energy requirements, and estimates its cost to an
auto manufacturer at a user-specified production level in the year 2020. This model is
documented in the ANL draft report "Modeling the Cost and Performance of Lithium-Ion
Batteries for Electric-Drive Vehicles."
In order to validate and review this work, EPA, in coordination with DOE's Office of Vehicle
Technology, has contracted with ICF to oversee a peer review of the ANL model and
documentation. This report documents the peer review process and comments by the peer
reviewers.
The Peer Review Process
From December 2010 to March 2011, EPA contracted with ICF to coordinate this peer review.
ICF coordinated the peer review in compliance with EPA's Peer Review Handbook (3rd Edition).
EPA requested that the peer reviewers represent subject matter expertise in automobile
packaging, battery chemistry, battery mass production, and/or commodities/raw materials. If
possible, representation from different types of organizations was also requested, i.e.,
academia, auto manufacturers, battery manufacturers, and tier 1 suppliers.
ICF developed a list of qualified candidates from the following sources: (1) ICF experts in this
field with knowledge of relevant professional society membership, industry, academia, and other
organizations, and (2) suggestions from the technical staff from U.S. EPA and the National
Highway Traffic Safety Administration.
ICF identified 44 qualified individuals as candidates to participate in the peer review. ICF 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. ICF attached to the email the
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reviewer charge to ensure each candidate was familiar with the scope of work. ICF also 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
several others did not respond. ICF 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 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 objectives in
mind. As stated in the EPA's Peer Review Handbook, 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.
ICF selected and proposed the initial list of candidate reviewers to EPA. Based on input from
EPA, ICF identified additional potential peer reviewers to better cover the expertise areas
needed. Two of the final candidates declined to participate due to unforeseen circumstances.
Two alternate candidates were recommended by ICF. EPA approved all of the final peer
reviewers recommended by ICF.
The following five individuals agreed to participate in the peer review:
1. Dr. M. Stanley Whittingham, Binghamton University
2. Mr. Kurt Kelty, Tesla Motors
3. Dr. Erin O'Driscoll, Dow Kokam
4. Mr. Joseph Adiletta, A123 Systems
5. Mr. Michael Ely, General Motors
Exhibit 1 shows the representation of the peer reviewers in the required areas of expertise.
Exhibit 1. Chart of Peer Reviewer Expertise Areas
Peer Reviewers
Auto
Packaging
Battery
Chemistry
Battery Mass
Production
Commodities/
Raw Materials
S.
Whittingham,
Binghampton
University
S
K. Kelty,
Tesla Motors
^
^
V
S
E. O'Driscoll,
Dow Kokam
S
S
J. Adiletta,
A123 Systems
S
M. Bly,
General
Motors
/
/
March 31, 2011
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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. ICF executed
subcontract agreements with all but Mr. Ely, who performed the review gratis. Mr. Ely signed a
memorandum of understanding.
ICF provided reviewers with the following materials:
The draft Report by ANL, entitled, "Modeling the Performance and Cost of Lithium-Ion
Batteries for Electric-Drive Vehicles," dated January 15, 2011;
A supporting spreadsheet detailing a bottom-up approach of the costing;
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, as well as example
questions, for preparing their overall review, with particular emphasis on assumptions found
within the model, numerical inputs, values, and specific parameters, costing methodology,
performance methodology, and the cost components of battery pack manufacturing. In addition,
EPA asked each reviewer to provide recommendations on the "overall adequacy of the model
for predicting future battery prices, and on any improvements that might reasonably be adopted
by the authors to improve the model."
A mid-review teleconference was held on February 17, 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 Mr. Kelty, Dr. O'Driscoll, and Dr. Whittingham, as
well as EPA staff Cheryl Caffrey and Joe McDonald, who were familiar with the model and
report.
The charge to peer reviewers is provided in Appendix A. The CVs for the reviewers are
included in Appendix B.
Peer Reviewer Comments in Response to Charge Questions
The charge questions for the peer reviewers are listed Exhibit 2. Reviewers provided
responses to six charge questions that address aspects of the report related to (1) assumptions,
(2) inputs and parameters, (3) cost methodology, (4) performance methodology, (5)
completeness, and (6) recommendations. Example assumptions or specific topics were
provided in the charge to help the reviewers respond to the questions in a detailed manner.
ICF entered the peer reviewer comments into a spreadsheet and sorted them by charge
question and assumption/topic. Appendix C provides a report that was generated from this
spreadsheet. The spreadsheet itself is also being delivered with this report to allow alternate
sorting and filtering of the comments. Appendix D provides the peer review comments in the
form they were received.
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Exhibit 2. Peer Review Charge Questions
1. Assumptions. Please comment on the validity of any assumptions embedded in the
model that could affect projected battery pack price or performance. Please comment
on any assumptions that appear to be unstated and/or implicit.
2. 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. Please comment on any caveats or limitations that these inputs and
parameters entail with respect to use of the results as the basis for estimating the
manufacturing cost or performance of lithium-ion battery packs.
3. Cost Methodology. Please comment on the validity and applicability of the
methodologies used in estimating battery manufacturing costs. Please comment on
any apparent unstated or implicit assumptions and related caveats or limitations.
4. Performance Methodology. Please comment on the validity and applicability of the
methodologies used in calculating the power and energy performance of the designed
battery. Please comment on any apparent unstated or implicit assumptions (e.g.,
regarding ambient temperatures or other factors that may affect battery performance)
and on any related caveats or limitations.
5. Completeness. Please comment on whether the model adequately identifies the cost
components of battery pack manufacturing.
6. Recommendations. Please comment on the overall adequacy of the model for
predicting future battery prices, and on any improvements that might reasonably be
adopted by the authors to improve the model.
Summary of Peer Reviewer Comments
In addition to the verbatim sorted comments provided in Appendix C, a written summary of the
peer reviews is provided here. In this summary, reviewer comments were combined and
summarized by topic, and grouped into three areas: comments on technical issues, comments
on manufacturing, and comments on the modeling tool.
Technical Comments
Reviewers provided several comments on cell construction and format. While Dr.
Whittingham agreed with the choice of flat prismatic cells as the best cell format, other
reviewers suggested that cylindrical cells, such as those used today in HEV designs, should
also be considered. Mr. Adiletta noted that the choices for cell construction produce a generally
usable view of the market, but several reviewers noted that the model does not include
optimized designs that individual manufacturers are exploring. Specifically, the reviewers
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identified options for metal-canned prismatic cells and alternative methods for manufacturing
individual electrodes (winding vs. back-and-forth folding). The assumptions for electrode
thickness should be verified, and the report should be clarified to better explain the model's
design choices. In addition, Mr. Kelty recommended that the report document how the choice of
battery form factor would impact costs.
All reviewers expressed concerns about how the model addressed thermal management
issues. Dr. Whittingham noted that thermal management was the most challenging aspect of
large batteries, and he believed that the choice of air-cooling was not practical in the long term.
He recommended that liquid cooling be modeled instead. Although, he noted that current EV
designs such as the Nissan Leaf rely on air cooling. Dr. O'Driscoll agreed and notied that while
2020 battery packs may be able to achieve acceptable performance using air cooling alone, the
model should justify the choice of this approach. Mr. Adiletta recommended including a variety
of cooling strategies, including air and liquid cooling, as well as active and passive designs. Mr.
Ely commented that the thermal management requirements did not appropriately recognize the
trade offs of life and thermal effects and said that much further model refinements would be
needed to improve the model's accuracy.
Reviewers questioned the model's approach to many technical aspects of battery electrode
design. Mr. Kelty noted that the effect of electrode volumetric change is not considered in the
model, and Dr. O'Driscoll recommended that a 10% change over the full state of charge range
would be more reasonable. Dr. Whittingham stated that volumetric changes would not be a
major concern for the electrode materials chosen in the model. However, an exception would
be the use of lithium titanium oxide (LTO) as the anode material. As a zero-expansion material,
volume changes in LTO would not compensate for volume changes in the cathode.
The model's approach to calculating component dimensions was generally supported, with
the exception of certain components and usage. Drs. O'Driscoll and Whittingham agreed that
the battery design model seems sound; however, Dr. Whittingham raised concerns about how
the effective tap density of the materials is incorporated into the model. Mr. Adiletta noted
several problems with the approach for cell thickness and number of layers. The model
produced unrealistic results for certain inputs - for a standard 10mm PHEV unit, the model
calculated a 16um cathode size, which would require an unrealistically large number of 64
layers. As an alternate approach, he recommended targeting a thickness based on the type of
cell desired, and subsequently varying the number of layers to achieve differing mileage and
capacity packs. There was not necessarily a need to constrain the thickness of the cell based
on the cell type. In non-standard designs, the thickness may be chosen once capacity and
footprint targets have been determined. Dr. Whittingham further noted that assumptions about
the thickness of PHEV cells did not match the model used for the Toyota Prius.
Similarly, the model's methodology with respect to calculation of battery operation was found
to be generally reasonable. Dr. Whittingham supported the approach for calculating power,
capacity, voltage and current, while Dr. O'Driscoll supported the theory behind these
calculations. Mr. Adiletta questioned why the power was a user input rather than calculated
from area-specific impedance (ASI), which was painstakingly calculated elsewhere in the model.
March 31, 2011
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Further, the limiting discharge rate (C-rate) will vary depending on the type of application for
which the battery is designed. Dr. O'Driscoll expressed reservations about how a full scale cost
model was built from basic battery theory, without correlation to actual data. Real-world
properties of these materials, such as the storage capacity, often vary from theoretical
modeling. She recommended validating the model with at least one example showing a cell
and/or battery pack.
Dr. Whittingham argued that the model's approach to battery design insufficiently captured the
variety of designs that will reach the market. Today's designs range from the planned Toyota
Prius, with 3 batteries (one power and two energy) and an all-electric range of 8 to 10 miles, to
the GM Volt with a 15 kWh battery, an electric generator and an all-electric drive-train and a
range of around 40 miles. He noted that the documentation comment about increasing levels of
electrification is incorrect; the Volt PHEV is all electric drive, the HEV buses are all electric drive
with around a 11 kWh lithium-ion battery and more than 2 million total miles demonstrating
reliability.
Reviewers provided several additional comments on other technical assumptions. Mr.
Adiletta questioned the assumption that all negative electrodes necessarily will use a water-
based binder system, especially given the range of cell-types being investigated - micro-HEV
through EV. In addition, he noted that a SOOum thick electrode coating was somewhat
aggressive to expect performance out of the design. For example, the oxide-based chemistries
often used ceramic coatings on the separator or anode to compensate for the inferior abuse
tolerance of that chemistry, the cost of which should be included in the cell cost. Mr. Kelty noted
that the key relationship used to design the battery is an estimate of the relationship between
impedance and electrode thickness. He said that these measurements were made for a few
different electrodes and are now applied to all electrodes. He questioned the lack of data that
would show that this is a reasonable assumption. In applying the model to battery design, Dr.
Whittingham asked how easy is it to manipulate and optimize the plate size, assuming that the
model methodology allows for increasing the current collector thickness as the plate size
increases so that the resistive losses do not increase. Further, he noted that on page 63, the
effect of manipulating the active material thickness is described so that the energy stored can
be increased by thickening the electrodes and therefore reducing the area of the current
collectors and separators needed.
Comments on Materials and Manufacturing
Comments on materials and component costs
Reviewers raised concerns about the ways in which material costs were represented in the
battery costing model. Dr. Whittingham expressed concerns regarding materials and
components costs, noting that the assumptions for material costs were poorly explained. He
argued that many of these materials are used in large quantities and extensively in the industry
today, so the report should include today's costs as well as explanations for how and why the
estimated cost differs from these values. As an example, he pointed to the material LiFePO4,
March 31, 2011
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which is not low cost, even though the raw materials are low cost. Dr. Whittingham pointed
specifically to Table 4.1 of the report, noted that there was no explanation (in the table or the
text) for the three numbers under the TIAX 2010 column, and suggested adding a footnote to
explain the different numbers to the reader. Further, he questioned why there was not a
number for LCO in the ANL 2010 column. In his view, this number must be well-known and
would represent a good baseline against which the other numbers and the spreadsheet model
could be evaluated. He pointed out that while the prices for cobalt and nickel metal prices were
given, the formation of the metal can be very expensive, and the price of the metal oxide should
be considered instead.
Dr. Whittingham and Mr. Adiletta further noted that assumptions about material costs do not
take into account the additional costs of proprietary materials. Dr. Whittingham noted that
there is no allowance made for the cost of using proprietary materials, such as licensing costs,
and that this may be important in comparing one material with another. The cost of some of the
key components may not drop dramatically if one material is sufficiently superior and the
manufacturer has patent protection. Proprietary technology should also be included in materials
costs. Dr. Whittingham highlighted recent litigation that has shown that a lower cost method for
production is well patented,1 and those who need to produce and/or sell in the United States are
going to have to pay licensing fees. Mr. Adiletta commented that the cost of licensing
technology has not been included in the model. He stated that no single outfit is going to have
complete "ownership" of the materials and design. This was not been built into the
methodology.
All reviewers provided comments about embedded or default values chosen by the model
authors. Dr. Whittingham found that the values seemed adequate, but in some cases, changing
the inputs had less impact on cost than he expected. He used the example that switching the
battery charge density from the default value of 155 to 50 Ah/kg had less than a 20% effect on
cost. Mr. Adiletta noted that since electrode design specifications are often unique to individual
manufacturers, the values might be adjusted based on other publicly available information and
that materials cost inputs do not necessarily match with going rates in volume production. Dr.
O'Driscoll found the report values in line with her expectations. Mr. Kelty raised concerns about
the lack of validation data, or documentation of validation, in the default values. Mr. Ely noted
that the model underestimated the cost of energy and consumables used in manufacture.
Dr. Whittingham, Mr. Adiletta both commented on the effect of demand on raw materials
costs. Dr. Whittingham stated that he thought the approach was fine as described in the report,
but mentioned that the model should keep away from low availability materials, where the
battery market is a prime user of the material, such as cobalt and nickel. As noted in the report,
iron and manganese prices are fine. He also mentioned that rare earth metals needed in the
electric motors are a bigger cost driver than the battery for electric vehicles. Dr. Whittingham
noted that while this is outside the scope of this report, the user of the model needs to be aware
that other items than the battery may be cost controlling. Mr. Adiletta agreed that the effects of
1 Valence Technology, Inc. v. Phostech Lithium Inc. 2011 FC 174, Gauthier J.
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low-availability materials did not seem to be addressed. The effect is real, quantifiable and quite
different for each battery manufacturer depending on volume and relationship. Especially in
2020 and beyond, some reasonable assumptions must be made based on today's high volume
cost rates. It does not appear that this was taken into account. At the very least a single input
for percent decrease based on volume might be added.
Addressing the overall approach to battery costs, Mr. Ely noted that the cost models do not
seem aggressive enough for the 2020 forecasted total costs.
Comments on manufacturing volumes and production levels
Dr. Whittingham and Mr. Adiletta commented on the effect of production level on
manufacturing and material costs. Dr. Whittingham found that the document's methodology
examples appeared reasonable, noting that the manufacturing cost will decrease with increased
knowledge from larger scales of production. Mr. Adiletta noted that there will be a significant
difference in materials costs based on expected production volume. He stressed that this
should be added to the model, even if in vague terms via percent cost downs based on specific
manufacturing thresholds. He recommended constructing the model to be based on number of
vehicles produced. In addition, coating facilities run at speeds entirely dependent on the
chemistry and cell design, thus drastically altering the amortization of costs to the cell, and this
augmentation might be considered.
All reviewers provided comments about safety and manufacturability. Dr. Whittingham noted
that an issue with all batteries is protection in the case of crashes, and the report did not really
address that issue. He suggested that if the battery insulation was intended to serve as a crash
protector, these costs need to be included. Mr. Adiletta agreed with the addition of certain
components to ensure safety. Dr. O'Driscoll noted that safe handling of inorganic metal powder
is not addressed well, arguing that EPA guidelines for handling materials with nickel and cobalt
are much different than those for iron, and hence, one would expect different cost structure to
handle the materials in the process. Specifically, section 4.3.2 of the report did not address
moving powder through the process and cleaning up safely. She also expressed concern about
how the model includes the handling of large quantities of electrolytes without contamination
and asked what size container is expected and how the material is kept clean and dry at this
scale. Mr. Kelty commented that assumptions about the safety features in the battery pack are
not clearly documented. Finally, Dr. Whittingham noted that, while no cost was assumed for
water, the cost of handling the contaminated waste water was not included. There are several
companies trying to use dry processing to eliminate these costs.
Dr. Whittingham, Mr. Adiletta and Mr. Ely commented on the general scaling methods on
manufacturing and material costs. Dr. Whittingham expressed confusion about the numbers
in Table 4.8 and the corresponding description on pages 46 and 48. He believes that a more
important metric from the user and consumer perspective is the cost per kWh or per mile driven,
not just battery capacity. He recognized that if more power is desired, then it is going to cost
more. But if more energy per cell is desired, then the cost of the cell per kWh goes down.
Whittingham recommended that this section should be rewritten to emphasize what is of interest
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to the end-user. Mr. Adiletta noted that at a certain volume, significant changes to
manufacturing process will be required, which will bring associated reductions in cost. The
model seemed to be based on today's methodologies, but applied to 2020, which may not be
realistic. Additionally, the material cost structure as outlined was not indicative of today's
pricing, which would imply significantly higher costs than what he would expect to see in 2020.
Further, he was critical of the assumption that manufacturing costs would scale independently of
cell design. As an example, while the cost of forming a cell may scale linearly with the number
of cell layers, the depreciation costs of the stacking equipment will not. Mr. Ely noted that the
estimated yield rates are overly conservative. While the model applies a yield rate of 92%, some
suppliers target a 98% yield rate.
