1

Memo 

To: Docket EPA-HQ-OAR-2010-0799

From: Joseph McDonald, U.S. EPA-OTAQ-ASD 

CC: Ed Nam, U.S. EPA-OTAQ-ASD 

Date: Tuesday, November 29, 2011 

Re: Peer Review Report for the ANL BatPaC Model 

The attached document entitled “Peer Review of the Draft Report - Modeling the Cost and 

Performance of Lithium-Ion Batteries for Electric-Drive Vehicles” documents the independent peer 

review of the BatPaC model conducted by ICF International. 
Peer Review of the Draft Report 

“Modeling the Cost and Performance of Lithium-Ion 

Batteries for Electric-Drive Vehicles” 

Revised Final Report 

March 31, 2011 

Prepared by 

ICF International 

9300 Lee Highway 

Fairfax, VA 

and 

620 Folsom Street, Suite 200 

San Francisco, CA

 
This report was prepared by ICF International for the U.S. Environmental Protection Agency 

(EPA), Office of Transportation and Air Quality under EPA Contract No. EP-C-06-094, Work 

Assignment 4-05, at the direction of EPA Work Assignment Manager Cheryl Caffrey.
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

iii March 31, 2011 
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page

iv March 31, 2011 
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. 

 

1 March 31, 2011 
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 

2 March 31, 2011 
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 Bly, 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 

S. 

Whittingham, 

Binghampton 

University 

K. Kelty, 

Tesla Motors 

E. O'Driscoll, 

Dow Kokam 

J. Adiletta, 

A123 Systems 

M. Bly, 

General 

Motors 

Auto 

Packaging 9 9

Battery 

Chemistry 

9 9 9 

Battery Mass 

Production 9 9 

Commodities/ 

Raw Materials 9 9 9

3 March 31, 2011 
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. Bly, who performed the review gratis. Mr. Bly 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. 

4 March 31, 2011 
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 

5 March 31, 2011 
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. 

Bly 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. 

6 March 31, 2011 
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 waterbased binder system, especially given the range of cell-types being investigated – micro-HEV 

through EV. In addition, he noted that a 300um 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, 

7 March 31, 2011 
8 March 31, 2011 

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. Bly 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. 
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. Bly 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. Bly 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 

9 March 31, 2011 
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. Bly 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. Bly 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. Bly 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. Bly 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. Bly 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 
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. Bly 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. 

Bly 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. Bly 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. Bly 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 
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. Bly 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. Bly 

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 
13 March 31, 2011 

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. Bly noted that the labor cost assumptions were 

appropriate only for the United States. 
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 
A-3 

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 Blaine at ICF International 

(SBlaine@icfi.com or 703-225-2471). If a reviewer has any questions about the EPA peer 

review process itself, please contact Ms. Ruth Schenk in EPA’s Quality Office, National Vehicle 

and Fuel Emissions Laboratory by phone (734-214-4017) or through e-mail 

(schenk.ruth@epa.gov). 
B-1 

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 Bly, General Motors 

 
B-2 

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page
1

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, SchlumbergerDoll 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)
2

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
3

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, I 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.
4

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), John Ngala (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 Schoonmaker‡; Adam Skoczylas‡; 

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 Kam‡ (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; ‡ 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 Héctor D. Abruña, “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 

LixNiyMnyCo1-2yO2 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). 
5

11. Y. Song, P. Y. Zavalij, M. S. Whittingham: ε-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-yMnyCo0.1O2 (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 MMo4O13·2H2O (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 ammoniumcopper-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.
Bio:

Kurt Kelty

________________________________________________________________________

Director, 

Battery Technology

Tesla Motors

3500 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.
DOW RESTRICTED - For internal use only

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. 
Erin O’Driscoll p2 of 2

DOW RESTRICTED - For internal use only

• 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 CO2 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
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. Bly

General Motors Executive Director, Group Global Functional Leader

Global Electrical Systems, Hybrids, Electric Vehicles, Batteries, Infotainment & OnStar Engineering

Micky Bly 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, Bly 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, Bly 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. Bly’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.” 

Bly 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, Bly 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, Bly 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.

