ANL-11/XX 

ARGONNE NATIONAL LABORATORY 

9700 S. Cass Ave. 

Argonne, IL 60439 USA 

DRAFT REPORT SUBMITTED TO THE ENVIRONMENTAL PROTECTION 

AGENCY FOR PEER-REVIEW

Modeling the Performance and Cost of Lithium-Ion Batteries for 

Electric-Drive Vehicles 

by 

Paul Nelson, Kevin Gallagher and Ira Bloom 

Electrochemical Energy Storage Theme 

Chemical Sciences and Engineering Division 

January 15, 2011 
ii 

This Page Intentionally Left Blank
iii 

TABLE OF CONTENTS

LIST OF FIGURES ......................................................................................................... vii 

LIST OF TABLES ............................................................................................................ ix 

ABBREVIATIONS ........................................................................................................... x 

LIST OF SYMBOLS ....................................................................................................... xii 

ACKNOWLEDGEMENTS ............................................................................................. xv 

EXECUTIVE SUMMARY ............................................................................................ xvi 

1. Introduction .....................................................................................................................1 

2. Battery and Cell Design Format .....................................................................................2 

 2.1 Cell Design.........................................................................................................3 

 2.2 Module Design ..................................................................................................4 

 2.3 Battery Pack Design ..........................................................................................5 

3. Modeling of Battery Design and Performance ...............................................................6 

 3.1 Criteria for Power, Energy, and Life ................................................................6 

 

 3.2 Voltage at Maximum Power .............................................................................8 

 3.3 Governing Equations ......................................................................................14 

 3.4 Calculation of the ASI ....................................................................................15 

 

 3.4.1 Current Collection Resistance ..........................................................17 

 3.4.2 Potential and Current Distribution ...................................................19 

 

 3.4.3 Determination of Module Terminal Size ..........................................21 

 3.5 Calculation of Battery Dimensions .................................................................21 

 

 3.5.1 Cell Dimensions ...............................................................................22 

 

 3.5.2 Module Dimensions .........................................................................22 
iv 

 3.5.3 Battery Pack Dimensions .................................................................23 

 

 3.6 Additional Considerations ..............................................................................23 

 

 3.6.1 Maximum Electrode Thickness .......................................................23 

 3.6.2 Accounting for Parallel Cell Arrangements .....................................24 

4. Modeling of Battery Pack Manufacturing Cost ............................................................25 

 4.1 Approach .........................................................................................................25 

 4.2 Materials Costs and Purchased Items .............................................................26 

 4.2.1 Battery Specific Materials Cost .......................................................26 

 

 4.2.2 Purchased Items Cost .......................................................................30

 4.3 Baseline Manufacturing Plant .........................................................................31 

 

 4.3.1 Receiving and Shipping ...................................................................32 

 

 4.3.2 Electrode Materials Preparation .......................................................34 

 4.3.3 Electrode Coating .............................................................................34 

 4.3.4 Calendering ......................................................................................35 

 4.3.5 Inter-Process Materials Handling ....................................................35 

 4.3.6 Electrode Slitting .............................................................................36 

 4.3.7 Final Electrode Drying .....................................................................36

 4.3.8 Control Laboratory ...........................................................................36 

 4.3.9 Cell Stacking ....................................................................................37 

 4.3.10 Current Collector Welding .............................................................37 

 4.3.11 Enclosing Cell in Container ...........................................................37 

 4.3.12 Electrolyte Filling and Cell Sealing ...............................................38 

 4.3.13 Dry Room Management .................................................................38 
v 

 4.3.14 Formation Cycling, Final Cell Sealing, etc ....................................38 

 4.3.15 Module and Battery Assembly .......................................................39 

 4.3.16 Rejected Cell and Scrap Recycle ...................................................40 

 4.3.17 Baseline Plant Summary ................................................................41 

 4.4 Adjustment of Costs for Rates ........................................................................41 

 4.5 Plant Investment Costs ....................................................................................43 

 4.6 Unit Costs for Battery Pack ............................................................................44 

 4.6.1 Variable Costs ..................................................................................44 

 

 4.6.2 Fixed Expenses ................................................................................45 

 4.6.3 Profits ...............................................................................................46 

 4.6.4 Battery Pack Warranty Costs ...........................................................46 

 4.7 Summary of Baseline Battery Cost .................................................................46 

5. Description of Spreadsheet Model and Instructions for Use ........................................49 

 5.1 Background .....................................................................................................49 

 5.2 Instructions ......................................................................................................49 

 5.2.1 Enabling Calculation ........................................................................49 

 5.2.2 System Selection Worksheet ............................................................50 

 5.2.3 Battery Design Worksheet ...............................................................50 

 5.2.4 Remaining Worksheets ....................................................................54 

 5.3 Battery Design Format Requirements .............................................................57 

 5.4 Troubleshooting and General Advice .............................................................57 

6. Illustrated Results ..........................................................................................................58 

 6.1 Number of Cells in Series ...............................................................................58 
vi 

 

 6.2 Battery Packs for HEVs...................................................................................58 

 6.3 Battery Packs for EVs .....................................................................................61 

 6.4 Parallel-Connected Cell Groups and Electrode Thickness .............................63 

 6.5 Effects of Manufacturing Scale on the Price of the Pack ...............................64 

7. Future Work ..................................................................................................................67 

 7.1 Thermal Modeling ..........................................................................................67 

 7.2 Optimum Battery Voltage for Minimum Drivetrain Cost ..............................67 

 7.3 Multipurpose Battery Manufacturing Plants ...................................................68 

 7.4 Stand-Alone Graphical User Interface for Model ...........................................68 

References .........................................................................................................................69 
vii 

LIST OF FIGURES

2.1 Prismatic cell and module design for battery packs ............................................................2 

2.2 Cell sandwich inside of prismatic pouch cells ....................................................................3 

2.3 Coated current collector foil for prismatic electrodes .........................................................4 

3.1. Summary flow of the design model ....................................................................................7 

3.2 a) Required change in [V/U] to maintain rated power with increases in internal 

 resistance over the life of the battery. b) Increase in current due to lowered [V/U] .........10 

3.3 Change in heat rejection requirement from increases in resistance for batteries with 

 different designed voltages at maximum power ...............................................................11 

3.4 Efficiencies for batteries designed to achieve maximum power at different fractions of 

 their open-circuit voltage ..................................................................................................13 