Comments on battery end-of-life and recycling
Dr. Whittingham, Mr. Adiletta, Dr. O'Driscoll, and Mr. Ely commented about scrap rates and
associated costs. Dr. Whittingham stated that the percent scrap rate appears reasonable, but
noted that no value is assigned to the scrap. Although by 2020, if the market is indeed there,
there should be a thriving recycling business that would take the scrap away. Mr. Adiletta asked
if scrap rates were inclusive of end of line testing and also noted that the NMP recycling number
seemed high. Mr. Ely noted that the scrap rates did not represent benchmark practices and
suggested that they should be re-evaluated. Dr. O'Driscoll found that the scrap rates looked
reasonable.
Dr. Whittingham noted that the value of recycled batteries were not discussed, even though it is
presumed by other ANL reports that eventually most of the lithium (and presumably any
expensive other elements) would come from recycled batteries. He also noted that the model
does not include any end-of-life scenarios, such as "spent" EV batteries for utility/alternative
energy load leveling/smoothing, which would reduce the effective life-time cost of a battery.
Comments about business and fiscal issues
Dr. Whittingham, Mr. Adiletta, Mr. Kelty, and Mr. Ely commented on how depreciation was
included in the ANL model. Dr. Whittingham found no real justification for how the model
approached depreciation costs. He said it was probably too low at 12.5%, which assumed an
8-year life. For a new and likely changing technology, a shorter depreciation time would be
needed, at least for the first 5 to 10 years. Mr. Adiletta asked if the report accounted for
government subsidies in the acquisition of capital equipment and argued that 8 years on
manufacturing equipment seemed a bit long. Mr. Kelty stated that 5-year depreciation would be
more appropriate. Mr. Ely agreed and notied that an 8-year amortization was slightly higher than
the current norms in the industry.
Dr. Whittingham also stated that the return-on-investment (ROI) appears too low at 5%. He
noted that the model fixes profit at 5% of total investment costs and says this seems too low for
a risky investment. An ROI closer to 10% would be more reasonable. Mr. Adiletta expressed
that it would make more sense to target a before-tax profit and structure the model around tax
margin. Predicting and/or modeling the going corporate tax rate would be difficult. He noted
10 March 31, 2011
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that the profit rate looks a bit lower than expected over the long-term. Dr. Whittingham
questioned why the model includes built-in assumptions for inflation rate, rather than allowing
the user to include a term for inflation. Mr. Ely commented that the model's assumptions about
profit and selling, general, and administrative expenses (SG&A) seemed to be very high
compared to the current market.
Reviewers commented on the model's approach for warranty costs. Dr. Whittingham stated
that for a new product the warranty cost assumptions of 1% failure per year appear too low. He
argued that since no lithium battery has been used in the proposed duty cycle for anywhere
close to 10 years, justification for this assumption should be made. The costs assumed
appeared to be those purely due to replacing the battery, not including other issues such as
liability insurance. Mr. Kelty stated that he would expect warranty assumptions to be somehow
related to performance, such as cycle life or calendar life. He believed an assumption related to
cooling system and life would make more sense but would be challenging to build into this
model at this point. Mr. Adiletta noted usually warranties are expressed as a percentage of
cost, which he assumed is what the authors intended by "added to price," rather than a percent
of the final price. Dr. O'Driscoll stated that without correlation to data, warranty assumptions
appeared reasonable.
Mr. Adiletta provided comments about research and development costs. He stated that
research and development comes in two forms, support for the manufacturing operation and
developing new products. It is not clear which of these the authors intended. He noted that it is
more typical to talk about research and development costs as a percent of revenue rather than
of depreciation.
On many aspects, the reviewers disagreed about the overall cost estimates. While Mr. Kelty
and Dr. O'Driscoll commented that the model underestimated costs of battery production, Mr.
Ely commented that in some ways the model overestimated the costs. Mr. Kelty ran the model
using several scenarios and found that the calculated costs of battery packs were lower than
anticipated, perhaps due to the extremely thick electrodes that the model predicted. He
suggested that the electrode thickness should be a user-defined value, with a value less than
200 microns. However, Mr. Ely suggested the costs were overestimated and argued that most
of the cost models did not seem aggressive enough for 2020 forecasted total costs.
Specifically, he said that the labor costs used in the model were appropriate only within the
United States. Further, Dr. Whittingham noted that the cost of handling contaminated
wastewater was not considered in the calculations. Overall, Mr. Ely concluded that the model
for building costs did not seem realistic, unless the model assumed continuous government
incentives. He further noted that the costs calculated in the model may vary regionally, and the
cost structure lacked detail in burden cost. Specifically, the estimate of the impact of
depreciation on burden cost was 1.5 times too high. Lastly, Mr. Kelty recommended that the
authors summarize in the report how the model accounts for costs in 2020. He suggested that
the model appeared to use cost as a user input. He recommended that cost projections should
focus on the cost of the active material, which is the largest component of battery costs.
11 March 31, 2011
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Comments on the ANL Spreadsheet Tool
All reviewers commented on the adequacy of user-specifiable parameters and their allowable
ranges. Dr. Whittingham found no difference in the battery cost whether the operation hours per
day were 10 hours, 24 hours (or even 48 hours, which should be outside the bounds of the
model) and noted that depreciation should cause some effect. The spreadsheet should be
programmed so that values exceeding 24 hours cannot be used. Mr. Adiletta stated that for
micro-HEV and HEV, it would make sense for the user to specify power required, rather than
the choices currently available: capacity, energy or range. This is especially true if half (two out
of four) of the options are HEV related (micro and full). He also assumed that some of the user
inputs are considered in the model for future use, specifically that the ASI seems to be
calculated but not necessarily applied, as do entries like temperature rise. Dr. O'Driscoll said it
was difficult for her fully assess the model in the time period given. Mr. Kelty noted that more
parameters should be user specifiable and that there are too many limitations currently on what
can be changed. Specifically, he identified five user-defined inputs, including a metric for
acceleration, such as the time it takes to accelerate from 0-60 miles per hour at a specified
temperature.
Dr. Whittingham, Mr. Adiletta, and Mr. Ely made comments about how the model handled
baseline plant design and scaling. Dr. Whittingham said that the general approach seemed
fine, but wondered how the model handleed the scaling of processes such as calendering,
which is modeled with one person per shift. No person is going to work continuously without a
break. He wondered how these breaks are covered when the process is presumed continuous,
and asked whether there would be flexibility for this issue to be built into the cost methodology.
Mr. Adiletta thought that the initial plant design looked reasonable, and suggested that the
model should consider scalability based on volume assumptions. At some point, volumes could
become large enough such that a transition to new manufacturing strategies would make sense
in order to continue down the cost curve. Using this approach, scaling would be done
incrementally based on capacity ramp-ups. To that extent, the model seemed to function
linearly with respect to invested capital, whereas in reality a large amount of capital is invested
for a fixed capacity which may or may not be fully utilized, which would affect the cost. Mr. Ely
noted that the 20-year amortization of capital investment was much lower than actual practice in
the Asia supply base. He commented that the model for building cost did not seem realistic,
unless the model assumes continuous government incentives, which he stated would not be
realistic in this timeframe. Further, the total costs for buildings and land appeared to be too
conservative.
Mr. Adiletta and Mr. Kelty suggested that the model's ease-of-use could be improved,
especially for users who are not well versed in specifics of chemistry. For instance, the model's
inputs and outputs may not be clear to the user. There were sheets that contained foundational
information, but these might not be used by someone performing a top-level analysis. Further,
a user on the outside of industry may not have the detailed information required for the model,
as many of the details will be held privately by individual manufacturers. Mr. Kelty
12 March 31, 2011
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recommended that the model include documentation on adjusting Microsoft Excel's settings for
iterative calculations.
Mr. Adiletta and Mr. Kelty made additional comments about how the model's design allowed
the user to determine battery costs. He stated that since the model will likely be reviewed by
OEMs as well as small startups and suppliers, it would be beneficial to break out the cost
analysis into cell and non-cell components. Because some OEMs will be buying cells and will
likely be interested the full cost analysis, the model's approach of combining all labor, overhead
and SGA into single buckets may not be the most appropriate strategy. Mr. Kelty commented
that the model's outputs could be altered to be more useful, for instance by showing the battery
pack costs over time for each chemistry type. In addition, he noted that outputs such as costs
per kw-hour at the cell and pack level would be helpful.
All reviewers noted specific opportunities to make the model more complete. Dr. O'Driscoll
stated that labor costs seemed low and there was no flexibility in the model to consider
improvements in automation that would further reduce labor costs in the manufacturing process.
Mr. Adiletta stated that manufacturing would require an inspection step with labor and
equipment costs, which were not considered. He further observed the omission of small
manufacturing costs such as the cost of tape in the cell (acknowledged to be small) and found
the overall cost of terminal assemblies to be low. Mr. Kelty noted the omission of the cost of
critical safety features in the battery, but acknowledged that these costs will be small in
comparison to drivers such as the active material. Dr. Whittingham recommended a more
rigorous approach to utility costs, including how utility costs may increase with plant automation
or the climate of the plant's location. He commented that unanticipated breakthroughs can
significantly reduce costs, but acknowledged the impossibility of anticipating these
breakthroughs. With regard to labor costs, Mr. Ely noted that the labor cost assumptions were
appropriate only for the United States.
13 March 31, 2011
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Appendix A: Charge to Peer Reviewers
Peer Reviewer Charge
Charge to Peer Reviewers of "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles"
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 costs of
technologies necessary to bring about such improvements. Some potential technology paths
that manufacturers might pursue to meet future standards may include hybrid electric vehicles
(HEVs), plug-in hybrid electric vehicles (PHEVs), and electric vehicles (EVs). The cost of
batteries for these vehicles is a major component of their cost and is subject to some
uncertainty, particularly with respect to future scales of production and demand.
EPA has identified a battery costing model developed by Argonne National Laboratories
(ANL) as a potential tool for predicting future battery costs to auto manufacturers. The model
designs a lithium-ion battery pack matched to user-specified power and energy requirements,
and estimates its cost to an auto manufacturer at a user-specified production level in the year
2020. This model is documented in the ANL draft report "Modeling the Cost and Performance of
Lithium-Ion Batteries for Electric-Drive Vehicles".
EPA is seeking the reviewers' expert opinion on the methodologies used in this model
and whether they are likely to yield realistic estimates of the cost of lithium-ion battery packs
likely to be produced for vehicles in the year 2020. We ask that each reviewer comment on all
aspects of the ANL model, with particular emphasis on the assumptions inherent to the model,
sources of information employed in the model, methods of calculation and any other key issues
the reviewer may identify. Findings of the peer review may be used toward validation and
improvement of the model by ANL and to inform EPA and NHTSA staff on potential use of the
model for predicting future battery costs. No independent data analysis will be required for this
review.
Reviewers are asked to orient their comments toward the six (6) general areas listed
below. Some possible topics in each area are provided as illustrative examples. Reviewers are
expected to identify additional topics or depart from these examples as necessary to best apply
their particular set of expertise toward review of the model.
(1) Assumptions. Please comment on the validity of any assumptions embedded in the
model that could affect projected battery pack price or performance. Examples might include
assumptions regarding: cell construction and format, and comparability to competing cell
formats; cooling and thermal management requirements; electrode volumetric change; limiting
parameters affecting cell dimensions or performance (for example, allowable A-hr capacity per
cell, maximum electrode thickness, etc); warranty costs and profit; scrap rates; safety and
manufacturability; anticipated industry design trends, and similar factors. Please comment on
any assumptions that appear to be unstated and/or implicit.
A-1
-------
(2) 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: any embedded or default values chosen by the authors (for example,
those that represent default material costs, material percentages, preferred dimensions,
experimentally measured values, etc); and the adequacy of user-specifiable parameters and
their allowable ranges (for example, those that specify performance requirements, or those that
relate to cell chemistries or cell/module/pack configuration possibilities). Please comment on
any caveats or limitations that these inputs and parameters entail with respect to use of the
results as the basis for estimating the manufacturing cost or performance of lithium-ion battery
packs.
(3) Cost methodology. Please comment on the validity and applicability of the
methodologies used in estimating battery manufacturing costs. Examples of such
methodologies might include: general scaling methods, effect of production level on
manufacturing and material costs, method of accounting for warranty costs and profit, effect of
demand on raw material costs, baseline plant design and scaling, etc. Please comment on any
apparent unstated or implicit assumptions and related caveats or limitations.
(4) Performance methodology. Please comment on the validity and applicability of the
methodologies used in calculating the power and energy performance of the designed battery.
Examples of such methodologies might include: how the physical properties and dimensions of
cell components are calculated from the inputs; how power, energy capacity, resistances,
currents, etc. are calculated; etc. Please comment on any apparent unstated or implicit
assumptions (e.g., regarding ambient temperatures or other factors that may affect battery
performance), and on any related caveats or limitations.
(5) Completeness. Please comment on whether the model adequately identifies the cost
components of battery pack manufacturing. Examples of such cost components might include:
physical components of the cells and assembled packs, manufacturing steps, raw materials and
labor, energy inputs and consumables used in manufacture, capital equipment, research and
development costs for battery design development and production implementation, battery
control systems, etc.
(6) Recommendations. Please comment on the overall adequacy of the model for
predicting future battery prices, and on any improvements that might reasonably be adopted by
the authors to improve the model. Please note that the authors intend the model to be open to
the community and transparent in the assumptions made and the methods of calculation.
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 ANL
A-2
-------
makes its report/cost model 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 ICF International
(SBIaine@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.qov).
A-3
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Appendix B. Reviewer Resumes
1. Dr. M. Stanley Whittingham, Binghamton University
2. Mr. Kurt Kelty, Tesla Motors
3. Dr. Erin O'Driscoll, Dow Kokam
4. Mr. Joseph Adiletta, A123 Systems
5. Mr. Michael Ely, General Motors
B-1
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B-2
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M. Stanley Whittingham
(http://materials.binghamton.edu/WHITTINGHAM/whit.html)
1. Education & Training
Oxford University, UK Chemistry B. A., 1960-1964
Oxford University, UK Solid State Chemistry M. A., D. Phil., 1964-1968
Stanford University, CA Materials S&E Research Associate, 1968-1972
2. Employment History
2001-Present Professor of Materials Science, Director Materials Science and Engineering
Program
1997-2001 Co-Chair, Research Advisory Council of SUNY
1994-2000 Vice-Chair, Board of Directors, Research Foundation of SUNY.
1993-1999 Vice-Provost Research at Binghamton
1988-Present Professor of Chemistry, State University of New York at Binghamton.
1988-Present Director of the Institute for Materials Research, State University of New York
at Binghamton.
1984-1988 Director of Physical Sciences and Member of Scientific Staff, Schlumberger-
Doll Research.
1972-1984 Director of Solid State and Catalytic Sciences Laboratory; Manager, Chemical
Engineering Technology Division; and Member of Scientific Staff, Exxon
Research & Engineering Company.
3. Awards and Honors
ACS-NERM Award for "Achievements in the Chemical Sciences", 2010
GreentechMedia top 40 innovators for contributions to advancing green technology, 2010
SUNY Chancellors Award for Excellence in Scholarship and Creative Activities, 2007
Research Foundation of SUNY Research Award, 2007
Fellow, The Electrochemical Society, 2004
Battery Research Award, The Electrochemical Society, 2002
JSPS Fellow, Physics Department, Tokyo University, 1993
Electrochemical Society Young Author Award, 1971
Gas Council Scholar, Oxford University, 1964-1967
4. Contributions to the Public
Leading a Binghamton consortium to bring to the public the excitement of new materials
and chemistry. We were one of 20 winning consortia in the US, who will work with WGBH in
Boston in the winter of 2011 to involve the public at the time of the NOVA broadcasts
(February). BU, BCC, the local schools, Oakdale Mall, Roberson Museum, and the local PBS
station are all participating. Seed funding has been provided.
Presentations to local groups on energy in Oswego and Binghamton
Radio broadcasts in 2010
BBC Radio "From NYC to Copenhagen" - discussion on the discovery of the Li
battery
NPR NYC on "What is a battery?" live broadcast with Q&A (40 mins)
WSKG Radio on "Renewable and Alternative Energy", live with Q&A (60 mins)
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5. Contributions to Scientific Organizations
American Chemical Society
Advisory Board of the Petroleum Research Fund
Past Chair, Solid-State Sub-Division
Past Chair, Binghamton local section
Organizer of several symposia, including superconductivity, and solid state
chemistry of energy (both published as books by ACS)
Organized the local Chemistry Olympiad one year in Binghamton.
The Electrochemical Society
Past Chair, New York Metropolitan Section
Organized numerous symposia at National and International meetings, most recently
in Vienna, Austria 2009
The Materials Research Society
Chair, Student Chapters (until 2010)
Chair, Academic Affairs Committee (from 2010)
Organized numerous symposia in both science and education areas.
American Physical Society
Lifetime member. Lectured on both science and education
International Society for Solid State Ionics
Presently President (until 2009-2011)
Co-organized International meeting in Lake Louise, Canada and co-chair 2011
meeting in Warsaw, Poland.
Gordon Research Conferences
Chaired two meetings in New Hampshire on Solid State Chemistry, and on Solid
State Ionics. Co-chaired Solid State Chemistry conference in Oxford, England.
International Symposium on the Reactivity of Solids
Past President of the International Board
Chaired international meeting in Princeton in 1988.
6. Contributions to Scientific Publications
Solid State Ionics
Principal Editor 1980-1999; Founding Editor 2000-present.