Bly 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. Bly 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

1 Whittingham 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.

2 O’Driscoll No comments

3 Kelty No comments

4 Adiletta No comments

207 Bly No comments

5 Whittingham 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.

6 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.

7 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.

8 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.

9 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).

10 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.

11 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.

12 O’Driscoll No comments

13 Kelty No comments

14 Adiletta No comments

208 Bly No comments

15 Whittingham 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.

16 O’Driscoll No comments

17 Kelty No comments

18 Adiletta No comments

209 Bly No comments

Question 1: Assumptions - (a) Propriety materials

Question 1: Assumptions - (b) Estimates of materials cost

Question 1: Assumptions - (c) Units of capacity

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

19 Whittingham 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.

20 O’Driscoll It is ambiguous if the cell is pouch or can in early sections (drawing is misleading). Later it 

become clear.

21 Construction and format are within norms, but many folks at winding with individual 

electrodes, not using the back and forth folding method.

22 Kelty Other form factors could be considered.

23 The cell size is arbitrarily limited.

24 Adiletta Opposite-side tabbing structures for energy-based systems goes against most common cell 

formats (canned or pouch), which have same-side terminals.

25 Specific material assumptions produce a generally usable view of the market, yet do not use 

optimized designs that specific manufacturers are likely to employ.

26 Thicknesses of substrates might be double-checked/triangulated.

210 Bly Seems reasonable and appropriate

27 Whittingham 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

28 O’Driscoll No comments

29 Kelty No comments

30 Adiletta 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.

31 Cylindrical cells for HEV are not considered, nor are wound electrode designs in general.

211 Bly Seems reasonable and appropriate

32 Whittingham 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)

33 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 ?)

34 O’Driscoll 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.

35 Kelty Cooling and thermal management requirements: This needs to improve for EV.

36 Cooling and thermal management requirements: Temperature effects should be 

considered.

37 Adiletta 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.

212 Bly Does not appropriately recognize the trade offs of life and thermal effects.

213 Much further model refinement would be needed to improve the models accuracy

Question 1: Assumptions - (f) Cooling and thermal management requirements

Question 1: Assumptions - (d) Cell construction and format

Question 1: Assumptions - (e) Comparability to competing cell formats

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

38 Whittingham 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.

39 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. 

40 O’Driscoll Assumption of zero volumetric change is optimistics 10% over full SOC range is more 

reasonable.

41 Kelty This is not considered.

42 Adiletta No comments

214 Bly No comments

43 Whittingham 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.

44 O’Driscoll 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. 

45 Kelty These are not validated in the paper and seem arbitrary.

46 Adiletta 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.

47 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.

215 Bly No comments

48 Whittingham 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.

49 The ROI appears too low at 5%

50 O’Driscoll 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.

51 Kelty No comments

52 Adiletta 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.

53 Profit rate looks a bit lower than expected over the long-term.

216 Bly See cooling and thermal management requirements

54 Whittingham The % scrap rate appears reasonable

55 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.

56 O’Driscoll Looks reasonable.

57 Kelty No comments

58 Adiletta Are scrap rates inclusive of end of line testing?

59 NMP recycling number seems high.

Question 1: Assumptions - (g) Electrode volumetric change

Question 1: Assumptions - (h) Limiting parameters affecting cell dimensions or performance (for 

example, allowable A-hr capacity per cell, maximum electrode thickness, etc.)

Question 1: Assumptions - (i) Warranty costs and profit

Question 1: Assumptions - (j) Scrap rates and associated costs

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.

60 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.

61 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.

62 Whittingham 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.

63 O’Driscoll 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.

64 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?

65 Kelty Where are the safety features in the battery pack? CID?

66 No comments

67 Adiletta 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.

68 I think that a 300um, thick electrode coating is somewhat aggressive to expect performance 

out of the design.

218 Bly No comments

69 Wittingham No comments

70 O’Driscoll 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.

71 Adiletta The industry seems to be attempting to move towards a more standardized form factor – 

VDA specifications, as well as SAE proposals.

72 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.

219 Bly No comments

Question 1: Assumptions - (k) Recycling value

Question 1: Assumptions - (l) Safety and manufacturability

Question 1: Assumptions - (m) Anticipated industry design trends, and similar factors

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

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 

(IC 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 a 11 kWh lithium-ion battery – more 

than 2 million total miles, so building up reliability experience]

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.