3.5 The change in current and potential within the positive and negative foils. The current 

collection design results in a uniform current distribution along the length of the foil ....20 

4.1 Metal ingot cost contribution to the current collector foils over a 20 year period ............30

4.2 Baseline lithium-ion battery manufacturing plant schematic diagram .............................32 

4.3 Breakdown of installed capital equipment costs for the baseline plant ............................43 

4.4 Breakdown of unit costs for baseline battery with total price to OEM of $2428 .............48 

5.1 Iteration must be enabled for the spreadsheet model to function .....................................49 

5.2 The specific cell chemistry for the battery design is selected on the System Selection 

 worksheet ..........................................................................................................................50 

5.3 System Selection worksheet .............................................................................................51 

5.4 Top portion of Battery Design worksheet .........................................................................52 

5.5 Middle portion of Battery Design worksheet ....................................................................53 

5.6 Bottom portion of Battery Design worksheet ...................................................................55 

5.7 Summary of Results worksheet ........................................................................................56 
viii 

6.1 The effect of the number of cells for LMO-Gr, 60-kW, PHEV20 packs with 7.14 kWh 

 total energy (70% useable) ................................................................................................58 

6.2 Cell area-specific impedance (ASI) for various cell chemistries for 25-kW HEV 

 battery packs delivering full power at about 238 A for 2 sec at 80% OCV .....................59 

6.3 Volume, voltage and maximum current for 1.6-kWh lithium-ion battery packs as a 

 function of pack power for packs delivering full power ...................................................60 

6.4 Battery pack price to OEMs at 100,000 packs per year manufacturing rate for 1.6-kWh 

lithium-ion battery packs as a function of pack power .....................................................61 

6.5 Weight and volume of electric vehicle battery packs with LFP, LMO, and NMC 

 electrodes versus graphite designed to deliver 150 kW of power at about 425 A ...........62 

6.6 Battery pack price to OEM for LFP-G, LMC-G and NMC-G battery packs ...................63 

6.7 Battery pack cost as a function of number of parallel cells and for different maximum 

 electrode thicknesses .........................................................................................................64 

6.8 The effects of manufacturing rate on the price calculated by the model for battery 

 packs of various cell chemistries, power capabilities and vehicle types ..........................65 
ix 

LIST OF TABLES 

3.1 Criteria for designing batteries for a specific end-use application ......................................6 

4.1 Details of stated costs for cathodes, anodes, electrolyte, and separator ...........................27 

4.2 Cost equations for purchased items ..................................................................................31 

4.3 Summary table of the baseline plant .................................................................................33 

4.4 Materials yields during electrode and cell fabrication ......................................................40 

4.5 The effect of processing rate (R) on cost for various scale factors ...................................42 

4.6 Battery pack manufacturing investment costs ..................................................................44 

4.7 Unit cost of battery pack ...................................................................................................45 

4.8 Summary of results for cost of baseline battery and that of similar batteries with 

 double the power and double the capacity of the baseline battery ....................................47 
x 

ABBREVIATIONS 

ASI area specific impedance 

BOL beginning of life 

DMC dimethyl carbonate 

EC ethylene carbonate 

EMC ethyl methyl carbonate 

EOL end of life 

EV electric vehicle 

Gr graphite 

GSA General, Sales, and Administration 

HEV hybrid electric vehicle 

HEV-HP high-power assist hybrid electric vehicle 

LCO lithium cobalt oxide 

LFP lithium iron phosphate 

Li lithium 

Li-ion lithium-ion 

LMO lithium manganese spinel 

LMR lithium and manganese rich 

LTO lithium titanate spinel 

microHEV micro or mild power assist hybrid electric vehicle 

NCA lithium nickel cobalt aluminum oxide 

NMC lithium nickel manganese cobalt oxide 

NMP N-Methyl-2-pyrrolidone 
xi 

OCV open-circuit voltage 

OEM original equipment manufacturer 

PE polyethylene 

PEP polyethylene terephthalate 

PHEV plug-in hybrid electric vehicle 

PP polypropylene 

R&D research and development 

SOC state of charge 

USGS United States Geological Survey 
xii 

LIST OF SYMBOLS 

Section 3 and 5 

a ratio of interfacial area to electrode volume, cm-1

Apos area of the positive electrode, cm2

Aterm area of the terminal, cm2

ASIenergy area specific impedance for energy, ohm cm2

ASIpower area specific impedance for power, ohm cm2

C cell capacity, Ah. 

Cp specific heat capacity, J/g K 

E total energy, Wh 

F Faraday constant, 96485.3 C/mol 

Hj

 height of j, cm 

H/W aspect ratio of pouch cell 

io exchange current density related to the interfacial area, A/cm2

I average current density, A/cm2 

Ilim

ionic ionic limiting current density, A/cm2

In local current density, A/cm2

Lj thickness of j, cm 

mj

 mass of j, g 

Nj number of j

P battery power, W 

Pbatt maximum designed battery power, W 

q heating rate, W 
xiii 

Q specific capacity of the electrode, mAh/g 

rC C-rate, h-1 

rC,lim limiting C-rate, h-1

rj radius of j, cm 

R universal gas constant, 8.3144 J/mol K 

Rj resistance of j, ohm 

T temperature, K 

t time, s 

Uocv,P open-circuit voltage at SOC for power, V 

Uocv,E open-circuit voltage at SOC for energy, V 

Vcell cell voltage, V 

v square root of dimensionless exchange current 

[V/U] fraction of the open-circuit voltage 

Wj width of j

Xcomp compression factor 

α constant, ohm cm3

β constant, ohm cm2

εact volume fraction of active material 

Φ1,k metal potential of foil k, V 

ρj density of j, g/cm3

σj conductivity of j, S/cm 
xiv 

Section 4 

C capital cost of an installed equipment for the designed battery, $ 

Co capital cost of an installed equipment for the baseline plant battery, $ 

p power factor 

R designed battery processing rate for specific process step 

Ro baseline plant processing rate for specific process step 
xv 

ACKNOWLEDGEMENTS 

Support from the Vehicle Technologies Program, Hybrid and Electric Systems, initially under 

Tien Duong and now David Howell, at the U.S. Department of Energy, Office of Energy 

Efficiency and Renewable Energy, is gratefully acknowledged. The submitted manuscript has 

been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory 

(“Argonne”). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated 

under contract no. DE-AC02-06CH11357. The U.S. Government retains for itself, and others 

acting on its behalf, a paid-up nonexclusive, irrevocable worldwide license in said article to 

reproduce, prepare derivative works, distribute copies to the public, and perform publicly and 

display publicly, by or on behalf of the Government. We especially thank Danilo Santini of 

Argonne’s Transportation R&D Center for his support and suggestions in carrying out this study. 