Professional Journal Boards
Have been on the editorial advisory boards of Chemistry of Materials, Materials
Research Bulletin, J. Applied Electrochemistry.
Reviewing for Journals
Very active in reviewing manuscripts for many major journals in chemistry, physics
and materials. Requests exceed 10 per week.
7. Contributions to Government Activities
NSF
Served on a number of committees, that resulted in reports advising the future
direction of Solid State Chemistry
Workshop participant, most recently at MIT on extending the drug discovery
techniques to the Energy Area.
Panel reviewer and proposal reviewer
DOE
Served on a number of committees, most recently on the extended workshop on
future directions for Energy Storage Research (2007). Co-chair of chemical energy
storage group (aka Batteries). Presented results of workshop at the National meetings
of the American Chemical Society and the Materials Research Society
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Served on numerous proposal panels and as reviewer of proposals.
On the External Advisory Boards of two EFRCs, one at Cornell and one at Argonne
National Lab.,
New York State
Served on committees in the formation of NYBEST (New York Battery and Energy
Storage Technology Consortium.
Binghamton's representative on NYBEST
Elected vice-chair for academia on the Board of Directors of NYBEST, 2010.
8. Externally Supported Research
NSF
My research has been continuously supported by NSF since 1989, as a single PI
investigator.
I organized the Solid State Chemistry Summer Program (REU-type activity) for five
years at Binghamton.
I have also received several education grants from NSF, both for bringing
infrastructure, research and teaching to Binghamton.
I was also co-leader of the NSF funded "bringing materials into the chemistry
curriculum" activity based at U. Wisconsin.
DOE
My research has been continuously supported by DOE-EERE since 1993, as a single
PI investigator.
In 2009,1 was part of the winning team of the DOE-BES-EFRC on energy storage,
and am now Associate Director of the activity. (15M$ over 5 years).
NYSERDA
This year NYSERDA initiated research in the battery area, and I received two
awards. One of these involves collaboration with two colleagues in the Chemistry
Department (with all the funds going to them), and the second involves collaboration
with Brookhaven National Laboratory to bring more of their forefront analytical
techniques to the battery areaMy research has been continuously supported by DOE-
EERE since 1993, as a single PI investigator.
Other
I have received funding from other federal agencies, such as DARPA, and from
industry from time to time. We also assist local industry in characterizing their
materials.
9. Student Education
General
I initiated a specialization in Materials Chemistry at both the undergraduate and
graduate levels, including development of new courses and curricula. Also revamped
the Chem 111 introductory course in Chemistry to make it more relevant and
rigorous. Enabled the introduction of computers into the curriculum by lobbying the
administration for two computer PODS in Science 2. Introduced listserves into
chemistry classes, and participated in the early days of distance learning through the
SUNY Learning network. This course had initially around 40 students and recently
peaked at over 400.
Took a lead role with colleagues in Chemistry and Physics to initiate a graduate
program in Materials Science (now Materials Science & Engineering), and steered it
successfully through its first "7-year" external review.
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Graduate
Numerous graduate students have received their PhD's under my guidance initially
in chemistry and now also in Materials. These students are now in teaching positions,
in National Laboratories or in Industry, both in the US and overseas.
Ken Reis (PhD), James Li (PhD), Jindong Guo (PhD), Hatem Maraqah (PhD), Tom Chirayil
(PhD 6/98-Englehard), Gerald Janauer (PhD 1/98), Rongji Chen (PhD 12/98); Curtis Weeks
(MS 12/97 US Air Force); Greg Moore (PhD 5/99), Fan Zhang (PhD 12/99), Sergei Zarembo
(PhD 01/01), Arthur Dobley (PhD 08/01), JohnNgala (PhD 8/03), Shoufeng Yang, (PhD
07/03) Yanning Song (PhD 03/04), Samuel Lutta (PhD 10/04), Miaomiao Ma (PhD, 2006),
Joel Christian (PhD 12/07), Michael Chin (MS 09/04) Chen Chen (PhD 12/07), Fan Quan
(PhD), Jiajun Chen (PhD), Jian Hong (PhD), Shijun Wang (PhD), Jie Xiao (PhD, 2009),
Chunmei Ban (PhD 2009) Chris Jacobs (MA), Megan Roppolo (PhD, 2010); Joel Miller,
Ruigang Zhang, Wenchao Zhou, Zheng Li, Fred Omenya, Hui Zhou, Heng Yang, et al.
Undergraduate
A number of undergraduate students have worked in my group, and most have gone
onto graduate school.
Charlotte Zaremba* (PhD-UC Santa Barbara); David Schoonmakert; Adam Skoczylast;
Paul Schnier*?(PhD-UC Berkeley); Jennifer Monteith*? (now at Columbia University);
Gregory Moore, Tom Chirayil, Stacia Wagner, Jacki Hinz*, Caroline Freitag*, James Reho*
(PhD-Princeton), Billlie Abrams, Lisa Boylan (Corning), Sean Kelly (now at UNC), Mark
Mamac (Honors Thesis), Melissa McCartney (MRS award winner), Kinson Kami (MRS
award winner, and Honors Thesis), Michael Chin*, Wai Chun Lan, Luke Moseley, Christine
Manlulu, Melanie Thornhill, Gene Nolis. [*Participated in NSF-DMR summer program in
Solid State Chemistry; t Chemistry degree with emphasis in Materials.]
10. Publications (a selection)
1. Jiajun Chen and M. Stanley Whittingham, "Hydrothermal Synthesis of Lithium Iron Phosphate",
Electrochem. Commun., 2006, 8: 855-858. (Top 25 most cited articles in the journal - ISE meeting
September 2010)
2. Jiajun Chen, Michael J. Vacchio, Shijun Wang, Natalya Chernova, Peter Y. Zavalij, M. Stanley
Whittingham, "The hydrothermal synthesis and characterization of olivines and related
compounds for electrochemical applications", Solid State Ionics, 2008, 178: 1676-1693. (2nd most
downloaded article in the journal)
M. S. Whittingham, "Materials Challenges Facing Electrical Energy Storage", Mater. Res. Soc.
Bulletin, 2008, 33:411-420
3. M. S. Whittingham: Lithium Batteries and Cathodes, Chemical Rev., 104: 4271-4301 (2004)
4. M. S. Whittingham, "Inorganic nanomaterials for batteries", Dalton Transactions, 2008, 5424-
5431.
5. Joel Christian, Sean P.E. Smith, M. Stanley Whittingham and Hector D. Abruiia, "Tungsten based
electrocatalyst for fuel cell applications", Electrochem. Commun. 2007, 9: 2128-2132.
6. N. A. Chernova, M. Ma, J. Xiao, M. S. Whittingham, J. Breger and C. P. Grey "Layered
LixNiyMnyCoi_2yO2 Cathodes for Lithium-Ion Batteries: Understanding Local Structure via
Magnetic Properties", Chem. Mater., 2007, 19: 4682-4693
7. J. Hong, C. S. Wang, X. Chen, S. Upreti, and M. S. Whittingham, "Vanadium Modified LiFePO4
Cathode for Li-Ion Batteries", Electrochem. Solid-State Letters, 2009, 12: A33-A38.
8. Y. Song, P. Y. Zavalij, N. A. Chernova, and M. S. Whittingham: Synthesis, Crystal Structure,
Electrochemical and Magnetic Study of New Iron (III) Hydroxyl-Phosphates, Isostructural
with Lipscombite. Chem.Mater., 17: 1139-1147(2005).
9. N. A. Chernova, M. Roppolo, A. Dillon and M. S. Whittingham, "Layered vanadium and
molybdenum oxides: batteries and electrochromics", J. Mater. Chem., 2009, 19: 2526-2552.
10. V. Petkov, P. Y. Zavalij, S. Lutta, M. S, Whittingham, V. Paranov, S. Shastri: Structure beyond
Bragg: Study of V2O5 nanotubes, Phys. Rev., B69: 085410 (2004).
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11. Y. Song, P. Y. Zavalij, M. S. Whittingham: e-VOPO4: Electrochemical Synthesis and Enhanced
Cathode Behavior, J. Electrochem. Soc., 152: A721-A728 (2005).
12. Jie Xiao, Natasha A. Chernova, and M. Stanley Whittingham, "Influence of Manganese Content
on the Performance of LiNi0 9_yMnyCo0 iO2 (0.45 < y < 0.60) as a Cathode Material for Li-Ion
Batteries", Chem. Mater., 2010, 22: 1180-1185.
13. Laura S. Rhoads, William T. Silkworth, Megan L. Roppolo, and M. Stanley Whittingham,
"Cytotoxicity of nanostructured vanadium oxide on human cells in vitro", Toxicology in Vitro,
2009, 24: 292-296.
14. Anurag Mishra, Afsar Ali, Shailesh Upreti, M. Stanley Whittingham and Rajeev Gupta, "Cobalt
complex as building blocks: Synthesis, characterization, and catalytic applications of {Cd2+-
Co3+-Cd2+} and {Hg2+-Co3+-Hg2+} heterobimetallic complexes", Inorganic Chemistry, 2009, 48,
5234-5243.
15. Natasha A. Chernova, Megan Roppolo, Anne Dillon and M. Stanley Whittingham, "Layered
vanadium and molybdenum oxides: batteries and electrochromics", J. Mater. Chem., 2009, 19:
2526-2552.
16. Kazuo Eda, Yu Ohshiro, Noriko Nagai, Noriyuki Sotani, and M. Stanley Whittingham, "Transition
metal tetramolybdate dihydrates MMo4Oi3-2H2O (M=Co,Ni) having a novel pillared layer
structure", J. Solid State Chem., 2009, 182: 55-59.
17. Chunmei Ban, Natalya Chernova, M. Stanley Whittingham, "Electrospun Nano-Vanadium
Pentoxide Cathode", Electrochem. Commun., 2009, 11: 522-525.
18. Jie Xiao, Natasha A. Chernova, and M. Stanley Whittingham, "Layered Mixed Transition Metal
Oxide Cathodes with Reduced Cobalt Content for Lithium Ion Batteries", Chemistry of
Materials, 2008, 20: 7454-7464.
19. Quan Fan, Peter Chupas and M. Stanley Whittingham, "Characterization of Amorphous and
Crystalline Tin-Cobalt Anodes". Electrochem. Solid State Letters, 2007, 10: A274-A278.
20. Quan Fan and M. Stanley Whittingham, "Electrospun Manganese Oxide Nanofibers as Anodes
for Lithium-Ion Batteries", Electrochem. Solid-State Letters, 2007, 10: A48-A51.
11. Patents (a selection)
1. Jin-Ming Chen, Yingjeng J. Li, Weir-Mirn Hurng and M. Stanley Whittingham, "Secondary
lithium battery using a new layered anode material", U. S. Patent 5,514,490.
2. M. Stanley Whittingham, "Chalcogenide Battery", U. S. Patent 4,049, 052.
3. M. Stanley Whittingham "Preparation of stoichiometric titanium disulfide", U. S. Patent
4,007,055.
4. M. Stanley Whittingham and Allan J. Jacobson, "High energy density plural chalcogenide
cathode-containing cell", U. S. Patent 4,233,375.
5. M. Stanley Whittingham, "Preparation of intercalated chalcogenides", U. S. Patent U. S. patent
4,040, 917.
6. M. Stanley Whittingham, "Electrochemical cells with cathode-active materials of layered
compounds", U. S. Patent 4,049,887.
7. M. Stanley Whittingham, "Alkali metal/niobium triselenide cell having a dioxolane-based
electrolyte", U. S. Patent 4,084,046.
8. Allan J. Jaconson and M. Stanley Whittigham, "Cells having cathodes derived from ammonium-
copper-molybdenum-chalcogen compounds", U. S. Patent 4,139,682.
9. Allan J. Jacobson, Russell R. Chianelli and M. Stanley Whittingham, "Cells having cathodes
containing chalcogenide compounds of the formula MaFeXb and species thereof exhibiting
alkali metal incorporation", U. S. Patent 4,143,213.
10. Allan J. Jacobson, Russell R. Chianelli and M. Stanley Whittingham, "Method of making cathodes
derived from ammonium-metal-chalcogen compounds", U. S. Patent 4,243,624.
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Bio:
Kurt Kelty
Director,
Battery Technology
Tesla Motors
3 5 00 Deer Creek Road
Palo Alto, CA 94030
650-413-4077
kurt@teslamotors. com
Kurt Kelty is the Director of Battery Technology at Tesla Motors. His team is
responsible for setting and implementing Tesla's battery cell usage. He is particularly
focused on evaluating the safety, performance and reliability of cells. His team then
develops basic cell packaging concepts for modules to enable the safe and efficient
packaging of the cells. Once the module and pack is designed, Mr. Kelty's team
validates the pack performance under extreme environmental conditions that might be
observed in the vehicle application.
Mr. Kelty is responsible for the technical exchanges and commercial negotiations with
each of the battery cell suppliers. He also leads the battery pack recycling and regulatory
efforts at Tesla. He is a member of SAE J2929 Electric and Hybrid Vehicle Propulsion
Battery System Safety Standard to create abuse standards for vehicle battery packs.
Mr. Kelty also leads the battery pack lifetime modeling and degradation efforts.
Before joining Tesla, Mr. Kelty worked for Matsushita (Panasonic) for nearly fifteen
years, seven of those years in Japan. At Panasonic, Mr. Kelty worked in various
planning and marketing capacities related to Ni-MH and Li-ion batteries. During the last
5 years, he founded and led Panasonic's battery research lab in Silicon Valley and created
R&D alliances between Panasonic and other battery and fuel cell developers in the U.S.
He is the author of 12 patents
Mr. Kelty received his B.A. in Biology from Swarthmore College in 1986 and his MSc
from the Stanford University Graduate School of Business in 1997.
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Erin O'DrisCOll erinod@charter.net
3856 Ken's Lane, Midland, MI 48642 989-859-9517
EXPERIENCE:
Dow Kokam, LLC, Global Research and Development Director 3/10 to Present
A innovative lithium ion battery technology company, providing batteries and packs into a variety of
advance applications.
Responsible for leading product development and innovation for Lithium Ion cell technology.
Currently building R&D capabilities from nothing. Includes hiring R&D team, converting empty
space into appropriate lab space (wet chemistry lab, pilot coating lab, cell testing lab, cell assembly
capabilities).
Developed and implement R&D strategy to double energy density as compared to current products.
Dow Koakm, Global Research and Development Director 3/10 to Present
Responsible for leading product development and innovation aligned to three markets, Pharma
Excipients, Food & Nutrition Additives and Industrial Specialty Additives. Managed $35 MM budget
with 120 people globally.
Led transition of R&D organization from a product driven effort into application and market focused
organization.
Enabled development of unique breakthrough in chemistry and process to transition into valued
added products aligned to critical market needs.
The Dow Chemical Company, Midland, MI 1990-3/2010
A leading science and technology company, providing innovative chemical, plastic and agricultural
products and services to many essential consumer markets.
Dow Wolff Cellulosics, Global Research and Development Director 3/09 to 3/2010
Responsible for leading product development and innovation aligned to three markets, Pharma
Excipients, Food & Nutrition Additives and Industrial Specialty Additives. Managed $35 MM budget
with 120 people globally.
Led transition of R&D organization from a product driven effort into application and market focused
organization.
Enabled development of unique breakthrough in chemistry and process to transition into valued
added products aligned to critical market needs.
BioScience Platform, Global Research and Development Director 10/07 to 3/09
Responsible for accelerating Dow's commercialization of biobased products by establishing new
strategic growth platform.
Responsibilities include developing and implementing internal R&D program, managing $11 MM
R&D budget and research staff of approximately 15 leaders. Other responsibilities include
negotiating key academic, institutional and business relationships, making recommendations on
Corporate Venture Capital investments and setting corporate strategy in advocacy and public
relations related to BioSciences.
Polyurethanes, New Business Development Manger 2/05 to 10/07
Responsible for developing and implementing the business plan to commercialize natural oil-based
polyols. Plan included a market entry strategy with key milestones for decisions on implementation of a
market growth strategy to meet Polyurethanes market and financial goals.
DOW RESTRICTED - For internal use only
-------
Erin O'Driscoll p2 of 2
Key decisions in developing market entry plan included setting scope of products offered, raw
material sourcing, scale of market development, breath of geographic launch, and product
positioning and pricing.
Key responsibilities in implementation of market entry strategy included, building a multifunctional
team, negotiating manufacturing contract, commissioning life cycle analysis, overseeing customer
trials, training sales teams geographies worldwide, establishing communication plan, preparing
Dow's investor relations personnel, conducting media interviews, and establishing and tracking
income statement. Responsible for $20 MM budget and staff of 10 functional leaders.
RENUVA was launched in September of 2007.
Responsible for biobased aspects of Dow's alternative feedstock strategy development.
Developed corporate talking points around biobased products, outlined US-based advocacy strategy,
participated in issues management teams, established market research program on biobased market
drivers.
Led preparation of multiple feedstock strategy documents for review by senior leadership resulting in
the creation of the BioSceinces Platform and my role as R&D director.
New Ventures/Natural Resources, Application Development Leader 1/04 to 2/05
Responsible for identifying and developing business growth options to diversify Dow's feedstock into
renewable materials.
Developed understanding of the market dynamics for key biomass feedstocks and surveyed
technologies to convert these feedstocks in products that fit with Dow's portfolio of products. Result
was a business case for projects in soybean oil based derivatives, cellulose polymers and a number of
glycerin based products.
Production of Epicholorohyrin from glycerin by Dow's Epoxy business is targeted for China in 2009.