75 Adiletta 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.

220 Bly In general most of the cost models do not seem aggressive enough for 2020 forecasted total 

costs

76 Whittingham 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?

77 O’Driscoll Embedded or default values chosen by the authors: Look in line with my expectations.

78 Kelty Active material cost projections would be helpful.

79 Dimensions for cells should be user defined & not specified by the model.

80 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?

81 Adiletta Electrode design specifications are often unique to individual manufacturers. The existing 

values might be adjusted based on other publicly available information.

82 Materials costs inputs do not necessarily match with going rates in volume production.

83 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.

221 Bly Seems appropriate for this study

Question 1: Assumptions - (n) PHEV types and drive train

Question 1: Assumptions - (o) Unanticipated breakthroughs

Question 1: Assumptions - (p) Additional reviewer comments

Question 2: Inputs and Parameters - (a) Embedded or default values chosen by the authors (for 

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

84 Whittingham 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.

85 O’Driscoll The adequacy of user-specifiable parameters and their allowable ranges: Difficult to fully 

assess this in the time period given.

86 Kelty More parameters should be user specifiable. There are a lot of limitations currently on what 

can be changed.

87 Adiletta 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).

88 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.

89 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.

222 Bly Seems appropriate for this study

90 Adiletta Any reason to not consider 2p configurations? Are you assuming that by 2020 all cells will 

be optimally sized for the application?

91 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.

92 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.

93 Have government subsidies on capex purchases been factored in here as well?

94 Whittingham 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.

95 As mentioned by this reviewer elsewhere, processing improvements that would potentially 

reduce costs are likely to come with licensing fees.

96 O’Driscoll No comments

97 Adiletta No comments

223 Bly No comments

Question 2: Inputs and Parameters - (b) The adequacy of user-specifiable parameters and their 

Question 2: Inputs and Parameters - (c) Additional reviewer comments - cell

Question 2: Inputs and Parameters - (c) Additional reviewer comments - pack

Question 3: Cost Methodology - (a) Dollar values

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

98 Whittingham 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?

99 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. 

100 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.

101 O’Driscoll No comments

102 Adiletta 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.

103 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.

224 Bly Raw material scaling costs are reasonable for this study

104 Whittingham Effect of production level on manufacturing and material costs: Several examples are given 

of the methodology are given and appear reasonable.

105 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].

106 O’Driscoll See previous comment on warranty. Without correlation to data warranty assumptions are 

reasonable. Profit assumptions are reasonable.

107 Adiletta 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.

108 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.

225 Bly No comments

Question 3: Cost Methodology - (b) General scaling methods on manufacturing and material costs

Question 3: Cost Methodology - (c) Effect of production level on manufacturing and material costs

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Electric‐Drive Vehicles," Sorted by Charge Question

109 Whittingham It is not clear that a method was used for warranty costs and profit.

110 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.

111 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.

112 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?

113 O’Driscoll No comments

114 Adiletta 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.

226 Bly Warranty cost model seems to be appropriate for this study

227 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

115 Whittingham 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.

116 As noted in the report, iron and manganese are fine.

117 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.

118 O’Driscoll No comments

119 Adiletta 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.

120 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.

228 Bly Demand assumptions do not show an obvious strong influence of material cost and seems 

reasonable

121 Whittingham 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.

122 O’Driscoll No comments

123 Kelty 5-year depreciation is more appropriate.

124 Adiletta Have you accounted for government subsidies in the acquisition of capital equipment?

125 8 years on manufacturing equipment seems a bit long.

229 Bly Model shows an 8 year amortization which is slightly higher than current norms in the 

industry

Question 3: Cost Methodology - (d) Method of accounting for warranty costs and profit accounting for 

Question 3: Cost Methodology - (e) Effect of demand on raw material costs

Question 3: Cost Methodology - (f) Depreciation

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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

126 Whittingham 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.

127 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.

128 O’Driscoll No comments

129 Adiletta Typically we’d talk about R&D as a % of revenue rather than of depreciation.

230 Bly No comment. Too variable in this fast pace development area

130 Whittingham Seems fine, but I wonder how the model handles for example 4.3.4 Callendering, 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.