Ralph Brodd reviewed our baseline plant and made several suggestions which we have 

incorporated in the present design. Fritz Kalhammer and Haresh Kamath of the Electric Power 

Research Institute have reviewed our work over several years and made suggestions that resulted 

in improvements. The work was done under the direction of Dennis Dees and Gary Henriksen of 

Electrochemical Energy Storage who provided guidance in carrying out the work and preparing 

this manuscript. 
xvi 

EXECUTIVE SUMMARY 

This report details a design and cost model developed at Argonne National Laboratory for 

lithium-ion battery packs used in automotive transportation. The model designs the battery for a 

specified power, energy, and degree of powertrain electrification. The cost of the designed 

battery is then calculated by accounting for every step in the lithium-ion battery manufacturing 

process. The assumed annual production level directly affects each process step. The total cost to 

the original equipment manufacturer calculated by the model includes the materials, 

manufacturing, and warranty costs for a battery produced in the year 2020. At the time this report 

is written, this calculation is the only publically available model that performs a bottom-up 

lithium-ion battery design and cost calculation. 

The purpose of the report is to document the equations and assumptions from which the model 

has been created. A user of the model will be able to recreate the calculations and perhaps more 

importantly, understand the driving forces for the results. Instructions for use and an illustration 

of model results are also presented. Almost every variable in the calculation may be changed by 

the user to represent a system different from the default values pre-entered into the program. 

The model will be openly distributed to the public in the year 2011. Currently, the calculations 

are based in a Microsoft®

 Office Excel spreadsheet. Instructions are provided for use; however, 

the format is admittedly not user-friendly. Future work is proposed to create a more intuitive 

user-interface with tools to prevent inappropriate values from being entered. A version that is 

more user-friendly will allow for wider adoption of the model. 
1 

1. Introduction 

The recent penetration of lithium-ion (Li-ion) batteries into the vehicle market has prompted 

interest in projecting and understanding the costs of this family of chemistries being used to 

electrify the automotive powertrain. The model described here-in is a calculation method that 

was developed at Argonne for estimating the manufacturing cost and performance of Li-ion 

batteries for electric-drive vehicles including hybrid-electrics (HEV), plug-in hybrids (PHEV), 

and pure electrics (EV). To date, a number of cost models of various levels of detail have been 

published in different forms.1-10 Most available cost models for batteries are based on a single 

linear equation dependent on the power and energy required such as $/kWh = a + b*kW. While a 

simplistic relation like this is attractive, it is only approximate and provides little guidance in 

reducing costs. The cost of a battery will change depending upon the materials chemistry, battery 

design, and manufacturing process.11,12 Therefore, it is necessary to account for all three areas 

with a bottom-up cost model. Other bottom-up cost models exist but are not available to the 

general public and have not been explicitly detailed in an open document. The motivation for this 

work is based on a need for a battery cost model that meets the following requirements: 

 1. Open and available to the entire community 

 2. Transparent in the assumptions made and method of calculation 

 3. Capable of designing a battery specifically for the requirements of an application 

 4. Based on a bottom-up calculation approach to account for every cost factor 

The model is the product of long-term research and development at Argonne National 

Laboratory. Over a period of years, Argonne has developed methods to design Li-ion batteries 

for electric-drive vehicles based on modeling with Microsoft®

 Office Excel spreadsheets.11-18

These design models provided all the data needed to estimate the annual materials requirements 

for manufacturing the batteries being designed. This facilitated the next step, which was to 

extend the effort to include modeling of the manufacturing costs of the batteries. In the following 

sections of this document, a model is presented that meets the above criteria and may be used to 

analyze the effect of battery design and materials properties on the cost of the final battery pack. 

Use of the model requires some basic knowledge of battery packs; however, a user does not need 

to be an expert. For instance, the number of cells and thus battery pack voltage must be specified 

by the user. However, default values are available for more specific requirements such as 

experimentally measured values. In this way, a person with reasonable knowledge of batteries 

may be able to conduct cost comparisons and “what if” studies. 

The battery pack design and cost calculated by the model represent projections of a 2020 

production year and a specified level of annual battery production, 10,000-1,000,000. As the goal 

is to predict the future cost of manufacturing batteries, a mature manufacturing process is 

assumed. The model designs a manufacturing plant with the sole purpose of producing the 

battery being modeled. The assumed battery design and manufacturing facility are based on 

common practice today but also assume some problems have been solved to result in a more 

efficient production process and a more energy dense battery. Our proposed solutions do not 

have to be the same methods used in the future by industry. We simply assume the leading 

battery manufacturers, those having successful operations in the year 2020, will reach these ends 

by some means. 
2 

2. Battery and Cell Design Format 

Various cell and battery design concepts are under development at battery manufacturers. The 

exact design of the battery does not have an important effect on the cost for a set cell chemistry 

system; the amounts of electrode materials and the number, capacity and electrode area of the 

cells, are the determining cost factors. The most common cell designs for batteries nearing largescale production are cylindrical wound cells, flat wound cells, and prismatic cells with flat plates. 

Cylindrical cells probably have a slight advantage for the assembly of the electrode-separator 

unit because of the ease of making a cylindrical winding. For the different cell designs, there are 

small differences in the weights of the terminal extensions and the procedures for connecting 

these extensions to the current collector sheets, with a small advantage for flat plate cells. The 

flat-wound and flat-plate cells form a more compact module and have better heat rejection 

capabilities than the cylindrical cells; although, each cell design can be adequately cooled for 

most applications. These small differences would have minor effects on the cost of batteries 

produced in high volume in a mature, automated production plant. We conclude that the cost 

calculations would be relevant for batteries differing considerably from the selected design 

approach. 

To provide a specific design for the calculations, a prismatic cell in a stiff-pouch container and a 

double-seamed module container was selected (Fig. 2.1). For this design, calculation of the 

current collector and terminal resistances are easily done. The electrical performance is near 

optimum in a compact, light-weight configuration. It is unlikely that we have selected the most 

viable design in this short study; there may be serious flaws in some details. However, the 

overall performance and low cost for the selected design will be challenging to match and will 

only be met by the most successful manufacturers, those that will dominate the market. 