Soybean oil derivatives projects were transferred to Polyurethane business and products were
launched in 2007.
Core R&D/New Products, Resource Leader 4/98 to 1/04
Led R&D group focused on new product development in area of coatings and functional polymers.
Managed 28 people, $8 MM budget spread over 10-15 projects focused on developing opportunities
for existing Dow business. Technologies included supercritical CC>2 decompressive spray, plasma
based siloxane coatings, low-dielectric coatings, living free-radical polymers, and photo-cured
coatings.
DowBrands R&D, Project Leader 2/91 to 4/98
Developed new products and led teams in the development of new household and personal care
products. Launched three new products and had two new products in test market from 1996-1998.
Represented DowBrands in two nationally televised T. V. and print ad campaigns.
Research Assignments Program, Senior Research Chemist 4/90 to 2/91
Completed projects in on-line analytical instrumentation, polymer kinetics, and consumer product
development.
Education:
Ph.D. in Physical Chemistry, University of Colorado-Boulder; Boulder, CO, 1990
B.S. in Chemistry, Boston College; Boston, MA, 1985
DOW RESTRICTED - For internal use only
-------
JOSEPH X. ADILETTA
5 West Place
Cambridge, MA 02139
H - (617) 547-8641; C - (703) 627-9905
j_adiletta@sloan.mit.edu
Education
2001 - 2003 MIT SLOAN SCHOOL OF MANAGEMENT Cambridge, MA
Master of Business Administration, June 2003
1992 - 1997 CORNELL UNIVERSITY Ithaca, NY
MEng - Civil Engineering, Management Option, May 1997
BS - Mechanical Engineering, May 1996
Experience
2006-Present A123 SYSTEMS Watertown, MA
Senior Manager, Market Intelligence (2010 -Present)
De
veloped and implemented a comprehensive market intelligence program for the company.
Ens
ured long-term differentiation of A123 products across three vertical market segments.
Dir
ected R&D technical and cost targets based on likely competitive development scenarios.
Senior Product Manager (2007- 2010)
Util
ized emerging technology trends, customer application input and competitive product knowledge to
provide strategic guidance and technical insight to next-generation cell development team.
Ma
naged technical development program for multiple small format products from business conception
through material selection and early pre-production runs.
Sup
ported focused cost reduction activities on highest value materials and processes.
Product Manager (2006-2007)
Tra
nslated customer needs into product specifications and drove development process.
Ov
erhauled key marketing assets, including website redesign, brand messaging, tradeshow strategy and
press release content and timing.
2006 GEN3 PARTNERS Boston, MA
Consultant
De
veloped and implemented front-end innovation methodologies to identify latent customer needs and
advance products' main parameters of value.
Pro
vided critical insight to clients by leveraging relationship with Russian technical team.
2003 - 2005 PRODUCT GENESIS Cambridge, MA
Strategic Innovation Consultant
Un
earthed client/customer needs using advanced innovation techniques such as Lead User analysis,
Voice of the Customer and Scenario Planning to assist Fortune 500 clients with next generation
product design and development.
Res
earched and analyzed clients' businesses to develop key future scenario models based on analogous
and historical adoption.
2002 BUYERZONE Watertown, MA
Category Manager
Augmented existing marketing programs through P&L analysis of fifteen business categories,
producing 35% revenue growth, and 24% net revenue growth.
Analyzed opportunities to expand business into additional marketplaces, down-selecting five
markets from a pool of fifty, which were added to active sales list.
1997-2001 MICROSTRATEGY Vienna, VA
Angel.com - Product Manager (2000-2001)
-------
Joseph X. Adiletta (page 2) (617) 547-8641
Created go-to-market strategy for incubated voice-technology venture, based on market
research and input from organized focus groups.
Various Functions (1997 -2000)
Developed and implemented new technical support offering geared towards high-end customer
needs, driven by sales and marketing analysis, and resulting in additional $1M in annual
support revenue within twelve months.
Managed resolution of escalated technical support issues for Global 2000 client base, reducing
overall support case-count by 50 percent based on thorough case tracking analysis.
As Quality Engineer, improved cutting-edge broadcast technology product and ensured early
release to market while exceeding quality standards.
-------
Michael (Micky) J. Ely
General Motors Executive Director, Group Global Functional Leader
Global Electrical Systems, Hybrids, Electric Vehicles, Batteries, Infotainment & OnStar Engineering
Micky Ely is Executive Director, Group Global Functional Leader of Vehicle Engineering's Electrical
Systems, Hybrids, Electric Vehicles, Batteries, Infotainment and OnStar Engineering for General Motors.
Named to this position in June of 2010, Ely oversees the company's design and development of traditional
electrical and infotainment systems, OnStar engineering, hybrid and electric vehicles, which includes the
Chevrolet Volt's vehicle integration and advanced battery development.
Previously, he was Executive Director of Engine Hardware Analysis, Design, Development and Validation.
From 2006-2008, Ely was Director of Global Hybrid Integration and Controls. He oversaw the teams
responsible for the production and development of GM's multiple hybrid vehicles, and contributed to the
integration work on the Volt. Ely' s team of engineers made sure all of the components - from the engine,
transmission, brakes and batteries, to the controllers and software - came together seamlessly. He is
particularly proud of the 2008 Chevrolet Tahoe Hybrid, which was named Green Car Journal's "Green Car
of the Year."
Ely joined GM as a student intern in 1986 and was hired to GM's Powertrain Engineering staff after
graduating from Georgia Tech with a bachelor's degree in mechanical engineering in 1990. In 2003, he
received a master's degree in engineering from Rensselaer Polytechnic Institute.
In his 20 years at GM, Ely has worked on various powertrain programs in the United States, England and
Germany. His first position was in Warren, Mich., as a Powertrain Development and Validation engineer.
He held positions of increasing responsibility in the Small Block V8 engine group, including lead
development engineer for the iconic Corvette C5 V8 engine group. In 1997, he was transferred to Lotus
Cars in Norwich, England, and promoted to Engine Management Systems engineer for GM's highly
successful Ecotec L4 - GM's first global four-cylinder engine program. He also was vehicle system
engineer for powertrain for the Opel Corsa and Vectra programs at Opel engineering in Russelheim,
Germany.
Upon returning to the U.S. in 2000, Ely was appointed engineering group manager for North America
Emission Controls Hardware. Two years later, he assumed the role of V6 Calibration System manager at
GM's Milford Proving Grounds. In 2003, he was appointed to oversee all technical briefings and staff
facilitation on behalf of the GM Powertrain group vice president and continued this work until his
executive appointment overseeing hybrid vehicle integration in 2006.
Ely is GM's key executive for the Georgia Institute of Technology and serves as a member of the Woodruff
School of Mechanical Engineering Advisory Board. He is Co-Director of the General Motors/ University
of Michigan Advanced Battery Coalition for Drivetrains, which is a joint research program focused on
spanning the gap between battery material synthesis and vehicle controls integration while developing the
next generation of battery engineers. He became a board member for Hughes Research Laboratories in
October 2009 and a board member of Michigan FIRST Robotics in 2010. Ely is the former co-executive
GM lead for EcoCAR, one of North America's premier college automotive engineering competitions that is
sponsored by GM and the U.S. Department of Energy.
July 2010
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 1 : Assumptions - (a) Propriety materials
1
2
3
4
207
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
There is no allowance made for the cost of using proprietary materials, such as licensing
costs. This may be important in comparing one material with another. Also see
[Wittingham's comments] below.
No comments
No comments
No comments
No comments
Question 1 : Assumptions - (b) Estimates of materials cost
5
6
7
8
9
10
11
12
13
14
208
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
In a number of places, it is stated that "it is estimated that the cost of for example the
separator is $2 per square meter, or the NMP is x.
These are well known materials that are used in large quantities and extensively in the
industry today. What are today's costs, and the authors need to explain how and why the
estimated cost differs from today's costs if they do.
The cost of some of the key components may not drop dramatically if one material is
sufficiently superior and the manufacturer has patent protection, for example the separator
(Celgard). See page 29, 1st full paragraph, where the first full paragraph justifies the cost
because the raw materials are low cost. It ignores the proprietary technology that must be
included in the cost. Separators are not simple, they must close down the battery if
necessary, prevent dendrite formation etc. Today's cost should be clearly listed. We all know
that LiFePO4 is not low cost, even though the raw materials are low cost.
In Table 4.1 there is no explanation (in the table or the text), that I could find, for the three
numbers under the TIAX 201 0 column. A footnote under the table on the same page could
easily explain the different numbers to the reader.
In Table 4.1, why is there not a number for LCO in the ANL 2010 column? This number must
be well-known and would represent a good and solid baseline to compare the other numbers
against (and to test the spreadsheet model against).
On page 28, 3rd line the prices for cobalt and nickel metal prices are given. The relevant
costs are those of the oxide or other raw material that will actually be used in the
manufacturing process; the formation of the metal can be very expensive. So perhaps the
price of the oxide should be substituted here.
On page 30 section 4.2.1 .4 "No cost is assumed for water" But what about the cost of
handling the contaminated waste water? There are several companies trying to use dry
processing to eliminate the cost of handling NMP and water.
No comments
No comments
No comments
No comments
Question 1: Assumptions - (c) Units of capacity
15
16
17
18
209
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
In some sentences, the weight of the material is in kg and then the capacity is given in
mAh/g. The latter should be changed throughout into Ah/kg for these large batteries. The
numbers stay the same.
No comments
No comments
No comments
No comments
C-1
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 1 : Assumptions - (d) Cell construction and format
19
20
21
22
23
24
25
26
210
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
The flat plate format chosen (prismatic/pouch cells) chosen for this study appears to be the
most appropriate. This part of the report perhaps could be made clearer.
It is ambiguous if the cell is pouch or can in early sections (drawing is misleading). Later it
become clear.
Construction and format are within norms, but many folks at winding with individual
electrodes, not using the back and forth folding method.
Other form factors could be considered.
The cell size is arbitrarily limited.
Opposite-side tabbing structures for energy-based systems goes against most common cell
formats (canned or pouch), which have same-side terminals.
Specific material assumptions produce a generally usable view of the market, yet do not use
optimized designs that specific manufacturers are likely to employ.
Thicknesses of substrates might be double-checked/triangulated.
Seems reasonable and appropriate
Question 1: Assumptions - (e) Comparability to competing cell formats
27
28
29
30
31
211
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
The most likely alternative as used today in HEV (cars, buses) is the cylindrical 18650 cell,
which are almost certainly more expensive for large batteries (too many cells with all their
contacts etc). Larger cylindrical cells are likely to have more severe thermal management
issues. So the flat plate prismatic cells chosen are best choice
No comments
No comments
The model assumes an opposite-end tabbed cell design in pouch form factor. Organizations
such as VDA are employing specifications for metal-canned prismatic cells as well, which
offer differing price/performance characteristics.
Cylindrical cells for HEV are not considered, nor are wound electrode designs in general.
Seems reasonable and appropriate
Question 1: Assumptions - (f) Cooling and thermal management requirements
32
33
34
35
36
37
212
213
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
Thermal management is inadequately covered. As described, the battery pack will have one
cm of insulation around it and be air-cooled. How does the battery get cooled in the summer
when it is operating? I do not believe that air cooling is realistic (or is there a refrigerator built
in for cooling the air). The battery pack will need liquid cooling (or heating in extreme
environments) to maintain a lifetime listed as 10 years. (I realize that the Nissan Leaf only
has air cooling, but is that realistic)
My recollection is that Lew Gaines (from Exxon Enterprises in the 1970s) found that thermal
management was the most challenging aspect of large batteries (paper published in
Intersociety Energy Conversion Conference ?)
Air cooling is often inadequate for EV packs today. It could be that pack in 2020 can achieve
good performance with air cooling alone, but this assumption should be spelled out more
clearly.
Cooling and thermal management requirements: This needs to improve for EV.
Cooling and thermal management requirements: Temperature effects should be
considered.
A wide variety of cooling strategies necessitates flexibility here, though perhaps with some
built-in functionality/choice around air vs liquid cooling and/or active versus passive.
Does not appropriately recognize the trade offs of life and thermal effects.
Much further model refinement would be needed to improve the models accuracy
C-2
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 1: Assumptions - (g) Electrode volumetric change
38
39
40
41
42
214
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
Electrode volumetric change: I did not see this item discussed in the report; but I do not view
it as a major concern for the materials considered. The electrodes must be kept under
compression to maintain capacity on cycling. As the anode contracts the cathode will
expand.
Electrode volumetric change: The one exception is the use of LTO as the anode. This is a
zero expansion material so that the volume changes in the cathode cannot be compensated
by the anode change.
Assumption of zero volumetric change is optimistics 10% overfull SOC range is more
reasonable.
This is not considered.
No comments
No comments
Question 1: Assumptions - (h) Limiting parameters affecting cell dimensions or performance (for
example, allowable A-hr capacity per cell, maximum electrode thickness, etc.)
43
44
45
46
47
215
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
These are all well described, but then hand-waived away by "successful cell manufacturers
will engineer ways to overcome these challenges to increase energy density and lower cost".
This gives no guidance to the user of the excel model.
Numbers are within standards today. I would assume by 2020 there would be higher
capacity materials that would give higher energy densities in smaller sizes.
These are not validated in the paper and seem arbitrary.
Assuming that all chemistries have a similar usable energy window (within 5% of one
another) is not valid in practice. This is true for both PHEV and EV. A larger disparity
between oxides and phosphates exists.
There will definitely be a max electrode thickness based on the specific chemistry involved.
More pointedly, there will be a max thickness based on the specific cell TYPE that is being
developed: microHEV, HEV, PHEV or EV.
No comments
Question 1 : Assumptions - (i) Warranty costs and profit
48
49
50
51
52
53
216
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
For a new product the warranty cost assumptions of 1 % failure per year appear too low. The
costs assumed appear to be those purely due to replacing the battery, not including other
issues such as liability insurance.
The ROI appears too low at 5%
would expect warranty assumptions to be somehow related to performance like cycle life or
calendar life. This is especially concerning in air cooled pack. I think an assumption related
to cooling system and life would make more sense but would be challenging to build into this
model now.
No comments
think that it would make more sense to target a before-tax profit and structure the model
around target margin. Predicting and/or modeling the going corporate tax rate would likely
be difficult in and of itself.
Profit rate looks a bit lower than expected over the long-term.
See cooling and thermal management requirements
Question 1 : Assumptions - (j) Scrap rates and associated costs
54
55
56
57
58
59
Whittingham
O'Driscoll
Kelty
Adiletta
The % scrap rate appears reasonable
No value is assigned to the scrap, although by 2020, if the market is indeed there, there
should be a thriving recycling business that would take the scrap away.
Looks reasonable.
No comments
Are scrap rates inclusive of end of line testing?
NMP recycling number seems high.
C-3
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
217 |Bly
Looks reasonable.
Question 1: Assumptions - (k) Recycling value
60
61
Whittingham
The value of the recycled battery is not discussed, even though it is presumed by other ANL
reports that eventually most of the lithium (and presumably any expensive other elements)
would come from recycled batteries.
There is also talk about using "spent" EV batteries for utility/alternative energy load
leveling/smoothing. Surely this would reduce the effective life-time cost of a battery.
Question 1: Assumptions - (I) Safety and manufacturability
62
63
64
65
66
67
68
218
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
An issue with all batteries is protection in the case of crashes. This report does not really
address that issue. Is it the intent that the one cm insulation will also serve as a crash
protector? Such protection costs money, and needs to be included.
Safe handling of inorganic metal powder is not addressed well at all here. EPA guidelines
for handle materials with Ni an Co are much different than Fe and hence one would expect
different cost structure to handle the materials in the process. Section 4.3.2 does not
address moving powder through the process and cleaning up safely.
Handling of large quantities of electrolyte without contamination is also not handled well.
What size container is expected and how is the material kept clean and dry at this scale?
Where are the safety features in the battery pack? CID?
No comments
Certainly the addition of certain components to ensure safety must be accounted for. For
example, the oxide-based chemistries often use ceramic coatings on the separator or anode
to compensate for the inferior abuse tolerance of that chemistry. The cost of this must be
included in the cell cost.
think that a SOOum, thick electrode coating is somewhat aggressive to expect performance
out of the design.
No comments
Question 1: Assumptions - (m) Anticipated industry design trends, and similar factors
69
70
71
72
219
Wittingham
O'Driscoll
Adiletta
Ely
No comments
believe that by 2020 there will be some non-slurry coating manufacturing approaches on
the market. In this case the solid electrode would be directly deposited on current collector -
difficult to model now but I believe this will be validated by then.
The industry seems to be attempting to move towards a more standardized form factor -
VDA specifications, as well as SAE proposals.
From a cost perspective, you'll likely have to assume some take-off in overall volumes.
There is some sensitivity to where this will all play out, but it will have a profound effect on
materials costs for specific manufacturers. Thus, constructing the model to be based on
number of vehicles produced makes sense.
No comments
C-4
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 1: Assumptions - (n) PHEV types and drive train
73
Whittingham
PHEV types and drive train: Table 3.1 addresses only one class of PHEV battery, whereas
today's scenario goes all the way from the planned Toyota Prius, with 3 batteries (one power
and two energy) each essentially the same size as in todays HEV Prius with a dual drivetrain
(1C and electric) and an all-electric range around 8-1 0 miles to the GM Volt with around a 1 5
kWh battery, an electric generator and an all-electric drive-train and a range of around 40
miles. So the assumptions made for PHEV may not be optimum or even correct, [the
comment about increasing levels of electrification is incorrect; the Volt PHEV is all electric
drive, the HEV buses are all electric drive with around a 1 1 kWh lithium-ion battery - more
than 2 million total miles, so building up reliability experience]
Question 1: Assumptions - (o) Unanticipated breakthroughs
74
Whittingham
It is almost impossible to anticipate a significant cost breakthrough, as occurred when the
Chinese decided that the common MCMB carbon used as the anode was too expensive and
they replaced it with a much lower cost graphitic carbon. MCMB is no longer manufactured.
