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: Barnett 2009 Citation 

The attached document contains a copy of materials presented by Brian Barnett of TIAX LLC at the 

U.S. DOE/EERE 2009 Vehicle Technologies Program Annual Merit Review, May 19, 2009. 
PHEV BAT

COST ASSE

Brian BarnettDavid OferYong YangBookeun OhJane RempelTIAX LLCMay 19, 2009

Chris McCoyTodd RhodesMildred HastbSuresh Sririra

This presentation does not contaproprietary, confidential, or otherrestricted information
ObjectiveTIAX’s objective was to assess cost implications “at a higbattery chemistries being considered for PHEV applicatio

PHEV Battery 

Cost Assessments

Selected

Battery Chemistries

• Insight into the relative benefits of alternative ch• Identification of factors with significant impact o• Identification of areas where more research coul

significant reductions in battery cost

Results:
ApproachWe employed a parametric approach in which TIAX’s cosmany times with different sets of input parameters.

TIAX 

Cost MODEL

INPUTS

Constraints/Assumptions

APPLICATION 

• Battery Chemistries• SOC range• Electrode loadings• Power output• Power input• Fade• Cell format• Nominal battery pack voltage• Energy required (20 mile range)• PHEV annual production

• PHEV battery costs and cost ranges• Factors with significant influence on battery 

OUTPUTS
The input variables defining the “base case” scenarios wand included (1) cathode material, (2) electrode loading, a

4

x 1 x

2

x

• The requested cost modeling factors produced 16 different sce

considered.

– Each scenario based on a state-of-charge (SOC) range of 80

– Other cost factors varied as part of a sensitivity analysis of e

– Costs to be estimated at a production volume correspondin

• Note that it is not clear whether target power and fade levels ca

loadings and over the modeled SOC range for all chemistries.

For a 5.5 kWh-usable Li-ion battery pack for PHEV, a

implications to the battery cost of using the following 

factors and conditions:

Battery Configurations Modeled & Costed

Cathode Material Anode Material Electrode Loading P

Graphite Low (1.5 mAh/cm2) 

High (3 mAh/cm 

2)

NCANCMLiFePO4LiMn2O4
Since Li-ion batteries of the design and size considered ibeen manufactured and tested, several key assumptions agreed with DOE) about the battery performance.• Power Output: Peak power (40 kW for 2 sec., or 20 kW for 100 

battery even at low battery state of charge (SOC). Low temperaturconsidered.

• Power Input: The battery can be recharged at the peak rate (30 

battery is at a high SOC.

• Battery Life: The battery is assumed to be able to achieve the lif

selected scenarios.

– 5.5 kWh usable: Each design scenario to yield 5.5 kWh of usa

discharge) at end of life after accounting for assumed SOC limita

– Nominal Li-ion cell energy: Energy for full discharge at 1C foll– Fade: 

- 0% scenarios provide 5.5kWh of usable energy at end of life w

- 30% scenarios provide 5.5 kWh of usable energy at end of life 

battery size is 9.8 kWh nominal to deliver 5.5 kWh of usable e

– SOC range:

- 10-90 % (i.e., battery size is 6.9 kWh nominal to deliver 5.5 kW

• Format: cylindrical cell

Key Study Parameters / Assumptions for All Chemistries
For cell production, the TIAX cost model yields estimates goods sold (COGS), i.e., manufacturing cost, including ca

TIAX Cost Model for Large Format Cells 

Materials and manufacturing 

cost estimates were based on 

production of cylindrical format 

cells in high volume.
For PHEV battery production, the cost model assumes a integrated manufacturing process from cell fabrication thbattery system.

Cell 

Production

Battery Pack 

Assembly

Battery 

Electronics 

Assembly

Vertically Integrated Manufactur

Materials• Cell • Electronics• Thermal Components• Pack Components

Battery Thermal 

Management 

Assembly

• All supplied materials, e.g., cell materials, packaging components, are trea

include supplier mark-ups.

• No “supplier” mark-up is included on in-process goods (e.g. cells to be ass

TIAX Cost Model for Large Format Batteries
Note: 

The PHEV battery manufacturing cost analysis assumed materials and “current” processing technology in high vo

“Current” Materials“Current” Processing Technologies(500k vehicles/year)

Improved Materials

Existing 

Manufacturing 

Technology

“Current” Materials

Improved 

Manufacturing 

Technology

Improved Materials 

and Manufacturing 

Technology

“Current” Future

“Current” Future Processing Technology

Materials Technology

TIAX Cost Model Assumptions

“Current” materials implies currently available materials used in commercial rech

of which have yet been used in commercial scale production o

“Current” processing technologies implies those adapted from high volume cylin

into portable power applications.