Figure 2.1 Prismatic cell and module design for battery packs

Terminal Seal

Polymer Seal of 

Cell Container 

to Terminal 

Ultrasonic Welds

of Terminal to 

Collector Foils

Cell Cross-Section Battery Module

Double-Seamed 

Module Closure

Heat Transfer Surfaces 

on Top and Bottom of 

Container in Contact 

with Cell Edge Seals

Cell Terminal 

Connections

Cell with Stiff, MultiLayer Container

Polymer 

Edge Seal 
3 

2.1 Cell Design 

The prismatic cell of this design embodies individual positive and negative electrodes consisting 

of current collector foils coated with electrode materials on both sides. The current collectors are 

usually solid copper and aluminum foils for the positive and negative electrodes respectively. An 

illustration of a segment of the cell is detailed in Figure 2.2. Each electrode is made up of active 

material particles held together by a polymeric binder. A conductive additive, carbon black 

and/or graphite, is added to the positive electrode and sometimes to the negative electrode. The 

electrodes and separator each have porosity that is filled with the electrolyte solution. During 

discharge, the Li-ions move from the negative electrode particles into the electrolyte, across the 

separator, and then insert into the particles composing the opposite positive electrode. The 

electrons simultaneously leave the cell through the current collection system and then enter 

through the opposite side after doing external work. The materials currently used in Li-ion cells 

are based on an intercalation mechanism. In this process, the Li-ion is inserted into or removed 

from the crystal structure of the active material. The oxidation state of the active material, or 

host, is concurrently changed by gaining or losing an electron. Other electrode materials based 

on conversion reactions or electrodeposition could be implemented into the model if desired. 

separator

negative

electrode

+ – +

Li+

positive

electrode

e

-

separator

negative

electrode

+ – +

Li+

positive

electrode

e

-

Figure 2.2 Cell sandwich inside of prismatic pouch cells. 

The electrodes are efficiently prepared by coating wide sheets of foil (up to 2-meters in width) 

with uncoated strips running the lengths of the foil being coated. The individual electrodes can 

be cut from these sheets with little waste of electrode coating material or foil (Fig. 2.3). The 

separator for these cells can be handled as a single sheet that is folded back and forth as the 

electrodes are inserted. The electrodes are inserted so that all of the positive tabs extend beyond 

the separator sheet in one direction and the negative tabs extend in the opposite direction. The 

design model selects the number of electrodes for a set cell thickness determined by the type of 

cell: HEV, 6 mm; PHEV, 12 mm; EV, 14 mm. The cell terminals are formed from flat stock to 

be almost as wide as the entire cell. They are bent to the shape shown in Fig. 2.1 and 

ultrasonically welded to the current collector tabs. The cell stack is then sealed between the two 

halves of the cell container. The cell housing material is a tri-layer consisting of an outer layer of
4 

polyethylene terephthalate (PEP) for strength, a middle layer of 0.1-mm aluminum for stiffness 

and impermeability to moisture and electrolyte solvent vapors and an inner layer of 

polypropylene (PP) for sealing by heating.19,20 The two halves of the cell container are preshaped to facilitate assembly. The aluminum foil in the cell container material provides stiffness 

and it may be increased in thickness to assist in conducting heat to the module container. 

Figure 2.3 Coated current collector foil for prismatic electrodes 

2.2 Module Design 

The model designs a module casing of 0.5 mm aluminum that is sealed by double seaming, a 

process that is well established and inexpensive because it is automated, rapid, and uses low-cost 

capital equipment. The sealing of the module provides an additional barrier to the loss of 

electrolyte solvent from the cells and the entrance of water vapor. These deleterious transfers 

through the seals of pouch cells may shorten their lives to less than the desired fifteen years.19

The cells are placed on their sides in the module and the terminals of adjacent cells are connected 

either mechanically with small bolts and flat springs to maintain contact or by laser welding. 

Space is provided within the module casing on the left side, as sketched in Fig. 2.1, for an 

electronics package that includes cell monitoring for malfunctions (temperature and voltage) and 

for state-of-charge (SOC) control. The SOC control is activated whenever the battery is at rest 

and it diverts charge from the cells at highest voltage to those at lowest voltage. 

In the model, we assume the module is cooled only by air flowing over the upper and lower 

surfaces of the module. This method of cooling is most practical if the amount of heat generated 

is kept to moderate levels by defining full power as that provided at 80 % or higher fraction of 

the open-circuit voltage. To enhance heat flow from the cells to the cooled walls of the module 

casing, the edge seals, which include two layers of 0.1 mm thick aluminum foil (one from each 

half of the cell container), can be pressed against the walls of the casing by springs shaped as 

hoops. The heat transfer can be further enhanced by increasing the thickness of the aluminum 

Electrode 

Coating

Lines Showing 

Places to Cut for 

Electrodes

Uncoated Area 

for CC Tabs
5 

layer in the cell pouches or by adding an aluminum plate between the cells. The modules can 

also be cooled internally by a dielectric fluid such as a transformer coolant. For that approach, 

the fluid would be brought to the module through metal tubing or be supplied to the battery 

jacket and enter the modules through slots. Corrugated plates inserted between the cells would 

provide flow channels for the cooling fluid. In the current model, only air cooling on the outside 

of the module is provided. Further discussion of thermal issues may be found in Section 7. 

2.3 Battery Pack Design 

The model designs the battery pack in sufficient detail to provide a good estimate of the total 

weight and volume of the pack and the dimensions of the battery jacket so that its cost can be 

estimated. The modules are arranged within the battery jacket either in a single row, with the 

terminals facing the same side of the pack, or in an even number of rows with the terminals in 

one row facing the terminal of an adjacent row. The terminals are laid out on the module so as 

not to interfere with those on the opposite row of modules, thus conserving space in the battery 

pack. The modules in a row are interconnected, negative to positive terminals, by copper 

connectors. The modules casings are compressed together by two steel sheets bound with steel 

straps at the front and back of the battery pack. The compression is necessary to ensure intimate 

contact between the active layers that make up the pouch cells that are tightly fit into the 

modules. The compressive force also serves to add structural support to the module casing. 