131 O’Driscoll Working capital seems low.

132 Adiletta 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.

133 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.

231 Bly 20 year amortization of capital investment is much lower than actual practice in Asia supply 

base

232 Model for building cost does not seem realistic, unless model assumes continuous 

government incentives, which is not realistic in this timeframe.

134 Whittingham The methodology here is probably OK, as you would do in-house for several reasons: lower 

cost, security of supply, proprietary steps.

135 For each of the above reasons, the cost is presumed to be lower than purchasing outside, 

so methodology and numbers probably OK.

136 Adiletta No comments

Question 3: Cost Methodology - (g) Research and development

Question 3: Cost Methodology - (h) Baseline plant design and scaling

Question 3: Cost Methodology - (i) In-house vs purchasing outside (page 25 bottom)

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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

137 Whittingham The battery design model seems OK

138 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.

139 O’Driscoll Theory looks sound.

140 Kelty See above comment regarding lack of validation data for ASI assumptions

141 Adiletta 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.

142 As with thicknesses, densities are variable based on chemistry employed and desired cell 

type – HEV vs EV.

143 Adiletta 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.

233 Bly No comments

144 Whittingham These, like voltage at maximum power, seem very reasonable

145 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.

146 O’Driscoll Theory looks sound.

147 Kelty No comments

148 Adiletta 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.

149 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: microHEV, HEV, PHEV, EV.

234 Bly No 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.

152 Whittingham Yes [complete]

153 O’Driscoll No comments

154 Kelty CID?

155 Adiletta Physical components of the cells and assembled packs: Cost of terminal assemblies seems 

low.

156 Physical components of the cells and assembled packs: No cost accounted for tape in cell 

(albeit small cost).

235 Bly Seem appropriate

Question 4: Performance Methodology - (a) How the physical properties and dimensions of cell 

Question 4: Performance Methodology - (b) How power, energy capacity, resistances, and currents 

Question 4: Performance Methodology - (c) Additional reviewer comments

Question 5: Completeness - (a) Physical components of the cells and assembled packs

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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

157 Whittingham Yes [complete]

158 O’Driscoll Active cell balance is new but should be standard for 2020.

159 Kelty No comments

160 Adiletta No comments

236 Bly Model assumptions simplify the circuitry to represent a state of the art battery management 

system

161 Whittingham Yes [complete]

162 O’Driscoll Very standard.

163 Kelty No comments

164 Adiletta There are certainly inspection steps that require personnel and equipment not included in 

the process steps.

237 Bly No comments

165 Whittingham Yes, but see earlier comments about situation where only one person ahs been assigned to 

the task (what happens in breaks)

166 O’Driscoll 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.

167 Kelty See above comment regarding projecting future costs for active materials.

168 Adiletta No comments

238 Bly Labor rates are appropriate only for US

169 Whittingham Consumables discussed, but impact of cleaning resulting waste streams did not appear to 

be covered.

170 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.

171 O’Driscoll No comments

172 Kelty No comments

173 Adiletta No comments

239 Bly This model significantly underestimates energy input cost. Unrealistic as presented

174 Whittingham Yes [complete]

175 O’Driscoll No comments

176 Kelty No comments

177 Adiletta No comments

240 Bly Very much underestimate capital investment required for cell manufacturing with state of the 

cell technologies

Question 5: Completeness - (b) Support circuitry such as for cell charge control and balancing

Question 5: Completeness - (c) Manufacturing steps

Question 5: Completeness - (d) Raw materials and labor

Question 5: Completeness - (e) Energy inputs and consumables used in manufacture

Question 5: Completeness - (f) Capital equipment

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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

178 Whittingham 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.

179 O’Driscoll No comments

180 Kelty No comments

181 Adiletta No comments

241 Bly Unable to comment

182 Whittingham Yes [complete]

183 O’Driscoll No comments

184 Kelty 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.

185 Adiletta No comments

242 Bly Seems appropriate based on state of the art design

186 Adiletta It would be nice to have an overall summary sheet that compared packs of different 

chemistries side by side.

187 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.

188 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.

189 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.

243 Bly Model seems to have a very high level of cost structure with lack of details in burden, 

interest, maintenance, and indirect labor.