Since yet to ability technoperforuntestVariouwere aperforwithin 
Cell designs are built up from specific electrode propertie

• Materials properties • Electrode loading & formulation• Anode/cathode ratio

Calculate the total area of 

electrode/separator stack-up 

that gives the nominal cell 

energy

Calculate the electrode length 

and the cell diameter

• Jelly roll height• Mandrel diameter • Cell can thickness & he

Calculate weights of all cell 

components and total cell 

weight

Data on 1st cycle efficie

average voltage and ca

different C-rates

Specified

Measured*

Calculated

Calculate the thickness, mass 

and energy of a single 

cathode/anode/

separator stack-up

Calculate the nomina

energy, number of cel

nominal cell ener

• Pack voltage• Available energy• SOC range

Cell Designs
Optimized cell designs will inevitably be determined by crelationships between operational requirements/characteparameters, factors that cannot be integrated into this stu

Chemistry

(cathode, anode,

electrolyte)

Fade

(battery life)

SOC l

Electrode Design

(loading, 

composition)

Operating 

Requirements & 

Characteristics

(rate, duty cycle,

temperature)

Cell Designs
Key model inputs were identified and a likely range of valfor each.

Cathode – LiMn2O4 ($/kg) 12.0 16.0 Cathode – LiFePO4 ($/kg) 15.0 20.0 

Wage Rate ($/hr) 21.0 25.0 

98.0 100.0 

Process Parameters (units)Separator ($/m 1.0 2.5 

2)

Anode ($/kg) 17.0 20.0 Cathode – NCM ($/kg) 40.0 45.0 Cathode – NCA ($/kg) 34.0 40.0 Material Cost Inputs (units)Cell components ($/cell) 2.1 2.5 Electrolyte ($/kg) 18.5 21.5 Cost Factor Low Value Baseli

Input Parameters Baseline Values and Low/High Ranges

“Baseline” values were used for single point projectio

low and high values were used in multi-variable sensit

generate cost probability curves.

Process Yield (%)
Analyses of the sensitivity of battery cost to input paramein order to determine factors with significant impact on b• Single variable sensitivity analyses were carried out using C

analysis software/ tornado chart tool*.

• Single variable sensitivity analysis manipulates one input va

measuring the impact on the output and displays the results chart”

• A tornado chart ranks input parameters in terms of their imp

– Input parameters can be assumptions and/or decision variables– Chart provides a convenient way to determine the relative sensi

an entire set of input parameters.

* Crystal Ball® is a trademark of Decisioneering, Inc., www.decisioneeri

Single Variable Sensitivity Analysis Impact of Inputs on Output
• Multi-variable analysis: all input parameters varied statistically over 

each

• Result of multi-variable analysis: a plot of battery cost vs. probabili

costs)

Multi-variable analysis allowed us to answer the question battery cost of a combination of variations (from baselineparameters?” 

Statistic 

Mean Median Standard Deviation Minimum Maximum TIAX Baseline* 

Multi-variable Sensitivity Analysis

Example:

LiFePO4 / 3.0 Loading / 0% Fade (short electrode, ze

* The forecast value using 

parameters. This foreca

projection o

Battery Cost

Multi-Variable Sensitivity Analysis
To help understand if and how battery cost might be drivwe developed four additional “what if” scenarios to test tvalues of related input parameters. 

Increase coater speed by a factor of 10 from 5 m/mDouble all manufacturing process speedsAll cathode and anode active materials cost $5/kg 

Assumption Variables Baseline Cases 

Labor Rate ($/hr) 25 

Equipment Discount Factor (%) 100% 

NCA Cost ($/kg) $40.00 

NCM Cost ($/kg) $45.00 

“Made in China”

1234

“WHAT IF” Scenarios (applied individually to Base Scenarios)

* Bureau of Labor Statistics, Department of Labor, " International Comparisons of Hourly Comp

published in 2008 ** The Boston Consulting Group white paper, " Made in China: Why Industrial Goods Are Going 

“What If?” Analysis
Cost of cathode active material is a somewhat less imporsystem cost than might have been thought.• Upfront cell design is a critical factor in battery cost.

– Electrode loading (i.e., electrode length) seems to be mo

cathode active material cost, within the ranges evaluated

– Active materials’ influence on cell design has greater imp

does the (cathode) active materials’ cost itself.

• Manufacturing processing speed matters

ResultsPHEV battery configurations modeled in this study result(COGS) ranging from $264/kWh to $710/kWh, or $1452 to usable power.*

* These cost ranges were the output from 

variable sensitivity analy
There is significant overlap in battery costs among the fowith wider variation within each chemistry than between 

Plots of the resulting ranges of battery costs, 

grouped by cathode active material, show 

significant cost range overlap between the 

cathode classes, with battery costs 

“bottoming” just below $300/kWh, and show 

wider variation within each chemistry than 

between chemistries.