The battery jacket consists of a sheet of aluminum on each side of a 10-mm thick layer of ridged, 

light-weight high-efficiency insulation. The thickness of each of the aluminum layers is selected 

by the modeling program to be 1- to 2-mm thick, depending on the total volume of the modules. 

The insulation slows the interaction of the battery with the external environment that cools the 

battery in the winter and heats it in the hot summer weather.14
6 

3 Modeling of Battery Design and Performance 

The design portion of the model calculates the physical properties of a battery based on userdefined performance requirements and minimal experimental data. An illustration of the model is 

shown in Figure 3.1. The user is asked to enter a number of design parameters such as the battery 

power, number of cells and modules, and target voltage at maximum power, etc. In addition, the 

user must enter one of the following three measures of energy: battery pack energy, cell capacity, 

or vehicle electric range. Defining one of these values will determine the value of the other two. 

An iterative procedure then solves for the user defined energy parameter (energy, capacity, or 

range) and remaining battery properties by varying the cell capacity and electrode thickness. The 

result is the dimensions, mass, volume, and materials requirements for the cells, modules, and 

battery pack. 

The model has been designed to allow the user to enter as many customized values as desired. In 

this way, the model allows flexibility in the battery chemistries studies and some of the cell, 

module, and battery design aspects. Hence, the focus of this report is on the method of 

calculation and not the exact values chosen for a specific capacity or cell thickness. However, the 

default cell design parameters as well as experimental data measured at Argonne National 

Laboratory, for a number of different battery chemistries, are available for use within the model. 

There are five governing equations for battery performance that calculate the current density, 

battery energy, electrode area, electrode thickness, and resistance. The voltage at maximum 

power and the area specific impedance (ASI) are two important parameters in the design model 

for calculating the battery performance. Most of the discussion will be spent on these two 

properties. 

3.1 Criteria for Power, Energy, and Life 

In order to fully specify a battery design, the user of the design model must supply criteria for 

power, energy, and life. These criteria will depend on the application for which the battery will 

be used. While the user may change some of the settings as they prefer, we list our suggestions in 

Table 3.1. The battery type is defined by the end-use application. Hybrid electric vehicles 

(HEVs), plug-in hybrid electric vehicles (PHEVs), and electric vehicles (EVs) have increasing 

levels of electrification of the vehicle drivetrain. The model will use Table 3.1 or the user’s 

explicit inputs to size the battery correctly for the chosen application. 

Table 3.1 Criteria for designing batteries for a specific end-use application 

Battery Type microHEV HEV-HP PHEV EV 

SOC for Rated Power, % 50 50 25 25 

Power Duration, sec 2 10 10 10 

SOC Range for Useable Energy, % 40-65 40-65 25-95 15-95 

Cell Thickness, mm 6 6 10 14 
7 

Battery Design Model

Iterative Spreadsheet

Solves for cell capacity 

and designs battery pack 

by varying:

1. Cell area

2. Electrode thickness

3. Internal resistance

Pack Requirements

• power

• energy or range

• number of cells

Cell Chemistry

Measured Properties

• pulse power ASI

• discharge ASI

• mAh/g, g/cm3

• electrode porosity

• SOC window

• physical properties

ASI = area specific impedance

Key Constraints

• max electrode thickness

• target cell potential, V, at 

peak power

• cell/module format

Calculated Battery

Pack Properties

• dimensions

• volume & mass

• specific energy, 

power

• materials required

Figure 3.1 Summary flow of the design model 
8 

The microHEV is a micro or mild-hybrid that provides a moderate power level, ~25 kW, for two 

seconds. This design is best suited for cell chemistries capable of very high power-to-energy 

(P/E) ratios. The HEV-HP is a power-assist hybrid that provides the rated power for a full 10 

second pulse. The power for both HEV applications is rated at 50 % state-of-charge (SOC). The 

energy available for discharge and charging is 25 % of the total energy to ensure long cycle life. 

As the capacity of the HEV cells is typically small, a cell thickness of 6 mm is used. The PHEV 

utilizes a much larger portion of the total energy, 70 %. At the end of discharge, the PHEV 

battery is operated in a charge sustaining mode. Therefore, the power rating for the battery is 

determined at 25 % SOC. PHEV cells should be much larger than HEV cells and thus a cell 

thickness of 10 mm is assumed. Finally, EV batteries use 80 % of their total energy with their 

power rated near the end of discharge. Cell thicknesses are set to 14 mm to accommodate a high 

capacity design. As noted later in the report, selecting a parallel arrangement of cells 

automatically assumes a cell thickness of 6 mm regardless of the end-use application. 

Additionally, the use of negative electrodes operating at potentials high above the lithium metal 

potential may extend the upper end of the available SOC range from 95 to 100 %. The lithium 

titanate spinel, Li4Ti5O12 (LTO), negative electrode is an example of intercalation electrode with 

almost no risk of plating lithium metal during a charge pulse. On this basis, the available energy 

for LTO-based Li-ion chemistries is suggested to be 75 % for PHEVs and 85 % for EVs. 

Accounting for capacity and power fade in the battery requires the user to design the battery with 

the appropriate excess energy and power at the beginning-of-life (BOL). Defining the voltage at 

which maximum power is achieved at BOL is one way to set the allowable power fade over the 

life of the battery. This is discussed in detail in the following section. Capacity or energy fade 

must be accounted for by over-sizing the battery at BOL. If the user has a certain fade 

requirement, then the BOL energy may be increased to meet the end-of-life (EOL) target. The 

design model does not attempt to predict fade rates or even suggest an allowable fade for a 

specific application. It is our view that many aspects of materials chemistry, cell design, and 

battery use directly affect the decay of the battery pack. Hence, we allow the user to make 

accommodations for decay as he or she believes is necessary. 