Question 5: Completeness - (g) Research and development costs for battery design, development, 

Question 5: Completeness - (h) Battery control system hardware and software

Question 5: Completeness - (i) Additional reviewer comments

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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

190 Whittingham 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).

191 2 The weakness of any model is that a major scientific/technological breakthrough might 

transform the playing field.

192 3 Keep the wording simple, for example what kind of dollars are being used. Stick to 2010 

dollars and let the user consider inflation.

193 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.

194 O’Driscoll 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.

195 Kelty 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. 

196 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.

197 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.

198 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.

199 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.

Question 6: Recommendations - (a) Recommendations

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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

200 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.

201 It is mentioned as a future work item – the model needs a cooling/heating system and to 

capture the effects of temperature.

202 The model would benefit from increasing the # of user definable inputs, such as SOC 

window of operation for an EV (80% is too conservative).

203 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.

204 5-year depreciation is commonly used in the battery industry. The study is using 8 year, 

which is too long.

205 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.

206 It would be helpful to see $/Wh cell and pack costs in the spreadsheet.

244 Bly 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).

245 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%

246 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.

247 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.

248 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.

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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 Bly 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.

250 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.

251 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
 D-1 

Appendix D: Peer Reviewer Comments as Submitted 
 D-1 

blank

page
1

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 Blaine 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@epa.gov).
2

(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 
3

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 handwaived away by “successful cell manufacturers 

will engineer ways to overcome these 
4

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 (IC 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 a 11 

kWh lithium-ion battery – more than 2 million 

total miles, so building up reliability 
5

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. 
6

(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.

•
7

(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 
8

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. 
9

No one outfit is going to have complete 

“ownership” of the materials and design. This 

is not built into the methodology.

Baseline plant design and scaling • Seems fine, but I wonder how the model 

handles for example 4.3.4 Callendering, 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.

In-house vs purchasing outside (page 25 bottom) • 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.
10

(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.
11

(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 • Yes

•

Support circuitry such as for cell charge control and 

balancing

• Yes

•

Manufacturing steps • Yes

•

Raw materials and labor • Yes, but see earlier comments about situation 

where only one person ahs been assigned to the 

task (what happens in breaks)

•

Energy inputs and consumables used in manufacture • 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.

Capital equipment • Yes

•

Research and development costs for battery design, 

development, and production implementation 

• 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.

•

Battery control system hardware and software • Yes

•
12

(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.
1

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 Blaine 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@epa.gov).
2

(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 • Other form factors could be considered.

• The cell size is arbitrarily limited.

Comparability to competing cell formats •

•

Cooling and thermal management requirements • This needs to improve for EV.

• Temperature effects should be considered.

Electrode volumetric change • This is not considered.

•

Limiting parameters affecting cell dimensions or 

performance (for example, allowable A-hr capacity per 

cell, maximum electrode thickness, etc)

• These are not validated in the paper and seem 

arbitrary.

•

Warranty costs and profit •

•

Scrap rates •

•

Safety and manufacturability • Where are the safety features in the battery 

pack? CID?

•

Anticipated industry design trends, and similar factors •

•

Additional reviewer comments • See additional document

•

Additional reviewer comments •

•
3

(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)

• 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?

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)

• More parameters should be user specifiable. 

There are a lot of limitations currently on what 

can be changed.

•

Additional reviewer comments •

•

Additional reviewer comments •

•
4

(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

•

•

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 • 5-year depreciation is more appropriate.

•

Research and development •

•

Baseline plant design and scaling •

•

Additional reviewer comments •

•

Additional reviewer comments •

•

(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

• See above comment regarding lack of 

validation data for ASI assumptions.

•

How power, energy capacity, resistances, currents, are 

calculated

•

•

Additional reviewer comments •

•

Additional reviewer comments •
5

(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 • CID?

•

Support circuitry such as for cell charge control and 

balancing

•

•

Manufacturing steps •

•

Raw materials and labor • See above comment regarding projecting future 

costs for active materials.

•

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 • 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.

•

Additional reviewer comments •

•

Additional reviewer comments •

•

(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 userdefined 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.
1

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 Blaine 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@epa.gov).
2

(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 
3

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?