Range of modeled costs as identified in the (multivariable) sensitivity analyses; each bar represents one scenario. 

Modeled L

($/kWh 

NCA N

Results

$0

$100$200$300$400$500$600$700$800

Battery System Cost ($/kWh)

Cathode – LiMn2O4 ($/kg)

Cathode – LiFePO4 ($/kg)

Cathode – NCM ($/kg)

Cathode – NCA ($/kg)

12.0 16.0 215.0 20.0 240.0 45.0 534.0 40.0 5

Material Cost Inputs (units)

Cost Factor Low Value Baseline High 

Material Cost Inputs to TIAX Battery Cost Model for Baseline C

Outputs and for Sensitivity Analyses (Single & Multivariable
The projected costs for PHEV batteries in this study confbe expected from consideration of 18650-based Li-ion ba

• 18650 cells are a standardized Li-ion design currently prod

approaching 1 billion cells/year worldwide, using the most processes currently available in the industry.

– This production volume corresponds to about 10GWh/ye

volume in terms of materials and electrode area to yield PHEVs/year.

• Current Li-ion OEM 18650 cell costs are in the $200-$250/

about 60% are the materials costs as supplied to battery mpowders, metal foils, separators, etc.

• 18650 cells are primarily used in battery packs for laptops, 

range from $400/kWh to more than $700/kWh.

Results
Within the PHEV battery scenarios modeled and evaluatematerial cost by itself is not a major factor in driving syst

• As expected qualitatively, higher fade leads to higher battery cost; 

loading (i.e., longer electrode length) leads to higher battery cost.

• Our cost model shows quantitatively the influence of fade and elec

system cost and, by implication, the cost reduction potential of new permit shorter, thicker electrodes.

• The results of an extreme “what if” analysis to test the impact of re

materials by as much as 90% reveals the impact on battery cost to modest.

Results
The “made in China” and “doubling speed of all manufacscenarios resulted in greater battery cost reductions than or “$5/kg active materials” in the NCA-based scenarios.

NCA

For each of these “what if” scenarios, battery cost is (still) ab

Base Scenario (from Table, p. 78)

Representative Example:

Results
Generally, battery system cost is a function of fade level length, i.e., battery cost increases with increasing % fade electrode length. 

0% fade

3.0 mAh/cm2

0% fade

2.25 mAh/cm2

0% fade

1.5 mAh/cm2

30% fade

3.0 mAh/cm2

30% fade

2.25 mAh/cm2

30% fade

1.5 mAh/cm

NCA

0% fade,

Increasing electrode length

30% fade,

Increasing electrode length

Battery cost ranges from a low of about $2000 to a 

(about $364/kWh to about $581/kW

$0

$500

$1,000$1,500$2,000$2,500$3,000$3,500

Cost ($)

Cathode Active Material Cost ($)

Total Battery Cost ($)

Example:

Results
Doubling the speed of all manufacturing processes noticbattery cost in most cases.• Analysis of the modeled battery scenarios reveals that sepa

speed are significant factors in battery system cost.

– Example: Modeled costs for NCA-based PHEV batteries range f

$2000 to a high of about $3200 (about $364/kWh to about $581separator cost alone accounts for more than 25% of that differen

– Single variable sensitivity analyses of modeled costs show that s

coater speed are of equal or greater impact on battery system cmaterial cost.

The ability to employ a wide SOC range contributes signienergy storage costs. • Lower fade and wider SOC range both reduce cost by resu

nominal battery energy and smaller battery size.

– For example, increasing the SOC range from 70% to 80% reduc

12%.

– Materials that support a wide SOC range, therefore, should help 

costs.

Results
For each candidate battery chemistry, the inter-relationshoperational requirements/characteristics and design parathat should be established experimentally.

Chemistry

(cathode, anode,

electrolyte)

Fade

(battery life)

SOC l

Electrode Design

(loading, 

composition)

Operating 

Requirements & 

Characteristics

(rate, duty cycle,

temperature)

Future Work
These results point to specific areas of research with potin battery cost.Future Work

Materials Cell/Electrode M

• Materials that 

support high power, and a wide SOC range

• Materials that 

provide minimal fade, impedance growth and calendar aging

• New chemistry and 

electrode designs permitting shorter, thicker electrodes

• In general, chemistries 

and designs that enable lower overall electrode area per battery and minimize battery size will reduce cost.

• Ide

of teccoun

- 

• Fu

elepro

...while meeting target requirements for power an