3.2 Voltage at Maximum Power 

The voltage at which a cell reaches the designed maximum power is one of the most important 

factors in the design of a battery. However, this specification is one of the least discussed aspects 

of battery design. The voltage at maximum power, Vcell, is a measure of the largest polarization 

the cell will undergo during operation at the BOL. This initial value has a direct effect on roundtrip battery efficiency, heat removal requirements, cold-cranking power, and allowable power 

fade. A basic calculation shows the maximum achievable power for a battery at BOL is at 50 % 

of the open-circuit voltage (OCV). Operating at these conditions would result in an inefficient 

battery and require a significant cooling system to reject heat. More importantly, the battery will 

never be able to reach this power level after any increase in impedance occurs. With all certainty, 

the impedance of a battery will rise with time and the power rating of battery will no longer be 

accurate. The remainder of this section presents a discussion for setting the BOL voltage at 

maximum power at no less than 80 % of the open-circuit voltage. Defining the voltage as a 

fraction of the OCV, [V/U], allows for direct calculation of all the necessary battery properties 

(see for example Eq. 3.6 or 3.8 in the section 3.3). 
9 

The allowable increase in battery resistance over the life of the battery is a function of the 

designed voltage for maximum power. In general, designing the battery to achieve maximum 

power at a higher [V/U] allows for larger resistance or impedance increases over the lifetime of 

the battery. Figure 3.2 created from Eq 3.1 displays how the voltage at maximum power will 

change to meet the designed power as the internal resistance of the battery increases. Clearly, 

achieving BOL power at a high fraction of the OCV allows for greater degradation within the 

usable lifetime of a battery. If the minimum voltage is 55 % of the OCV, the allowable increase 

in resistance for batteries designed for BOL max power at 70, 80, and 90 % OCV is 18, 55, and 

175 %. The consequence of achieving the power at lower and lower fractions of the open-circuit 

voltage is that both electric current and heat generation will increase over the lifetime of the 

battery, Figure 3.2b and Figure 3.3. The proper design of a battery will account for the changes 

over the entire lifetime and not just desired behavior at BOL. 

 













































− 











= + − 











1 1 1

2

2

1 1 4 1

2

1

U

V

U

V

R

R

U

V

 (3.1) 

The level of heat production is significantly different at BOL for batteries designed to meet 

maximum power at differing fractions of the open-circuit voltage. We may compare the 

differences in designed [V/U] by assuming the resistive heating (joule heating) is the most 

significant factor in determining the heat generation, Eq. 3.2. We also reasonably assume the ASI 

will not change significantly in the range of current densities and electrode thickness we vary in 

the comparisons. From this point, we can analyze the difference in heat generation from different 

designed [V/U] values, Eq 3.3. 

 

 ( )

j

j

j pos j

R

U

V

U

q A I R

2

2

2

1





























−

= = (3.2) 

 2

1

2

2

2

1

1

2

1

1





























−





























−

=

U

V

R

U

V

R

q

q

 (3.3) 

The ratio of resistances may be found by equating the power for the two cases. Then the 

resistances, and areas if the ASIs are equivalent, are determined solely by the fraction of the 

open-circuit voltage at which they achieve maximum power, Eq 3.4. Then substitution will give 

the ratio of heat production at maximum power for the two cases, Eq. 3.5. A battery that achieves 

maximum power at 80 % of OCV will have a heat production at maximum power that is 2.3 

times higher than one designed at [V/U] = 90 %. A battery producing power at 70 % of the OCV 

will have 3.9 time higher heat generation than at [V/U] = 90 %. 
10 

Figure 3.2 a) Required change in [V/U] to maintain rated power with increases in internal 

resistance over the life of the battery. b) Increase in current due to lowered [V/U]. 

50

55

60

65

70

75

80

85

90

95

0 25 50 75 100 125 150 175 200

 Increase in Resistance, %

Fraction of OCV at Full Power, %

90%

80%

70%

Designed 

BOL [V/U] at 

max Power

0

10

20

30

40

50

60

70

80

0 25 50 75 100 125 150 175 200

Increase in Resistance, %

Increase in Current, %

90%

80%

70%

Designed 

BOL [V/U] at 

max Power
11 

0

50

100

150

200

250

300

350

400

450

500

0 25 50 75 100 125 150 175 200

Increase in Resistance, %

Increase in Heat Generation, %

90%

80%

70%

Designed 

BOL [V/U] at 

max Power

Figure 3.3 Change in heat rejection requirement from increases in resistance for batteries with 

different designed voltages at maximum power. 

 

 





























− 







































− 











= =

2 2

1 1

2 1

1 2

2

1

1

1

U

V

U

V

U

V

U

V

ASI A

ASI A

R

R

power pos

power pos (3.4) 

 





























− 







































− 











=

2 1

1 2

1

2

1

1

U

V

U

V

U

V

U

V

q

q

 (3.5) 
12 

Two straightforward design changes will enable operating a battery at 90 % of OCV compared to 

80 % while maintaining the same power output. First, a second identical battery may be 

connected in parallel to the original battery. This will lower the resistance of the battery pack by 

one half but will also double the energy and cost of the battery. A more realistic approach is to 

reduce the electrode thickness by coating a larger separator area. The capacity of the cell is 

maintained while minimizing increases in cost from a larger separator, current collector and 

packaging area. This approach is feasible as long as the reduced electrode thickness is above the 

increase in ASI, > 20 microns as discussed in detail below. 

The efficiency of a battery defines the heat rejection requirements and may be measured or 

calculated. Measurement of round-trip efficiency of a battery is best performed by using a 

calorimeter to measure the heat given off during the cycling of the battery. The calorimeter 

removes the requirement of knowing the exact SOC of a battery during the entire drive cycle. 

Calculation of the round-trip efficiency of a battery requires a detailed transient battery model 

within a vehicle simulation program to exercise the battery over the many acceleration and 

deceleration periods that occur during a drive cycle. The interesting result is that the same battery 

will have different power ratings depending on what level of round-trip efficiency the user is 

willing to accept. 

Figure 3.4 shows the efficiency of a battery as a function of the designed potential at which the 

battery reaches maximum power. The figure is created using Equations 3.1 and 3.4 above. Each 

line may be considered a different drive cycle, or duty load, for a battery with the same energy 

but different impedance (changing separator area). The straight, solid black line represents the 

efficiency of the battery operated only at maximum power, P/Pmax = 1. In example, a battery 

designed at [V/U] = 0.8 will have 80 % efficiency for a single discharge pulse at maximum 

power. Likewise, a battery designed at 0.9 will be 90 % efficient at maximum power. Batteries 

are normally operated in the area above the line of the maximum power. Therefore, the other 

curves represent the efficiency of discharging a battery at power levels below maximum power 

(typical driving conditions). Consider two batteries each designed for a maximum power of 100 

kW although one achieves this power at a [V/U] = 0.9 and the other at 0.7. If the two batteries 

are discharged at 45 kW, P/Pmax = 0.45, the battery designed at [V/U] = 0.9 will be 6.4 % more 

efficient. This is significantly less than the 20 % efficiency improvement realized when operated 

at maximum power. The efficiency penalty is reduced as the battery operates less and less near 

the designed maximum power. 