Anticipated industry design trends, and similar factors • I believe that by 2020 there will be some nonslurry 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

•

Additional reviewer comments •

•

Additional reviewer comments •

•
4

(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)

• Look in line with my expectations

•

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)

• Difficult to fully assess this in the time period 

given.

•

Additional reviewer comments •

•

Additional reviewer comments •

•
5

(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

•

•

Effect of production level on manufacturing and material 

costs

•

•

Method of accounting for warranty costs and profit • See previous comment on warranty. Without 

correlation to data warranty assumptions are 

reasonable. Profit assumptions are reasonable.

•

Effect of demand on raw material costs •

•

Depreciation •

•

Research and development •

•

Baseline plant design and scaling •

•

Additional reviewer comments • Working capital seems low

•

Additional reviewer comments •

•
6

(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

• In theory looks good

•

How power, energy capacity, resistances, currents, are 

calculated

• Theory looks sound

•

Additional reviewer comments • 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.

•

Additional reviewer comments •

•
7

(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 •

•

Support circuitry such as for cell charge control and 

balancing

• Active cell balance is new but should be 

standard for 2020

•

Manufacturing steps • Very standard

•

Raw materials and labor • 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.

•

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 •

•
8

(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.
1

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 Blaine 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@epa.gov).
2

(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 energybased systems goes against most common cell 

formats (canned or pouch), which have sameside 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 doublechecked/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
3

Scrap rates • Are scrap rates inclusive of end of line testing?

• NMP recycling number seems high

Safety and manufacturability • 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 •

•
4

(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 – microHEV 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 
5

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?
6

(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 
7

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 •

•
8

(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 

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.

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 •

•
9

(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 
10

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.
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

Peer review of the report, “Modeling the Cost and Performance of Lithium-Ion Batteries for 

Electric-Drive Vehicles”

Report by: Michael Bly

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 Blaine 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@epa.gov).
2

(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 • Seems reasonable and appropriate

•

Comparability to competing cell formats • Seems reasonable and appropriate

•

Cooling and thermal management requirements • Does not appropriately recognize the trade offs 

of life and thermal effects.

• Much further model refinement would be 

needed to improve the models accuracy.

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 • See cooling and thermal management 

requirements

•

Scrap rates • Scraps rates do not represent benchmark 

practices ... should be re-evaluated.

Safety and manufacturability •

•

Anticipated industry design trends, and similar factors •

•

Additional reviewer comments • In general most of the cost models do not seem 

aggressive enough for 2020 forecasted total 

costs.

Additional reviewer comments •

•
3

(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)

• Seems appropriate for this study

•

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)

• Seems appropriate for this study

•

Additional reviewer comments •

•

Additional reviewer comments •

•
4

(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

• Raw material scaling costs are reasonable for 

this study

•

Effect of production level on manufacturing and material 

costs

•

•

Method of accounting for warranty costs and profit • 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

Effect of demand on raw material costs • Demand assumptions do not show an obvious 

strong influence of material cost and seems 

reasonable

•

Depreciation • Model shows an 8 year amortization which is 

slightly higher than current norms in the 

industry

•

Research and development • No comment. Too variable in this fast pace 

development area

•

Baseline plant design and scaling • 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.

Additional reviewer comments •

•

Additional reviewer comments •

•
5

(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

•

•

How power, energy capacity, resistances, currents, are 

calculated

•

•

Additional reviewer comments •

•

Additional reviewer comments •

•
6

(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 • Seem appropriate

•

Support circuitry such as for cell charge control and 

balancing

• Model assumptions simplify the circuitry to 

represent a state of the art battery management 

system

•

Manufacturing steps •

•

Raw materials and labor • Labor rates are appropriate only for US

•

Energy inputs and consumables used in manufacture • This model significantly underestimates energy 

input cost. Unrealistic as presented

•

Capital equipment • Very much underestimate capital investment 

required for cell manufacturing with state of the 

cell technologies

•

Research and development costs for battery design, 

development, and production implementation 

• Unable to comment

•

Battery control system hardware and software • Seems appropriate based on state of the art 

design

•

Additional reviewer comments • Model seems to have a very high level of cost 

structure with lack of details in burden, interest, 

maintenance, and indirect labor.

•

Additional reviewer comments •

•
7

(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.