Question 1 : Assumptions - (p) Additional reviewer comments
75
220
Adiletta
Ely
I mention this below, so you'll see it twice, but the way the cells are designed given the
thickness of electrodes and number of layers in many ways doesn't follow conventional
design strategy. For instance, in the base case sent around (PHEV done by mileage), the
thickness of the electrodes varies, which it wouldn't in practice, leading to higher overall
current collector costs in smaller capacity/range systems. In fact, it would work the other
way: You would settle on a single electrode design for the cell-type (HEV, PHEV, EV) and
then vary the number of layers based on that design to accommodate different ranges.
In general most of the cost models do not seem aggressive enough for 2020 forecasted total
costs
Question 2: Inputs and Parameters - (a) Embedded or default values chosen by the authors (for
76
77
78
79
80
81
82
83
221
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
Embedded or default values chosen by the authors: These seemed adequate, and I found
that I could change them and they had an effect on the resulting cost, but not nearly as much
as I would have expected. For example switch the capacity of LFP from the default value of
155 to 50 Ah/kg had less than a 20% effect. Can this be right?
Embedded or default values chosen by the authors: Look in line with my expectations.
Active material cost projections would be helpful.
Dimensions for cells should be user defined & not specified by the model.
What values were measured experimentally? There is no validation data in the report. The
key relationship used to design the battery is an estimation for the relationship between
impedance and electrode thickness. Presumably these measurements were made for a few
different electrodes & are now applied to all electrodes. Where is the data to show that this
is a reasonable assumption?
Electrode design specifications are often unique to individual manufacturers. The existing
values might be adjusted based on other publicly available information.
Materials costs inputs do not necessarily match with going rates in volume production.
The assumption that all negatives will necessarily use a water-based binder system should
be questioned, especially given the range of cell-types being investigated - micro-HEV
through EV.
Seems appropriate for this study
C-5
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 2: Inputs and Parameters - (b) The adequacy of user-specifiable parameters and their
84
85
86
87
88
89
222
Whittingham
O'Driscoll
Kelty
Adiletta
Ely
The adequacy of user-specifiable parameters and their allowable ranges: I found no
difference in the battery cost whether the operating hours per day were 10 hours, 24 hours
or 48 hours. Surely depreciation should cause some effect, and the spreadsheet should be
set-up so that no value over 24 hours can be input.
The adequacy of user-specifiable parameters and their allowable ranges: Difficult to fully
assess this in the time period given.
More parameters should be user specifiable. There are a lot of limitations currently on what
can be changed.
For micro-hev and HEV, it would make sense to specify power required, rather than the
choices currently available: Capacity, Energy or Range. This is especially true if 2/4 of the
options are HEV related (micro and full).
assume that some of the user inputs are considered in the model for future use? For
instance, ASI seems to be calculated but not necessarily applied, as do entries like
temperature rise, etc.
understand as reviewers we are supposed to focus on the quantitative aspects of the
model; however, structuring the model for use by someone not well versed in specifics of
chemistry would be useful. For instance, it's not quite clear exactly what all of the inputs and
outputs are. There are clearly sheets that contain foundational information but might not be
used by someone doing top-level analysis.
Seems appropriate for this study
Question 2: Inputs and Parameters - (c) Additional reviewer comments - cell
90
91
Adiletta
Any reason to not consider 2p configurations? Are you assuming that by 2020 all cells will
be optimally sized for the application?
You assume that manufacturing costs scale independently of cell design, which is not
entirely appropriate. For instance, the cost of forming a cell may be linear to the number of
cell layers, but the depreciation cost on a per cell basis of the stacking equipment will not be,
given that your cell designs do not appear to scale number of layers linearly with capacity.
Question 2: Inputs and Parameters - (c) Additional reviewer comments - pack
92
93
Adiletta
Looking at today's vastly different pack structures/constructions, it would make sense to
account for some variation there. Two examples: (1) I did not see a liquid versus air cooling
entry point; (2) Some packs use aluminum cooling plates as separators, others use only
passive-type cooling with no structural support.
Have government subsidies on capex purchases been factored in here as well?
Question 3: Cost Methodology - (a) Dollar values
94
95
96
97
223
Whittingham
O'Driscoll
Adiletta
Ely
On page 25, it is stated that "All dollar values are brought back to 2010 with allowance for
inflation". What does that mean? Why not use 2010 dollars in the first place and let the user
include a term for inflation, and build into the model.
As mentioned by this reviewer elsewhere, processing improvements that would potentially
reduce costs are likely to come with licensing fees.
No comments
No comments
No comments
C-6
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 3: Cost Methodology - (b) General scaling methods on manufacturing and material costs
98
99
100
101
102
103
224
Whittingham
O'Driscoll
Adiletta
Ely
am somewhat confused by the numbers in Table 4.8 and the cursory description on pages
46 and 48. As the text reads the cost of the double capacity goes up, but surely what the
model user/consumer wants to know what is the cost per kWh or per mile driven. Then does
not the cost go down when the capacity is increased? The writing is confusing. I understand
that if you want more power, then it is going to cost more, but if you want more energy per
cell then the cost of the cell per kWh goes down. This part should be rewritten to emphasize
what is of interest to the end-user: it will cost you $279/kWh for a 8.7 kWh battery and only
$206/kWh for a 1 7.1 kWh battery with the same number of plates?
Using the argument in the two lines above, I assume the model methodology allows for
increasing the current collector thickness as the plate size increases so that the resistive
losses do not increase. How easy is it to manipulate and optimize the plate size.
On page 63, the effect of manipulating the active material thickness is described so that the
energy stored can be increased by thickening the electrodes and therefore reducing the area
of the current collectors and separators needed.
No comments
I would only comment that at a certain volume, significant changes to manufacturing process
will be required, which will bring associated reductions in cost. This model seems based on
today's methodologies, however applied to 2020, which may not be realistic.
The material cost structure (BOM) as outlined is not indicative of TODAY'S pricing, which
would imply significantly higher costs than what we would expect to see in 2020.
Raw material scaling costs are reasonable for this study
Question 3: Cost Methodology - (c) Effect of production level on manufacturing and material costs
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Whittingham
O'Driscoll
Adiletta
Ely
Effect of production level on manufacturing and material costs: Several examples are given
of the methodology are given and appear reasonable.
Effect of production level on manufacturing and material costs: On page 28, it is argued that
the manufacturing cost will decrease with increased knowledge form larger scales of
production. This is related to a discussion of LFP. However, a recent litigation has shown
that a lower cost method for production is well patented (Valence vs Phostech), and those
who need to produce and/or sell in the US are going to have to pay licensing fees. [LFP does
not require a reducing atmosphere and a carbon coating step - it can be done in one stop by
the carbothermal process of Valence using low cost ferric raw materials].
See previous comment on warranty. Without correlation to data warranty assumptions are
reasonable. Profit assumptions are reasonable.
There is going to be a significant delta in materials costs based on expected production
volume. This should be able to be added, even if in vague terms via percent cost downs
based on specific manufacturing thresholds.
Coating facilities run at speeds entirely dependent on the chemistry and cell design, thus
drastically altering the amortization of costs to the cell. This augmentation might be
considered.
No comments
C-7
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 3: Cost Methodology - (d) Method of accounting for warranty costs and profit accounting for
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Whittingham
O'Driscoll
Adiletta
Ely
It is not clear that a method was used for warranty costs and profit.
Profit is fixed at 5% of total investment costs. This seems too low for a risky investment. An
ROI closer to 10% would be more reasonable.
The cost methodology for warranty costs is not too sound. Where did the writers come up
with an annual failure rate of 1% (page 46)? What is it today for the much simpler HEV cell
in the Prius or in the Honda (where I gather there may be an early failure problem). No
lithium battery has been used in the proposed duty cycle for anywhere close to 10 years.
Justification for this assumption should be made.
Insurance is mentioned in a couple of places, but it seems to be associated with the
manufacturing plant. What is the need for liability insurance in the case of an injury related
incident of the finished product when in use?
No comments
Typically we'd talk about warranty as a % of cost, which I assume is what "added to price"
means, rather than a % of final price.
Warranty cost model seems to be appropriate for this study
SG&A and profit seem to be very high compared to current market and will not improve to
these levels with current over capacity projects in the free trade markets
Question 3: Cost Methodology - (e) Effect of demand on raw material costs
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228
Whittingham
O'Driscoll
Adiletta
Ely
This is fine as described: keep away from low availability materials, where the battery market
is a prime user of the material, such as cobalt. The report also mentions the high cost of
nickel.
As noted in the report, iron and manganese are fine.
A bigger issue than the battery for electric vehicles is probably the rare earth metals needed
in the electric motors. This naturally is not a part of this report, but the user of the model
needs to be aware that other items than the battery may be cost controlling.
No comments
This does NOT seem to be accounted for. The effect is real, quantifiable and quite different
for each battery manufacturer depending on volume and relationship.
Especially out in 2020 and beyond, some reasonable assumptions must be made based on
today's high volume cost rates. It does not appear that this was taken into account. At the
very least a single input for % decrease based on volume might be added.
Demand assumptions do not show an obvious strong influence of material cost and seems
reasonable
Question 3: Cost Methodology - (f) Depreciation
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Whittingham
O'Driscoll
Kelty
Adiletta
Ely
No real justification for model used for depreciation - appears to be pulled out of the air.
Probably too low at 12.5%; this value assumes an 8-year life. For a new and probably
changing technology a shorter depreciation time is needed at least for the first 5-10 years.
No comments
5-year depreciation is more appropriate.
Have you accounted for government subsidies in the acquisition of capital equipment?
8 years on manufacturing equipment seems a bit long.
Model shows an 8 year amortization which is slightly higher than current norms in the
industry
C-8
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 3: Cost Methodology - (g) Research and development
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Whittingham
O'Driscoll
Adiletta
Ely
R&D comes in two forms, support for the manufacturing operation (quality control etc), as
well as developing new products, that is to remain state-of-the-art. It is not clear which is
intended here.
As mentioned in this review elsewhere, the cost of licensing technology has not been
included. No one outfit is going to have complete "ownership" of the materials and design.
This is not built into the methodology.
No comments
Typically we'd talk about R&D as a % of revenue rather than of depreciation.
No comment. Too variable in this fast pace development area
Question 3: Cost Methodology - (h) Baseline plant design and scaling
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Whittingham
O'Driscoll
Adiletta
Ely
Seems fine, but I wonder how the model handles for example 4.3.4 Calendering, which has
1 person per shift. No person is going to work continuously without a break. How are these
breaks covered whne the process in presumably continuous. This is perhaps asking is there
flexibility built into the cost methodology.
Working capital seems low.
Initial plant design looks reasonable. I think you should consider scalability based on volume
assumptions. At some point, volumes could become large enough that a transition to new
manufacturing strategies would make sense in order to continue down the cost curve.
Scaling would be done incrementally based on capacity ramp-ups. To that extent, the model
seems to function linearly with respect to invested capital, whereas that's not the "true"
effect, where 100s of millions are invested for a fixed capacity which may or may not be fully
utilized, and thus cost affected.
20 year amortization of capital investment is much lower than actual practice in Asia supply
base
Model for building cost does not seem realistic, unless model assumes continuous
government incentives, which is not realistic in this timeframe.
Question 3: Cost Methodology - (i) In-house vs purchasing outside (page 25 bottom)
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Whittingham
Adiletta
The methodology here is probably OK, as you would do in-house for several reasons: lower
cost, security of supply, proprietary steps.
For each of the above reasons, the cost is presumed to be lower than purchasing outside,
so methodology and numbers probably OK.
No comments
C-9
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Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 4: Performance Methodology - (a) How the physical properties and dimensions of cell
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Whittingham
O'Driscoll
Kelty
Adiletta
Adiletta
Ely
The battery design model seems OK
The only are [sic] I have concern with is how the effective tap density of the materials is
incorporated into the model. It appears to be through the void volume.
Theory looks sound.
See above comment regarding lack of validation data for ASI assumptions
It seems that the cell thickness and number of layers are oddly calculated. In the standard
10mi PHEV case, you end up with a 16um cathode -obviously unrealistic, which then
required 64 layers? I think an alternate approach would be to target a thickness based on
the type of cell desired, and subsequently vary the number of layers to achieve differing
mileage/capacity packs.
As with thicknesses, densities are variable based on chemistry employed and desired cell
type - HEV vs EV.
You would not necessarily constrain the thickness of the cell based on the cell type, for
instance 10mm for PHEV. In non-standard designs (those outside of a footprint standard
like VDA), you might float the thickness to achieve a given capacity once you have a
footprint in mind.
No comments
Question 4: Performance Methodology - (b) How power, energy capacity, resistances, and currents
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Whittingham
O'Driscoll
Kelty
Adiletta
Ely
These, like voltage at maximum power, seem very reasonable
As noted under (1), some generic statements like "PHEV cells should be much larger than
HEV cells and thus a cell thickness of 10 mm is assumed" are almost certainly not entirely
correct if Toyota's Prius model is to be believed.
Theory looks sound.
No comments
I'm curious as to why the power was a user input rather than calculated from the ASI, which
seemed to be painstakingly calculated. When comparing chemistry to chemistry, the
delivered power based on the cell design is important.
Your limiting C-rate is not going to be constant, it will vary based on cell design and
chemistry, which is also based on the application you would be designing the cell for: micro-
HEV, HEV, PHEV, EV.
No comments
Question 4: Performance Methodology - (c) Additional reviewer comments
151
O'Driscoll
In general I have concerns that with the approach from theory only to full scale cost model.
Any theory should be correlated with experimental results. I am surprise that no correlation
is made to actual data. While properties of materials like mA/g are true in theory many times
they are not accurate in practice. At least one example showing a cell and/or pack that
correlates to this model is necessary for credibility that this approach is valid.
Question 5: Completeness - (a) Physical components of the cells and assembled packs
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Whittingham
O'Driscoll
Kelty
Adiletta
Ely
Yes [complete]
No comments
CID?
Physical components of the cells and assembled packs: Cost of terminal assemblies seems
low.
Physical components of the cells and assembled packs: No cost accounted for tape in cell
(albeit small cost).
Seem appropriate
C-10
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 5: Completeness - (b) Support circuitry such as for cell charge control and balancing
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Whittingham
O'Driscoll
Kelty
Adiletta
Ely
Yes [complete]
Active cell balance is new but should be standard for 2020.
No comments
No comments
Model assumptions simplify the circuitry to represent a state of the art battery management
system
Question 5: Completeness - (c) Manufacturing steps
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Whittingham
O'Driscoll
Kelty
Adiletta
Ely
Yes [complete]
Very standard.
No comments
There are certainly inspection steps that require personnel and equipment not included in
the process steps.
No comments
Question 5: Completeness - (d) Raw materials and labor
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Whittingham
O'Driscoll
Kelty
Adiletta
Ely
Yes, but see earlier comments about situation where only one person ahs been assigned to
the task (what happens in breaks)
Labor is low across the board. Labor may be lower in 2020 but I don't see additional
automation build in to achieve a decrease in labor.
See above comment regarding projecting future costs for active materials.
No comments
Labor rates are appropriate only for US
Question 5: Completeness - (e) Energy inputs and consumables used in manufacture
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Whittingham
O'Driscoll
Kelty
Adiletta
Ely
Consumables discussed, but impact of cleaning resulting waste streams did not appear to
be covered.
Energy input (aka utility costs) were not specifically covered, except as in "Variable
Overhead" in Table 4.7 and these are assumed to be 60% of the direct labor costs. This is
probably not ideal, as the more automated the plant the lower the labor costs and the higher
the utility costs. Building the plant in a low humidity climate, such as Tucson, might result in
lower utility costs than in humid Michigan because of the extensive dry-rooms that must be
used.
No comments
No comments
No comments
This model significantly underestimates energy input cost. Unrealistic as presented
Question 5: Completeness - (f) Capital equipment
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Whittingham
O'Driscoll
Kelty
Adiletta
Ely
Yes [complete]
No comments
No comments
No comments
Very much underestimate capital investment required for cell manufacturing with state of the
cell technologies
C-11
-------
Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 5: Completeness - (g) Research and development costs for battery design, development,
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Whittingham
O'Driscoll
Kelty
Adiletta
Ely
As noted elsewhere, the whole are of licensing fees has been neglected, even though lithium
batteries are the subject of many expensive litigations these days.
No comments
No comments
No comments
Unable to comment
Question 5: Completeness - (h) Battery control system hardware and software
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Whittingham
O'Driscoll
Kelty
Adiletta
Ely
Yes [complete]
No comments
This is lacking in completeness. Critical safety features are not included (isolation
contactors, etc.). The argument could be made however, that these costs are an
insignificant cost of the total battery pack - the active materials being the key cost driver.
This then leads to the argument that the model should be much more focused on the costs
of these active materials.
No comments
Seems appropriate based on state of the art design
Question 5: Completeness - (i) Additional reviewer comments
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Adiletta
Ely
It would be nice to have an overall summary sheet that compared packs of different
chemistries side by side.
The targeted user should be considered when structuring the model's inputs/outputs such
that someone not completely versed in battery chemistry/manufacturing structure might be
able to use the tool.