 
13 

Figure 3.4 Efficiencies for batteries designed to achieve maximum power at different fractions 

of their open-circuit voltage. Comparative efficiency lines are shown for equivalent power 

demands over a period of battery operation.

50%

60%

70%

80%

90%

100%

0.5 0.6 0.7 0.8 0.9 1

Designed [V/U] at Max Power

Efficiency During Discharge

0.10

0.20

0.30

0.45

0.60

0.80

1.00

P/Pmax
14 

3.3 Governing Equations 

The five coupled, algebraic equations that govern the battery design are presented in this section. 

While these equations are perhaps the most important, many other equations are used to fully 

define the battery mass and volume. These other equations will be specified where necessary in 

the following subsections. 

The user of the model specifies the required maximum power, Pbatt, of the battery. This power is 

translated to a current density, I, in Eq 3.6 using the area of the positive electrode, Apos, the 

number of cells, Ncell, the open-circuit voltage at the SOC for power, Uocv,P, and the fraction of 

the open-circuit voltage at which maximum power is achieved, [V/U]. 

 













=

U

V

A N U

P

I

pos cell ocv P

batt

,

 (3.6) 

The relationship between capacity and battery energy is described by Equation 3.7. Formally, the 

energy of a battery is the product of the capacity and the average voltage at which the energy is 

obtained. The average cell voltage is approximated in Eq. 3.7 by subtracting the polarization 

from discharging the battery at a C/3 rate from the open-circuit voltage at the SOC for energy, 

Uocv,E. The energy for all batteries designed by the design model is calculated at a C/3 rate and 

the average open-circuit voltage at 50 % SOC. The remaining necessary values are the capacity 

of the cell, C, ASI for energy, ASIenergy, number of cells, and area of positive electrode. Either the 

battery energy or capacity may be specified. The energy may alternatively be determined from a 

stated range, fraction of total energy available, and energy usage rate for the vehicle (Wh/mile). 

 















= −

pos

energy

cell ocv E

A

C ASI

E N C U

3

,

 (3.7) 

The area of the positive electrode in Eq. 3.8 is determined largely by the area specific impedance 

for power, ASIpower, and resulting voltage drop. The voltage of cell at max power, Vcell,P, is found 

from the product [V/U]Uocv,P. In general, the area of the cell will increase if the ASI for power 

increases. The areas of the negative electrode and separator are determined from the area of the 

positive electrode. The negative electrode is taken to be 1 mm larger than the positive electrode 

in both height and width to alleviate concerns of lithium plating during charge pulses. The 

separator area is slightly larger than the negative electrode to prevent the electrical shorting of 

the two electrodes. 

 

( ) 



























− 











=

U

V

U

V

N U

ASI P

A

cell ocv P

power batt

pos

1

2

,

 (3.8) 

The positive electrode thickness, Lpos, in Eq. 3.9 is determined from the capacity of the cell, C, 

specific capacity of the electrode, Q, volume fraction of active material, εact, bulk density of the 
15 

active material, ρ, and the positive electrode area. The negative electrode thickness is determined 

by its specific reversible-capacity and the designed excess-capacity to prevent lithium plating 

during charging. We have chosen a ratio of 1.25 negative to positive reversible-capacity (N/P 

ratio) for the default value for the cells with graphite negative electrodes. LTO negative electrode 

based cells are designed at a 1.1 N/P ratio because of the previously mentioned minimal 

possibility of lithium deposition. The maximum allowable electrode thickness is a user defined 

value. The calculation for the electrode area changes when the designed thickness is greater than 

the maximum allowed (Section 3.6.1). 

 

act pos

pos Q A

C

L

ρε

= (3.9) 

Finally, the ASI for power (and for energy to a lesser extent) is calculated using an expression 

that is based on the electrode thicknesses, the current density, and the C-rate. The exact 

expression will be discussed in the next session. The ASI in Eq 3.10 shows the basic 

dependencies with α and β being constant valued parameters. 

 

 

( )

β

α

+

+

=

Lpos

f I

ASI (3.10) 

3.4 Calculation of the ASI 

In most battery design scenarios, the ASI directly determines the electrode thickness to meet a 

specified power-to-energy (P/E) ratio. From this electrode thickness, the area of the electrode is 

set to meet the capacity requirements. Clearly, the ASI plays a significant role in the design of a 

battery and particularly in the case of the P/E ratios required by automotive applications. 

However, the ASI is not an inherent constant of a specific battery chemistry or cell design. The 

measured value of the ASI is a complex combination of resistances within the battery resulting 

from the physical processes occurring at different length and time scales. Consequently, the 

measured value is a function of many factors (state of charge, pulse length, current density, Crate, particle size, transport and kinetic parameters, etc). The calculation used for the ASI in this 

battery design model has been discussed in detail elsewhere.18 The physical meaning of the 

equation will be discussed but those interested in the derivation are directed to the separate 

publication. We note that the ASI described here is slightly different than the one addressed in 

the paper. The thermodynamic component is removed that originated from the change in opencircuit potential with concentration for the intercalation materials. Equation 3.11 contains the 

definition of the ASI used in this document. It1 is a positive valued current density for a 

discharge pulse. It2 is equal to zero as it is during the relaxation period after the pulse. Time 0, t0, 

is the time just before a current pulse begins, time 1, t1, is the time just before the current pulse 

ends, and time 2, t2, is the time long after the current pulse when the cell is at open-circuit and 

the concentration gradients have relaxed. Therefore, this ASI measurement is not troubled by 

accounting for a change in open-circuit voltage with the passage of current. In general, the ASI 

measured with this definition is similar, although smaller, in value to those produced using the 

more standard definition used elsewhere. 
16 

 

1 2

2 1

t t

t t

I I

V V

ASI

−

−

= (3.11) 

The ASI for the electrochemical charge and discharge process is referred here-in as ASIechem. Our 

calculation approach for both the ASI for power and for energy involves adding three 

components together to reach the ASIechem, Eq. 3.12. The first two factors include impedance that 

arises from the interfacial charge transfer and transport. The third factor is a lumped parameter 

used to capture the remaining impedance. 