From a general completeness standpoint, I would say that the model has MOST aspects
well covered. The real issue is with generalizing battery manufacturing. Every manufacturer
deals with a specific chemistry, with specific designs, with specific manufacturing processes,
subsidies, etc. This makes this type of information extremely difficult to not only publicly
disclose, but also to model with reliable and useful results. Being on the outside of the
industry looking in is a difficult position to be in relative to modeling each of these
parameters such that a lay-person might understand the key issues that a specific
manufacturer has to tackle.
Augmenting the model with the capability to size a system based on desired capacity/energy
rather than dealing with system sizes as prescribed by the model.
Model seems to have a very high level of cost structure with lack of details in burden,
interest, maintenance, and indirect labor.
C-12
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Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
Question 6: Recommendations - (a) Recommendations
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Whittingham
O'Driscoll
Kelty
1 Clearly the spreadsheet needs to be made user-friendly, yet not allow for the non-expert to
make unrealistic inputs and assumptions.
a. For example daily operating time should not be allowed to exceed 24 hours
b. To be user-friendly one should be able to just select the system of interest, and not have
to cut and paste it in the System Selection screen.
c. There is a heading issue with the cost input screen. When switching from NCA to LFP, the
cathode heading does not change to LFP but the numbers do.
d. The description for users needs to be generalized. Page 49 - There is no "Options" under
the "Tools" drop-down menu on the Mac excel 201 1 ; it can be found under the main Excel
drop down menu (by going to Preferences , then to calculation).
2 The weakness of any model is that a major scientific/technological breakthrough might
transform the playing field.
3 Keep the wording simple, for example what kind of dollars are being used. Stick to 201 0
dollars and let the user consider inflation.
4 The model needs to include better thermal management. Long-lived batteries will almost
certainly need liquid cooling or heating in certain climates in winter.
The article is very ambitious in its goals. As I wrote in my comments, I have concerns with
the approach from theory to full scale cost model without correlating theory to data.
We simulated a few EV packs and the price is lower than anticipated. This may be due in
part to the extremely thick electrodes that the model predicted. The model should limit
electrode thickness to a user defined value, we suggest less than 200 micron.
Please summarize somewhere clearly in the report how the model accounts for the cost in
2020. It appears that current costs are input, and the spreadsheet does not appear to be
adjusting anything except the plant scale.
User-defined inputs are currently:
1 . Battery power
2. # of cells & modules
3. Target voltage at max power
4. Battery pack energy or vehicle electric range & efficiency. I think that this model would be
improved with this input also (or in place of #1):
1 . A metric for acceleration such as the time it takes to accelerate from 0-60 mph at a
specified temperature.
Metal pricing is ignored. This model claims to be forecasting pack cost in 2020 but does not
appear to be accounting for changes in the cost of active materials over time. This paper
would benefit from an overview early on as to how typical battery pack cost breaks down. By
far and large, the main component of pack cost is battery active material cost. Cost
projections should focus on the impact of this - the biggest slice of the pie.
The impact of form factor is not given much attention. The assumption is made that form
factor will not make much of a difference at high volume. It would help to see some
calculations backing up this assumption. Show that a cylindrical cell will cost about the
same as a stacked prismatic or indicate the anticipated differences in cost.
C-13
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Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
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Kelty
The model solves iteratively for pack energy or range, varying cell capacity & electrode
thickness & then determines the mass, volume & material requirements to make the car.
These requirements are used to calculate cost. We think that the output from this model
could be much more useful. We'd like to see pack cost over time for each chemistry.
There was no data shown to validate the assumptions that were made in calculating
electrode thickness from ASI measurements for each chemistry. Impedance measurements
change drastically depending on not just electrode thickness, but also chemistry, particle
size, separator thickness, current-collector thickness, choice of electrolyte, and temperature,
etc. This model is making some very big assumptions and it is not clear what error may be
introduced. Does it make sense to use the same assumptions for HEV, PHEV and EV
batteries (for example, current collector thickness)? What error could be introduced? Can
this be quantified? This should be discussed.
It is mentioned as a future work item -the model needs a cooling/heating system and to
capture the effects of temperature.
The model would benefit from increasing the # of user definable inputs, such as SOC
window of operation for an EV (80% is too conservative).
The model attempts to capture the fixed costs for the battery pack, but ends up making
some very simplified assumptions. If this section remains in the model, we suggest that it
involve many user-defined inputs. The model currently does not capture the cost of safety
features such as isolation contactors.
5-year depreciation is commonly used in the battery industry. The study is using 8 year,
which is too long.
Please include instructions for how to turn on iterations for other versions of Excel, including
2007. The pointer about closing all open Excel documents worked for us but was given over
email.
It would be helpful to see $/Wh cell and pack costs in the spreadsheet.
244
Ely
245
246
247
248
Overall the model is very comprehensive in its design and structure. The information
provided in the modeling uses publically recognized inputs but has a wide variation in cost
that may be regionally dependent. All costs are projected for calendar year 2020 and are
based on a high level structure that lacks detail in burden cost (missing energy cost, interest,
machine maintenance, in-directed labor, etc).
Additionally, there are several areas in which the assumptions are very conservative when
compared to what has been achieved in production today. For example: Manufacturing
Yield rate (92%) estimated by ANL is conservative for 2020. Targets from Tier 1 suppliers
have been a minimum of 98%
Additionally, there are several areas in which the assumptions are very conservative when
compared to what has been achieved in production today. For example: Labor Cost - ANL
did not specify an hourly rate of labor but estimated a rate of $1.62 per cell. Production labor
cost is significantly less based on a per cell basis.
Additionally, there are several areas in which the assumptions are very conservative when
compared to what has been achieved in production today. For example: Depreciation Cost
- The assembly line process capacity does not seem realistic and will have a direct impact
of the total cost for the Electrode and Assembly. As a result, the estimate for impact to
burden cost is greater than 1.5 times too high.
Additionally, there are several areas in which the assumptions are very conservative when
compared to what has been achieved in production today. For example: Area Cost - The
building construction cost does not seem realistic and is lower in years amortized for capital
investment and total dollars for building and land.
C-14
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Appendix C. Peer Reviewer Comments on "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles," Sorted by Charge Question
249
250
251
Ely
Additionally, there are several areas in which the assumptions are very conservative when
compared to what has been achieved in production today. For example: SGA and Profit -
ANL estimated 25% of direct labor and variable overhead plus 35% of depreciation for SGA.
ANL also estimated 5% of investment cost for profit. Again, these estimates result in a cost
impact greater than 1 .5 times too high.
Additionally, there are several areas in which the assumptions are very conservative when
compared to what has been achieved in production today. For example: Warranty Cost -
The warranty cost for the pack alone seems too high.
It is expected that by 2020 there will be significant improvements in cost. With the cost
numbers in this report already conservative when compared to what has been achieved in
production today, the cost model may be overstated by the time actual 2020 costs are
realized.
C-15
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Appendix D: Peer Reviewer Comments as Submitted
D-1
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D-1
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Peer review of the report, "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles"
Report by: M. Stanley Whittingham
Date of Report: February 20th 2011
As a reviewer you are to orient your comments toward the six (6) general areas listed below. You are
expected to identify additional topics or depart from these examples as necessary to best apply your
particular set of expertise toward review of the model.
Comments should be sufficiently clear and detailed to allow readers to familiarize 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 ANL makes its report/cost model
and supporting documentation public. EPA will notify the reviewers when this occurs.
Below you will find a template for your comments. You are free 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 you have 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 you have 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(g),epa.gov).
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(1) Assumptions. Please comment on the validity of any assumptions embedded in the model that could
affect projected battery pack price or performance. Please comment on any assumptions that appear to be
unstated and/or implicit.
Assumptions
Reviewer Comment(s)
Proprietary Materials
There is no allowance made for the cost of
using proprietary materials, such as licensing
costs. This may be important in comparing one
material with another. Also see below.
Estimates of Materials costs
In a number of places, it is stated that "it is
estimated that the cost of for example the
separator is $2 per square meter, or the NMP is
x.
These are well known materials that are used in
large quantities and extensively in the industry
today. What are today's costs, and the authors
need to explain how and why the estimated cost
differs from today's costs if they do.
The cost of some of the key components may
not drop dramatically if one material is
sufficiently superior and the manufacturer has
patent protection, for example the separator
(Celgard). See page 29, 1st full paragraph,
where the first full paragraph justifies the cost
because the raw materials are low cost. It
ignores the proprietary technology that must be
included in the cost. Separators are not simple,
they must close down the battery if necessary,
prevent dendrite formation etc. Today's cost
should be clearly listed. We all know that
LiFePO4 is not low cost, even though the raw
materials are low cost.
In Table 4.1 there is no explanation (in the table
or the text), that I could find, for the three
numbers under the TIAX 2010 column. A
footnote under the table on the same page could
easily explain the different numbers to the
reader.
In Table 4.1, why is there not a number for
LCO in the ANL 2010 column? This number
must be well-known and would represent a
good and solid baseline to compare the other
numbers against (and to test the spreadsheet
model against).
On page 28, 3rd line the prices for cobalt and
nickel metal prices are given. The relevant
costs are those of the oxide or other raw
material that will actually be used in the
manufacturing process; the formation of the
metal can be very expensive. So perhaps the
price of the oxide should be substituted here.
On page 30 section 4.2.1.4 "No cost is assumed
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for water" But what about the cost of handling
the contaminated waste water? There are
several companies trying to use dry processing
to eliminate the cost of handling NMP and
water.
Units of capacity
In some sentences, the weight of the material is
in kg and then the capacity is given in mAh/g.
The latter should be changed throughout into
Ah/kg for these large batteries. The numbers
stay the same.
Cell construction and format
The flat plate format chosen (prismatic/pouch
cells) chosen for this study appears to be the
most appropriate. This part of the report
perhaps could be made clearer.
Comparability to competing cell formats
The most likely alternative as used today in
HEV (cars, buses) is the cylindrical 18650 cell,
which are almost certainly more expensive for
large batteries (too many cells with all their
contacts etc). Larger cylindrical cells are likely
to have more severe thermal management
issues. So the flat plate prismatic cells chosen
are best choice.
Cooling and thermal management requirements
Thermal management is inadequately covered.
As described, the battery pack will have one cm
of insulation around it and be air-cooled. How
does the battery get cooled in the summer when
it is operating? I do not believe that air cooling
is realistic (or is there a refrigerator built in for
cooling the air). The battery pack will need
liquid cooling (or heating in extreme
environments) to maintain a lifetime listed as
10 years. (I realize that the Nissan Leaf only
has air cooling, but is that realistic)
My recollection is that Lew Gaines (from
Exxon Enterprises in the 1970s) found that
thermal management was the most challenging
aspect of large batteries (paper published in
Intersociety Energy Conversion Conference ?)
Electrode volumetric change
I did not see this item discussed in the report;
but I do not view it as a major concern for the
materials considered. The electrodes must be
kept under compression to maintain capacity on
cycling. As the anode contracts the cathode will
expand.
The one exception is the use of LTO as the
anode. This is a zero expansion material so that
the volume changes in the cathode cannot be
compensated by the anode change.
Limiting parameters affecting cell dimensions or
performance (for example, allowable A-hr capacity per
cell, maximum electrode thickness, etc)
These are all well described, but then hand-
waived away by "successful cell manufacturers
will engineer ways to overcome these
-------
challenges to increase energy density and lower
cost". This gives no guidance to the user of the
excel model.
Warranty costs and profit
For a new product the warranty cost
assumptions of 1% failure per year appear too
low. The costs assumed appear to be those
purely due to replacing the battery, not
including other issues such as liability
insurance.
The ROI appears too low at 5%.
Scrap rates and associated costs
The % scrap rate appears reasonable
No value is assigned to the scrap, although by
2020, if the market is indeed there, there should
be a thriving recycling business that would take
the scrap away.
Recycling value
The value of the recycled battery is not
discussed, even though it is presumed by other
ANL reports that eventually most of the lithium
(and presumably any expensive other elements)
would come from recycled batteries.
There is also talk about using "spent" EV
batteries for utility/alternative energy load
leveling/smoothing. Surely this would reduce
the effective life-time cost of a battery.
Safety and manufacturability
An issue with all batteries is protection in the
case of crashes. This report does not really
address that issue. Is it the intent that the one
cm insulation will also serve as a crash
protector? Such protection costs money, and
needs to be included.
Anticipated industry design trends, and similar factors
PHEV types and drive train
Table 3.1 addresses only one class of PHEV
battery, whereas today's scenario goes all the
way from the planned Toyota Prius, with 3
batteries (one power and two energy) each
essentially the same size as in todays HEV
Prius with a dual drivetrain (1C and electric)
and an all-electric range around 8-10 miles to
the GM Volt with around a 15 kWh battery, an
electric generator and an all-electric drive-train
and a range of around 40 miles. So the
assumptions made for PHEV may not be
optimum or even correct, [the comment about
increasing levels of electrification is incorrect;
the Volt PHEV is all electric drive, the HEV
buses are all electric drive with around all
kWh lithium-ion battery - more than 2 million
total miles, so building up reliability
-------
experience]
Unanticipated Breakthroughs
It is almost impossible to anticipate a
significant cost breakthrough, as occurred when
the Chinese decided that the common MCMB
carbon used as the anode was too expensive
and they replaced it with a much lower cost
graphitic carbon. MCMB is no longer
manufactured.
-------
(2) 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. Please comment on any
caveats or limitations that these inputs and parameters entail with respect to use of the results as the basis
for estimating the manufacturing cost or performance of lithium-ion battery packs.
Example Assumptions
Reviewer Comment(s)
Embedded or default values chosen by the authors (for
example, those that represent default material costs,
material percentages, preferred dimensions,
experimentally measured values, etc)
These seemed adequate, and I found that I
could change them and they had an effect on
the resulting cost, but not nearly as much as I
would have expected. For example switch the
capacity of LFP from the default value of 155
to 50 Ah/kg had less than a 20% effect. Can
this be right?
The adequacy of user-specifiable parameters and their
allowable ranges (for example, those that specify
performance requirements, or those that relate to cell
chemistries or cell/module/pack configuration
possibilities)
I found no difference in the battery cost
whether the operating hours per day were 10
hours, 24 hours or 48 hours. Surely
depreciation should cause some effect, and the
spreadsheet should be set-up so that no value
over 24 hours can be input.
-------
(3) Cost methodology. Please comment on the validity and applicability of the methodologies used in
estimating battery manufacturing costs. Please comment on any apparent unstated or implicit
assumptions and related caveats or limitations.
Example Assumptions
Reviewer Comment(s)
Dollar Values
On page 25, it is stated that "All dollar values
are brought back to 2010 with allowance for
inflation". What does that mean? Why not use
2010 dollars in the first place and let the user
include a term for inflation, and build into the
model.
As mentioned by this reviewer elsewhere,
processing improvements that would
potentially reduce costs are likely to come with
licensing fees.
General scaling methods on manufacturing and material
costs
I am somewhat confused by the numbers in
Table 4.8 and the cursory description on pages
46 and 48. As the text reads the cost of the
double capacity goes up, but surely what the
model user/consumer wants to know what is the
cost per kWh or per mile driven. Then does not
the cost go down when the capacity is
increased? The writing is confusing. I
understand that if you want more power, then it
is going to cost more, but if you want more
energy per cell then the cost of the cell per kWh
goes down. This part should be rewritten to
emphasize what is of interest to the end-user: it
will cost you $279/kWh for a 8.7 kWh battery
and only $206/kWh for a 17.1 kWh battery
with the same number of plates?
Using the argument in the two lines above, I
assume the model methodology allows for
increasing the current collector thickness as the
plate size increases so that the resistive losses
do not increase. How easy is it to manipulate
and optimize the plate size.
On page 63, the effect of manipulating the
active material thickness is described so that the
energy stored can be increased by thickening
the electrodes and therefore reducing the area
of the current collectors and separators needed.
Effect of production level on manufacturing and material
costs
Several examples are given of the methodology
are given and appear reasonable.
On page 28, it is argued that the manufacturing
cost will decrease with increased knowledge
form larger scales of production. This is related
to a discussion of LFP. However, a recent
litigation has shown that a lower cost method
for production is well patented (Valence vs
Phostech), and those who need to produce
and/or sell in the US are going to have to pay
-------
licensing fees. [LFP does not require a reducing
atmosphere and a carbon coating step - it can
be done in one stop by the carbothermal
process of Valence using low cost ferric raw
materials].
Method of accounting for warranty costs and profit
Accounting for liability insurance
It is not clear that a method was used for
warranty costs and profit.
Profit is fixed at 5% of total investment costs.
This seems too low for a risky investment. An
ROI closer to 10% would be more reasonable.
The cost methodology for warranty costs is not
too sound. Where did the writers come up with
an annual failure rate of 1% (page 46)? What is
it today for the much simpler HEV cell in the
Prius or in the Honda (where I gather there may
be an early failure problem). No lithium battery
has been used in the proposed duty cycle for
anywhere close to 10 years. Justification for
this assumption should be made.
Insurance is mentioned in a couple of places,
but it seems to be associated with the
manufacturing plant. What is the need for
liability insurance in the case of an injury
related incident of the finished product when in
use?
Effect of demand on raw material costs
This is fine as described: keep away from low
availability materials, where the battery market
is a prime user of the material, such as cobalt.
The report also mentions the high cost of
nickel.
As noted in the report, iron and manganese are
fine.
A bigger issue than the battery for electric
vehicles is probably the rare earth metals
needed in the electric motors. This naturally is
not a part of this report, but the user of the
model needs to be aware that other items than
the battery may be cost controlling.
Depreciation
No real justification for model used for
depreciation - appears to be pulled out of the
air. Probably too low at 12.5%; this value
assumes an 8-year life. For a new and probably
changing technology a shorter depreciation
time is needed at least for the first 5-10 years.
Research and development
R&D comes in two forms, support for the
manufacturing operation (quality control etc),
as well as developing new products, that is to
remain state-of-the-art. It is not clear which is
intended here.
As mentioned in this review elsewhere, the cost
of licensing technology has not been included.
-------
No one outfit is going to have complete
"ownership" of the materials and design. This
is not built into the methodology.
Seems fine, but I wonder how the model
handles for example 4.3.4 Calendering, which
has 1 person per shift. No person is going to
work continuously without a break. How are
these breaks covered whne the process in
presumably continuous. This is perhaps asking
is there flexibility built into the cost
methodology.
The methodology here is probably OK, as you
would do in-house for several reasons: lower
cost, security of supply, proprietary steps.
For each of the above reasons, the cost is
presumed to be lower than purchasing outside,
so methodology and numbers probably OK.
Baseline plant design and scaling
In-house vs purchasing outside (page 25 bottom)
-------
(4) Performance methodology. Please comment on the validity and applicability of the methodologies
used in calculating the power and energy performance of the designed battery. Please comment on any
apparent unstated or implicit assumptions (e.g., regarding ambient temperatures or other factors that
may affect battery performance) and on any related caveats or limitations.
Example Assumptions
Reviewer Comment(s)
How the physical properties and dimensions of cell
components are calculated from the inputs
The battery design model seems OK
The only are I have concern with is how the
effective tap density of the materials is
incorporated into the model. It appears to be
through the void volume.
How power, energy capacity, resistances, currents, are
calculated
These, like voltage at maximum power, seem
very reasonable.
As noted under (1), some generic statements
like "PHEV cells should be much larger than
HEV cells and thus a cell thickness of 10 mm is
assumed" are almost certainly not entirely
correct if Toyota's Prius model is to be
believed.
10
-------
(5) Completeness. Please comment on whether the model adequately identifies the cost components of
battery pack manufacturing.
Example Assumptions
Physical components of the cells and assembled packs
Support circuitry such as for cell charge control and
balancing
Manufacturing steps
Raw materials and labor
Energy inputs and consumables used in manufacture
Capital equipment
Research and development costs for battery design,
development, and production implementation
Battery control system hardware and software
Reviewer Comment(s)
Yes
Yes
Yes
Yes, but see earlier comments about situation
where only one person ahs been assigned to the
task (what happens in breaks)
Consumables discussed, but impact of cleaning
resulting waste streams did not appear to be
covered.
Energy input (aka utility costs) were not
specifically covered, except as in "Variable
Overhead" in Table 4.7 and these are assumed
to be 60% of the direct labor costs. This is
probably not ideal, as the more automated the
plant the lower the labor costs and the higher
the utility costs. Building the plant in a low
humidity climate, such as Tucson, might result
in lower utility costs than in humid Michigan
because of the extensive dry-rooms that must
be used.
Yes
As noted elsewhere, the whole are of licensing
fees has been neglected, even though lithium
batteries are the subject of many expensive
litigations these days.
Yes
11
-------
(6) Recommendations. Please comment on the overall adequacy of the model for predicting future
battery prices, and on any improvements that might reasonably be adopted by the authors to improve the
model. Please note that the authors intend the model to be open to the community and transparent in the
assumptions made and the methods of calculation. 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 Clearly the spreadsheet needs to be made user-friendly, yet not allow for the non-expert
to make unrealistic inputs and assumptions.
a. For example daily operating time should not be allowed to exceed 24 hours
b. To be user-friendly one should be able to just select the system of interest, and not
have to cut and paste it in the System Selection screen.
c. There is a heading issue with the cost input screen. When switching from NCA to
LFP, the cathode heading does not change to LFP but the numbers do.
d. The description for users needs to be generalized. Page 49 - There is no
"Options" under the "Tools" drop-down menu on the Mac excel 2011; it can be
found under the main Excel drop down menu (by going to Preferences , then to
calculation).
2 The weakness of any model is that a major scientific/technological breakthrough might
transform the playing field.
3 Keep the wording simple, for example what kind of dollars are being used. Stick to 2010
dollars and let the user consider inflation.
4 The model needs to include better thermal management. Long-lived batteries will almost
certainly need liquid cooling or heating in certain climates in winter.
12
-------
Peer review of the report, "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles"
Report by: Kurt Kelty
Date of Report: Feb. 17, 2011
As a reviewer you are to orient your comments toward the six (6) general areas listed below. You are
expected to identify additional topics or depart from these examples as necessary to best apply your
particular set of expertise toward review of the model.
Comments should be sufficiently clear and detailed to allow readers to familiarize 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 ANL makes its report/cost model
and supporting documentation public. EPA will notify the reviewers when this occurs.
Below you will find a template for your comments. You are free 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 you have 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 you have 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(g),epa.gov).
-------
(1) Assumptions. Please comment on the validity of any assumptions embedded in the model that could
affect projected battery pack price or performance. Please comment on any assumptions that appear to be
unstated and/or implicit.
Example Assumptions
Cell construction and format
Comparability to competing cell formats
Cooling and thermal management requirements
Electrode volumetric change
Limiting parameters affecting cell dimensions or
performance (for example, allowable A-hr capacity per
cell, maximum electrode thickness, etc)
Warranty costs and profit
Scrap rates
Safety and manufacturability
Anticipated industry design trends, and similar factors
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
Other form factors could be considered.
The cell size is arbitrarily limited.
This needs to improve for EV.
Temperature effects should be considered.
This is not considered.
These are not validated in the paper and seem
arbitrary.
Where are the safety features in the battery
pack? CID?
See additional document
-------
(2) 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. Please comment on any
caveats or limitations that these inputs and parameters entail with respect to use of the results as the basis
for estimating the manufacturing cost or performance of lithium-ion battery packs.
Example Assumptions
Embedded or default values chosen by the authors (for
example, those that represent default material costs,
material percentages, preferred dimensions,
experimentally measured values, etc)
The adequacy of user-specifiable parameters and their
allowable ranges (for example, those that specify
performance requirements, or those that relate to cell
chemistries or cell/module/pack configuration
possibilities)
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
Active material cost projections would be
helpful.
Dimensions for cells should be user defined &
not specified by the model.
What values were measured experimentally?
There is no validation data in the report. The
key relationship used to design the battery is an
estimation for the relationship between
impedance and electrode thickness.
Presumably these measurements were made for
a few different electrodes & are now applied to
all electrodes. Where is the data to show that
this is a reasonable assumption?
More parameters should be user specifiable.
There are a lot of limitations currently on what
can be changed.
-------
(3) Cost methodology. Please comment on the validity and applicability of the methodologies used in
estimating battery manufacturing costs. Please comment on any apparent unstated or implicit
assumptions and related caveats or limitations.
Example Assumptions
General scaling methods on manufacturing and material
costs
Effect of production level on manufacturing and material
costs
Method of accounting for warranty costs and profit
Effect of demand on raw material costs
Depreciation
Research and development
Baseline plant design and scaling
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
5 -year depreciation is more appropriate.
(4) Performance methodology. Please comment on the validity and applicability of the methodologies
used in calculating the power and energy performance of the designed battery. Please comment on any
apparent unstated or implicit assumptions (e.g., regarding ambient temperatures or other factors that
may affect battery performance) and on any related caveats or limitations.
Example Assumptions
How the physical properties and dimensions of cell
components are calculated from the inputs
How power, energy capacity, resistances, currents, are
calculated
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
See above comment regarding lack of
validation data for ASI assumptions.
.
.
-------
(5) Completeness. Please comment on whether the model adequately identifies the cost components of
battery pack manufacturing.
Example Assumptions
Physical components of the cells and assembled packs
Support circuitry such as for cell charge control and
balancing
Manufacturing steps
Raw materials and labor
Energy inputs and consumables used in manufacture
Capital equipment
Research and development costs for battery design,
development, and production implementation
Battery control system hardware and software
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
CID?
See above comment regarding projecting future
costs for active materials.
This is lacking in completeness. Critical safety
features are not included (isolation contactors,
etc.). The argument could be made however,
that these costs are an insignificant cost of the
total battery pack - the active materials being
the key cost driver. This then leads to the
argument that the model should be much more
focused on the costs of these active materials.
(6) Recommendations. Please comment on the overall adequacy of the model for predicting future
battery prices, and on any improvements that might reasonably be adopted by the authors to improve the
model. Please note that the authors intend the model to be open to the community and transparent in the
assumptions made and the methods of calculation. Therefore recommendations for clearly defined
improvements that would utilize publicly available information would be preferred over those that would
make use of proprietary information.
See additional document.
-------
Review of "Modeling the Performance and Cost of Lithium-Ion Batteries for Electric-Drive Vehicles"
Kurt Kelty
Tesla Motors
2/22/11
Comment #1:
We simulated a few EV packs and the price is lower than anticipated. This may be due in part to the
extremely thick electrodes that the model predicted. The model should limit electrode thickness to a
user defined value, we suggest less than 200 micron.
Comment #2:
Please summarize somewhere clearly in the report how the model accounts for the cost in 2020. It
appears that current costs are input, and the spreadsheet does not appear to be adjusting anything
except the plant scale.
Comment #3:
User-defined inputs are currently:
1. Battery power
2. # of cells & modules
3. Target voltage at max power
4. Battery pack energy or vehicle electric range & efficiency
We think that this model would be improved with this input also (or in place of #1):
1. A metric for acceleration such as the time it takes to accelerate from 0-60 mph at a specified
temperature.
Comment #4
Metal pricing is ignored. This model claims to be forecasting pack cost in 2020 but does not appear to
be accounting for changes in the cost of active materials over time. This paper would benefit from an
overview early on as to how typical battery pack cost breaks down. By far and large, the main
component of pack cost is battery active material cost. Cost projections should focus on the impact of
this - the biggest slice of the pie.
-------
Comment #5
The impact of form factor is not given much attention. The assumption is made that form factor will not
make much of a difference at high volume. It would help to see some calculations backing up this
assumption. Show that a cylindrical cell will cost about the same as a stacked prismatic or indicate the
anticipated differences in cost.
Comment #6
The model solves iteratively for pack energy or range, varying cell capacity & electrode thickness & then
determines the mass, volume & material requirements to make the car. These requirements are used
to calculate cost. We think that the output from this model could be much more useful. We'd like to
see pack cost over time for each chemistry.
There was no data shown to validate the assumptions that were made in calculating electrode thickness
from ASI measurements for each chemistry. Impedance measurements change drastically depending on
not just electrode thickness, but also chemistry, particle size, separator thickness, current-collector
thickness, choice of electrolyte, and temperature, etc. This model is making some very big assumptions
and it is not clear what error may be introduced. Does it make sense to use the same assumptions for
HEV, PHEV and EV batteries (for example, current collector thickness)? What error could be introduced?
Can this be quantified? This should be discussed.
Comment #7
It is mentioned as a future work item - the model needs a cooling/heating system and to capture the
effects of temperature.
Comment #8
The model would benefit from increasing the # of user definable inputs, such as SOC window of
operation for an EV (80% is too conservative).
Comment #9
The model attempts to capture the fixed costs for the battery pack, but ends up making some very
simplified assumptions. If this section remains in the model, we suggest that it involve many user-
defined inputs. The model currently does not capture the cost of safety features such as isolation
contactors.
Comment #10
5-year depreciation is commonly used in the battery industry. The study is using 8 year, which is too
long.
-------
Comment #11
Please include instructions for how to turn on iterations for other versions of Excel, including 2007. The
pointer about closing all open Excel documents worked for us but was given over email.
Comment #12
It would be helpful to see $/Wh cell and pack costs in the spreadsheet.
-------
Peer review of the report, "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles"
Report by: Erin O'Driscoll
Date of Report:
As a reviewer you are to orient your comments toward the six (6) general areas listed below. You are
expected to identify additional topics or depart from these examples as necessary to best apply your
particular set of expertise toward review of the model.
Comments should be sufficiently clear and detailed to allow readers to familiarize 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 ANL makes its report/cost model
and supporting documentation public. EPA will notify the reviewers when this occurs.
Below you will find a template for your comments. You are free 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 you have 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 you have 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(g),epa.gov).
-------
(1) Assumptions. Please comment on the validity of any assumptions embedded in the model that could
affect projected battery pack price or performance. Please comment on any assumptions that appear to be
unstated and/or implicit.
Example Assumptions
Reviewer Comment(s)
Cell construction and format
It is ambiguous if the cell is pouch or can in
early sections (drawing is misleading). Later it
become clear.
Construction and format are within norms, but
many folks at winding with individual
electrodes, not using the back and forth folding
method.
Comparability to competing cell formats
Cooling and thermal management requirements
Air cooling is often inadequate for EV packs
today. It could be that pack in 2020 can
achieve good performance with air cooling
alone, but this assumption should be spelled out
more clearly
Electrode volumetric change
Assumption of zero volumetric change is
optimistics 10% over full SOC range is more
reasonable.
Limiting parameters affecting cell dimensions or
performance (for example, allowable A-hr capacity per
cell, maximum electrode thickness, etc)
Numbers are within standards today. I would
assume by 2020 there would be higher capacity
materials that would give higher energy
densities in smaller sizes.
Warranty costs and profit
I would expect warranty assumptions to be
somehow related to performance like cycle life
or calendar life. This is especially concerning
in air cooled pack. I think an assumption
related to cooling system and life would make
more sense but would be challenging to build
into this model now.
Scrap rates
Looks reasonable.
Safety and manufacturability
Safe handling of inorganic metal powder is not
addressed well at all here. EPA guidelines for
handle materials with Ni an Co are much
different than Fe and hence one would expect
different cost structure to handle the materials
in the process. Section 4.3.2 does not address
moving powder through the process and
-------
cleaning up safely
Handling of large quantities of electrolyte
without contamination is also not handled well.
What size container is expected and how is the
material kept clean and dry at this scale?
I believe that by 2020 there will be some non-
slurry coating manufacturing approaches on the
market. In this case the solid electrode would
be directly deposited on current collector -
difficult to model now but I believe this will be
validated by then
Anticipated industry design trends, and similar factors
Additional reviewer comments
Additional reviewer comments
-------
(2) 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. Please comment on any
caveats or limitations that these inputs and parameters entail with respect to use of the results as the basis
for estimating the manufacturing cost or performance of lithium-ion battery packs.
Example Assumptions
Embedded or default values chosen by the authors (for
example, those that represent default material costs,
material percentages, preferred dimensions,
experimentally measured values, etc)
The adequacy of user-specifiable parameters and their
allowable ranges (for example, those that specify
performance requirements, or those that relate to cell
chemistries or cell/module/pack configuration
possibilities)
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
Look in line with my expectations
Difficult to fully assess this in the time period
given.
-------
(3) Cost methodology. Please comment on the validity and applicability of the methodologies used in
estimating battery manufacturing costs. Please comment on any apparent unstated or implicit
assumptions and related caveats or limitations.
Example Assumptions
General scaling methods on manufacturing and material
costs
Effect of production level on manufacturing and material
costs
Method of accounting for warranty costs and profit
Effect of demand on raw material costs
Depreciation
Research and development
Baseline plant design and scaling
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
See previous comment on warranty. Without
correlation to data warranty assumptions are
reasonable. Profit assumptions are reasonable.
Working capital seems low
-------
(4) Performance methodology. Please comment on the validity and applicability of the methodologies
used in calculating the power and energy performance of the designed battery. Please comment on any
apparent unstated or implicit assumptions (e.g., regarding ambient temperatures or other factors that
may affect battery performance) and on any related caveats or limitations.
Example Assumptions
How the physical properties and dimensions of cell
components are calculated from the inputs
How power, energy capacity, resistances, currents, are
calculated
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
In theory looks good
Theory looks sound
In general I have concerns that with the
approach from theory only to full scale cost
model. Any theory should be correlated with
experimental results. I am surprise that no
correlation is made to actual data. While
properties of materials like mA/g are true in
theory many times they are not accurate in
practice. At least one example showing a cell
and/or pack that correlates to this model is
necessary for credibility that this approach is
valid.
-------
(5) Completeness. Please comment on whether the model adequately identifies the cost components of
battery pack manufacturing.
Example Assumptions
Physical components of the cells and assembled packs
Support circuitry such as for cell charge control and
balancing
Manufacturing steps
Raw materials and labor
Energy inputs and consumables used in manufacture
Capital equipment
Research and development costs for battery design,
development, and production implementation
Battery control system hardware and software
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
Active cell balance is new but should be
standard for 2020
Very standard
Labor is low across the board. Labor may be
lower in 2020 but I don't see additional
automation build in to achieve a decrease in
labor.
-------
(6) Recommendations. Please comment on the overall adequacy of the model for predicting future
battery prices, and on any improvements that might reasonably be adopted by the authors to improve the
model. Please note that the authors intend the model to be open to the community and transparent in the
assumptions made and the methods of calculation. Therefore recommendations for clearly defined
improvements that would utilize publicly available information would be preferred over those that would
make use of proprietary information.
Statement in Dr. O'Driscoll's e-mail during submission of comments:
The article is very ambitious in its goals. As I wrote in my comments, I have concerns with the approach
from theory to full scale cost model without correlating theory to data.
-------
Peer review of the report, "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles"
Report by: Joe Adiletta, A123 Systems
Date of Report: 2/28/11
As a reviewer you are to orient your comments toward the six (6) general areas listed below. You are
expected to identify additional topics or depart from these examples as necessary to best apply your
particular set of expertise toward review of the model.
Comments should be sufficiently clear and detailed to allow readers to familiarize 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 ANL makes its report/cost model
and supporting documentation public. EPA will notify the reviewers when this occurs.
Below you will find a template for your comments. You are free 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 you have 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 you have 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(g),epa.gov).
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(1) Assumptions. Please comment on the validity of any assumptions embedded in the model that could
affect projected battery pack price or performance. Please comment on any assumptions that appear to be
unstated and/or implicit.
Example Assumptions
Reviewer Comment(s)
Cell construction and format
Opposite-side tabbing structures for energy-
based systems goes against most common cell
formats (canned or pouch), which have same-
side terminals
Specific material assumptions produce a
generally usable view of the market, yet do not
use optimized designs that specific
manufacturers are likely to employ
Thicknesses of substrates might be double-
checked/triangulated
Comparability to competing cell formats
The model assumes an opposite-end tabbed cell
design in pouch form factor. Organizations
such as VDA are employing specifications for
metal-canned prismatic cells as well, which
offer differing price/performance characteristics
Cylindrical cells for HEV are not considered,
nor are wound electrode designs in general
Cooling and thermal management requirements
A wide variety of cooling strategies
necessitates flexibility here, though perhaps
with some built-in functionality/choice around
air vs liquid cooling and/or active versus
passive
Electrode volumetric change
Limiting parameters affecting cell dimensions or
performance (for example, allowable A-hr capacity per
cell, maximum electrode thickness, etc)
Assuming that all chemistries have a similar
usable energy window (within 5% of one
another) is not valid in practice. This is true for
both PHEV and EV. A larger disparity
between oxides and phosphates exists.
There will definitely be a max electrode
thickness based on the specific chemistry
involved. More pointedly, there will be a max
thickness based on the specific cell TYPE that
is being developed: microHEV, HEV, PHEV or
EV
Warranty costs and profit
I think that it would make more sense to target
a before-tax profit and structure the model
around target margin. Predicting and/or
modeling the going corporate tax rate would
likely be difficult in and of itself
Profit rate looks a bit lower than expected over
the long-term
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Scrap rates
Safety and manufacturability
Are scrap rates inclusive of end of line testing?
NMP recycling number seems high
Certainly the addition of certain components to
ensure safety must be accounted for. For
example, the oxide-based chemistries often use
ceramic coatings on the separator or anode to
compensate for the inferior abuse tolerance of
that chemistry. The cost of this must be
included in the cell cost.
I think that a 300um, thick electrode coating is
somewhat aggressive to expect performance out
of the design
Anticipated industry design trends, and similar factors
The industry seems to be attempting to move
towards a more standardized form factor -
VDA specifications, as well as SAE proposals
From a cost perspective, you'll likely have to
assume some take-off in overall volumes.
There is some sensitivity to where this will all
play out, but it will have a profound effect on
materials costs for specific manufacturers.
Thus, constructing the model to be based on
number of vehicles produced makes sense.
Additional reviewer comments
I mention this below, so you'll see it twice, but
the way the cells are designed given the
thickness of electrodes and number of layers in
many ways doesn't follow conventional design
strategy. For instance, in the base case sent
around (PHEV done by mileage), the thickness
of the electrodes varies, which it wouldn't in
practice, leading to higher overall current
collector costs in smaller capacity/range
systems. In fact, it would work the other way:
You would settle on a single electrode design
for the cell-type (HEV, PHEV, EV) and then
vary the number of layers based on that design
to accommodate different ranges.
Additional reviewer comments
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(2) 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. Please comment on any
caveats or limitations that these inputs and parameters entail with respect to use of the results as the basis
for estimating the manufacturing cost or performance of lithium-ion battery packs.
Example Assumptions
Reviewer Comment(s)
Embedded or default values chosen by the authors (for
example, those that represent default material costs,
material percentages, preferred dimensions,
experimentally measured values, etc)
Electrode design specifications are often unique
to individual manufacturers. The existing
values might be adjusted based on other
publicly available information
Materials costs inputs do not necessarily match
with going rates in volume production
The assumption that all negatives will
necessarily use a water-based binder system
should be questioned, especially given the
range of cell-types being investigated - micro-
HEV through EV
The adequacy of user-specifiable parameters and their
allowable ranges (for example, those that specify
performance requirements, or those that relate to cell
chemistries or cell/module/pack configuration
possibilities)
For micro-hev and HEV, it would make sense
to specify power required, rather than the
choices currently available: Capacity, Energy
or Range. This is especially true if 2/4 of the
options are HEV related (micro and full)
I assume that some of the user inputs are
considered in the model for future use? For
instance, ASI seems to be calculated but not
necessarily applied, as do entries like
temperature rise, etc.
I understand as reviewers we are supposed to
focus on the quantitative aspects of the model;
however, structuring the model for use by
someone not well versed in specifics of
chemistry would be useful. For instance, it's
not quite clear exactly what all of the inputs and
outputs are. There are clearly sheets that
contain foundational information but might not
be used by someone doing top-level analysis.
Additional reviewer comments - cell
Any reason to not consider 2p configurations?
Are you assuming that by 2020 all cells will be
optimally sized for the application?
You assume that manufacturing costs scale
independently of cell design, which is not
entirely appropriate. For instance, the cost of
forming a cell may be linear to the number of
cell layers, but the depreciation cost on a per
cell basis of the stacking equipment will not be,
given that your cell designs do not appear to
scale number of layers linearly with capacity
Additional reviewer comments - pack
Looking at today's vastly different pack
structures/constructions, it would make sense to
account for some variation there. Two
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examples: (1) I did not see a liquid versus air
cooling entry point; (2) Some packs use
aluminum cooling plates as separators, others
use only passive-type cooling with no structural
support
Have government subsidies on capex purchases
been factored in here as well?
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(3) Cost methodology. Please comment on the validity and applicability of the methodologies used in
estimating battery manufacturing costs. Please comment on any apparent unstated or implicit
assumptions and related caveats or limitations.
Example Assumptions
Reviewer Comment(s)
General scaling methods on manufacturing and material
costs
I would only comment that at a certain volume,
significant changes to manufacturing process
will be required, which will bring associated
reductions in cost. This model seems based on
today's methodologies, however applied to
2020, which may not be realistic
The material cost structure (BOM) as outlined
is not indicative of TODAY'S pricing, which
would imply significantly higher costs than
what we would expect to see in 2020
Effect of production level on manufacturing and material
costs
There is going to be a significant delta in
materials costs based on expected production
volume. This should be able to be added, even
if in vague terms via percent cost downs based
on specific manufacturing thresholds
Coating facilities run at speeds entirely
dependent on the chemistry and cell design,
thus drastically altering the amortization of
costs to the cell. This augmentation might be
considered
Method of accounting for warranty costs and profit
Typically we'd talk about warranty as a % of
cost, which I assume is what "added to price"
means, rather than a % of final price
Effect of demand on raw material costs
This does NOT seem to be accounted for. The
effect is real, quantifiable and quite different
for each battery manufacturer depending on
volume and relationship
Especially out in 2020 and beyond, some
reasonable assumptions must be made based on
today's high volume cost rates. It does not
appear that this was taken into account. At the
very least a single input for % decrease based
on volume might be added
Depreciation
Have you accounted for government subsidies
in the acquisition of capital equipment?
8 years on manufacturing equipment seems a
bit long
Research and development
Typically we'd talk about R&D as a % of
revenue rather than of depreciation
Baseline plant design and scaling
Initial plant design looks reasonable. I think
you should consider scalability based on
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volume assumptions. At some point, volumes
could become large enough that a transition to
new manufacturing strategies would make
sense in order to continue down the cost curve.
Scaling would be done incrementally based on
capacity ramp-ups. To that extent, the model
seems to function linearly with respect to
invested capital, whereas that's not the "true"
effect, where 100s of millions are invested for a
fixed capacity which may or may not be fully
utilized, and thus cost affected.
Additional reviewer comments
Quick point of presentation. Given that the
model will likely be reviewed by OEMs as well
as small startups and suppliers, it would be
beneficial to break out your cost analysis into
Cell and non-cell components. Some OEs will
be just buying cells and will likely be interested
in your analysis, thus lumping all labor, OH
and SGA into single buckets may not be the
most appropriate strategy.
Additional reviewer comments
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(4) Performance methodology. Please comment on the validity and applicability of the methodologies
used in calculating the power and energy performance of the designed battery. Please comment on any
apparent unstated or implicit assumptions (e.g., regarding ambient temperatures or other factors that
may affect battery performance) and on any related caveats or limitations.
Example Assumptions
Reviewer Comment(s)
How the physical properties and dimensions of cell
components are calculated from the inputs
It seems that the cell thickness and number of
layers are oddly calculated. In the standard
lOmi PHEV case, you end up with a 16um
cathode - obviously unrealistic, which then
required 64 layers? I think an alternate
approach would be to target a thickness based
on the type of cell desired, and subsequently
vary the number of layers to achieve differing
mileage/capacity packs
As with thicknesses, densities are variable
based on chemistry employed and desired cell
type-HEVvsEV
You would not necessarily constrain the
thickness of the cell based on the cell type, for
instance 10mm for PHEV. In non-standard
designs (those outside of a footprint standard
like VDA), you might float the thickness to
achieve a given capacity once you have a
footprint in mind.
How power, energy capacity, resistances, currents, are
calculated
I'm curious as to why the power was a user
input rather than calculated from the ASI,
which seemed to be painstakingly calculated.
When comparing chemistry to chemistry, the
delivered power based on the cell design is
important
Your limiting C-rate is not going to be constant,
it will vary based on cell design and chemistry,
which is also based on the application you
would be designing the cell for: micro-HEV,
HEV, PHEV, EV
Additional reviewer comments
Additional reviewer comments
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(5) Completeness. Please comment on whether the model adequately identifies the cost components of
battery pack manufacturing.
Example Assumptions
Reviewer Comment(s)
Physical components of the cells and assembled packs
Cost of terminal assemblies seems low
No cost accounted for tape in cell (albeit small
cost)
Support circuitry such as for cell charge control and
balancing
Manufacturing steps
There are certainly inspection steps that require
personnel and equipment not included in the
process steps
Raw materials and labor
Energy inputs and consumables used in manufacture
Capital equipment
Research and development costs for battery design,
development, and production implementation
Battery control system hardware and software
Additional reviewer comments
It would be nice to have an overall summary
sheet that compared packs of different
chemistries side by side
Augmenting the model with the capability to
size a system based on desired capacity/energy
rather than dealing with system sizes as
prescribed by the model
The targeted user should be considered when
structuring the model's inputs/outputs such that
someone not completely versed in battery
chemistry/manufacturing structure might be
able to use the tool
Additional reviewer comments
From a general completeness standpoint, I
would say that the model has MOST aspects
well covered. The real issue is with
generalizing battery manufacturing. Every
manufacturer deals with a specific chemistry,
with specific designs, with specific
manufacturing processes, subsidies, etc. This
makes this type of information extremely
difficult to not only publicly disclose, but also
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to model with reliable and useful results. Being
on the outside of the industry looking in is a
difficult position to be in relative to modeling
each of these parameters such that a lay-person
might understand the key issues that a specific
manufacturer has to tackle.
10
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(6) Recommendations. Please comment on the overall adequacy of the model for predicting future
battery prices, and on any improvements that might reasonably be adopted by the authors to improve the
model. Please note that the authors intend the model to be open to the community and transparent in the
assumptions made and the methods of calculation. Therefore recommendations for clearly defined
improvements that would utilize publicly available information would be preferred over those that would
make use of proprietary information.
11
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Peer review of the report, "Modeling the Cost and Performance of Lithium-Ion Batteries for
Electric-Drive Vehicles"
Report by: Michael Ely
Date of Report: Feb 28, 2011
As a reviewer you are to orient your comments toward the six (6) general areas listed below. You are
expected to identify additional topics or depart from these examples as necessary to best apply your
particular set of expertise toward review of the model.
Comments should be sufficiently clear and detailed to allow readers to familiarize 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 ANL makes its report/cost model
and supporting documentation public. EPA will notify the reviewers when this occurs.
Below you will find a template for your comments. You are free 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 you have 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 you have 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(giepa.gov).
-------
(1) Assumptions. Please comment on the validity of any assumptions embedded in the model that could
affect projected battery pack price or performance. Please comment on any assumptions that appear to be
unstated and/or implicit.
Example Assumptions
Cell construction and format
Comparability to competing cell formats
Cooling and thermal management requirements
Electrode volumetric change
Limiting parameters affecting cell dimensions or
performance (for example, allowable A-hr capacity per
cell, maximum electrode thickness, etc)
Warranty costs and profit
Scrap rates
Safety and manufacturability
Anticipated industry design trends, and similar factors
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
Seems reasonable and appropriate
Seems reasonable and appropriate
Does not appropriately recognize the trade offs
of life and thermal effects.
Much further model refinement would be
needed to improve the models accuracy.
See cooling and thermal management
requirements
Scraps rates do not represent benchmark
practices . . . should be re-evaluated.
In general most of the cost models do not seem
aggressive enough for 2020 forecasted total
costs.
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(2) 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. Please comment on any
caveats or limitations that these inputs and parameters entail with respect to use of the results as the basis
for estimating the manufacturing cost or performance of lithium-ion battery packs.
Example Assumptions
Embedded or default values chosen by the authors (for
example, those that represent default material costs,
material percentages, preferred dimensions,
experimentally measured values, etc)
The adequacy of user-specifiable parameters and their
allowable ranges (for example, those that specify
performance requirements, or those that relate to cell
chemistries or cell/module/pack configuration
possibilities)
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
Seems appropriate for this study
Seems appropriate for this study
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(3) Cost methodology. Please comment on the validity and applicability of the methodologies used in
estimating battery manufacturing costs. Please comment on any apparent unstated or implicit
assumptions and related caveats or limitations.
Example Assumptions
General scaling methods on manufacturing and material
costs
Effect of production level on manufacturing and material
costs
Method of accounting for warranty costs and profit
Effect of demand on raw material costs
Depreciation
Research and development
Baseline plant design and scaling
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
Raw material scaling costs are reasonable for
this study
Warranty cost model seems to be appropriate
for this study
SG&A and profit seem to be very high
compared to current market and will not
improve to these levels with current over
capacity projects in the free trade markets
Demand assumptions do not show an obvious
strong influence of material cost and seems
reasonable
Model shows an 8 year amortization which is
slightly higher than current norms in the
industry
No comment. Too variable in this fast pace
development area
20year amortization of capital investment is
much lower than actual practice in Asia supply
base
Model for building cost does not seem realistic,
unless model assumes continuous government
incentives, which is not realistic in this
timeframe.
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(4) Performance methodology. Please comment on the validity and applicability of the methodologies
used in calculating the power and energy performance of the designed battery. Please comment on any
apparent unstated or implicit assumptions (e.g., regarding ambient temperatures or other factors that
may affect battery performance) and on any related caveats or limitations.
Example Assumptions
How the physical properties and dimensions of cell
components are calculated from the inputs
How power, energy capacity, resistances, currents, are
calculated
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
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(5) Completeness. Please comment on whether the model adequately identifies the cost components of
battery pack manufacturing.
Example Assumptions
Physical components of the cells and assembled packs
Support circuitry such as for cell charge control and
balancing
Manufacturing steps
Raw materials and labor
Energy inputs and consumables used in manufacture
Capital equipment
Research and development costs for battery design,
development, and production implementation
Battery control system hardware and software
Additional reviewer comments
Additional reviewer comments
Reviewer Comment(s)
Seem appropriate
Model assumptions simplify the circuitry to
represent a state of the art battery management
system
Labor rates are appropriate only for US
This model significantly underestimates energy
input cost. Unrealistic as presented
Very much underestimate capital investment
required for cell manufacturing with state of the
cell technologies
Unable to comment
Seems appropriate based on state of the art
design
Model seems to have a very high level of cost
structure with lack of details in burden, interest,
maintenance, and indirect labor.
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(6) Recommendations. Please comment on the overall adequacy of the model for predicting future
battery prices, and on any improvements that might reasonably be adopted by the authors to improve the
model. Please note that the authors intend the model to be open to the community and transparent in the
assumptions made and the methods of calculation. Therefore recommendations for clearly defined
improvements that would utilize publicly available information would be preferred over those that would
make use of proprietary information.
Overall the model is very comprehensive in its design and structure. The information provided
in the modeling uses publically recognized inputs but has a wide variation in cost that may be
regionally dependent. All costs are projected for calendar year 2020 and are based on a high
level structure that lacks detail in burden cost (missing energy cost, interest, machine
maintenance, in-directed labor, etc). Additionally, there are several areas in which the
assumptions are very conservative when compared to what has been achieved in production
today. For example:
Manufacturing Yield rate (92%) estimated by ANL is conservative for 2020. Targets
from Tier 1 suppliers have been a minimum of 98%.
Labor Cost- ANL did not specify an hourly rate of labor but estimated a rate of $1.62
per cell. Production labor cost is significantly less based on a per cell basis.
Depreciation Cost - The assembly line process capacity does not seem realistic and will
have a direct impact of the total cost for the Electrode and Assembly. As a result, the
estimate for impact to burden cost is greater than 1.5 times too high.
Area Cost - The building construction cost does not seem realistic and is lower in years
amortized for capital investment and total dollars for building and land.
SGA and Profit - ANL estimated 25% of direct labor and variable overhead plus 35% of
depreciation for SGA. ANL also estimated 5% of investment cost for profit. Again,
these estimates result in a cost impact greater than 1.5 times too high.
Warranty Cost - The warranty cost for the pack alone seems too high.
It is expected that by 2020 there will be significant improvements in cost. With the cost numbers
in this report already conservative when compared to what has been achieved in production
today, the cost model may be overstated by the time actual 2020 costs are realized.
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