 

 ASI echem ASIintf ASIintf ASI const

pos neg

= + + (3.12) 

The interfacial impedance for positive and negative electrodes both contain the charge transfer 

resistance component RT/(ioaLF) as shown in Eq. 3.13 and 3.14. Here, io is the exchange current 

density related to the interfacial area and a is the ratio of interfacial area to electrode volume. An 

approximation often used for a relates the parameter to the volume fraction of the active material 

and the particle radius, a = 3εact/rp. The variables io and a should be specified to relate to the 

same area as they are often not independently determined. R and T correspond to the universal 

gas constant and absolute temperature respectively. F is Faraday’s constant. The influence of the 

interfacial impedance is that the ASIechem increases as the electrode thickness is reduced. This 

behavior is typically observed at electrode thicknesses less than 30 microns for common Li-ion 

battery materials. 

 

 

i aL F

RT

ASI

o neg

=

neg

intf (3.13) 

 

 

– 5.0

2

lim lim,

pos

intf 1 1

















































− 















= −

C

C

ionic

o pos r

r

I

I

i aL F

RT

ASI (3.14) 

The positive electrode interfacial impedance also includes two factors that account for the 

physical limitations that occur from depleting the concentration of the reactants within the 

porous electrode. The ionic I

lim term is the limiting ionic current for lithium cation transport through 

the porous separator. The C lim,r term is the limiting C-rate for solid state diffusion of lithium in 

the active materials. The C-rate may be related to the current density with Eq. 3.15. Here, the 

specific capacity, Q, the active material density, ρ, active material volume fraction, εact, and the 

electrode thickness, L, are used. If either the limiting C-rate or limiting ionic current are 

approached, the ASI will begin to approach an infinite value. The parameters required for the 

ASI expression are fit to experimental measurements. The ASI values are corrected for the 

interfacial contributions present during measurement so that the correct ASI may be determined 

at different electrode thicknesses. 
17 

 CQ act Lpos I = r ρε (3.15) 

 

The cell ASI for energy, ASIenergy, and power, ASIpower, are determined by adding the ASIechem to 

that of the current collectors, ASIcc, as discussed in the next subsection. The difference between 

ASIenergy and ASIpower is that the limiting currents are not important during the C/3 discharge for 

energy and the ASIconst is a different value for two cases. ASIenergy will always be higher than 

ASIpower if a battery is operated far from the limiting current. The higher impedance is due to the 

formation of significant concentration polarizations during the longer time scale of the energy 

discharge. A reasonable rule-of-thumb is that the ASIconst for energy is 2.2x the value for power 

in layered oxide materials such as LiNi0.80Co0.15Al0.05O2. 

3.4.1 Current Collection Resistance 

The resistance from the conductors used to collect the current must be accounted for as they can 

contribute significant ohmic drop to the battery. The ASI used to calculate the required cell 

separator area, ASIpower, is larger than the ASI for the electrochemical charge and discharge 

processes, ASIechem,P, as shown in Equation 3.16. The ASIechem value is typically measured from 

experiments and must be added to the external resistances that arise from the materials used to 

conduct the electric current. These resistances come from current collection in the cell and also 

those on the module and battery pack level. 

 

cells

cell cnct pos

power echem,P cc term N

R A

ASI = ASI + ASI + ASI + (3.16) 

The current collector foil impedance, ASIcc, is determined from an analytical expression, Eq. 

3.17, which accounts for the coated and uncoated region of the foil, labeled act for active and tab

respectively. The resistance factor, Rf, and the resistance of the current collector foils, Rcc, are 

also shown for clarity in Eq 3.18 and 3.19. The factor of 2 in the Rf

 term is due to assuming half 

of the foil thickness carries the current produced on one side of the foil. While all of the current 

passes through the tab region, the magnitude of the current varies along the height of the coated 

foil as the reaction area continually contributes current to the foil. An equivalent length for the 

resistance calculation may be determined so that multiplication by the total current for a cell will 

give the correct ohmic drop. This equivalent length is H/3 if the current density is relatively 

constant over the entire area. The derivation of this equivalent length as well as an in-depth 

discussion of the voltage and current distribution in the foils may be found in subsection 3.4.2. 

Also in the later subsection, the assumption of constant current density is verified with numerical 

modeling. 

 

 

( )

















= = + act tab

act

cc act act cc f H H

H

ASI H W R R

3

2

 (3.17) 

 















= +

foil neg foil neg foil pos foil pos

f

L L

R

, , , ,

2 2

σ σ

 (3.18) 
18 

 















= +

W

H

W

H

R R

tab

act

act

cc f

3

 (3.19) 

The cell terminals are ultrasonically welded to the ends of the current collector foil tabs. While 

the welding removes this contact resistance, the ASI of the terminal must be included in the total 

cell resistance. The ASI of the cell terminals, cell ASIterm , is the summation of the positive and 

negative cell terminals as shown in Eq 3.20. The dimensions for these terminals are set by the 

calculated width of the cell and the user defined terminal thickness and height. 

 pos

term term

term

term neg term pos

A

W L

H

ASI 















= +

, ,

cell

term

1 1

σ σ

 (3.20) 

The ASI for connection losses is the last term in the ASI summation stated in Eq. 3.16. This ASI 

value is calculated by multiplying the ratio of cell positive electrode area to number of cells by 

the summation of the resistances, Rcnct, for cell terminals, module terminals, module 

interconnects, and batteries terminals. In this way, each cell shares in the burden of overcoming 

the system losses from carrying the electric current. The calculation of Rcnct is detailed in Eq. 

3.21 with the individual sources of connection losses shown. The voltage drop resulting from 

cell-to-cell contact resistance, cell Rcntct , is taken to be 10-4Uocv,E in Eq. 3.22, a small fraction of the 

open-circuit voltage. A battery manufacturer would only tolerate a minimal voltage drop from 

cell-to-cell contact. One connection method is to physically press the two cell terminals together. 

This resistance could be lowered by increasing the physical pressure and contact area, or by laser 

welding the terminals together. Regardless, the value used in the model is left to the choice of the 

user to leave as is or to change to a different value. 

 ( )

batt

term incnt term

cell Rcnct = NcellRcntct + N R + N − R + Rmod

mod

mod

mod 1 (3.21) 

 

pos

cell cell ocv E

cnct IA

N U

R

4 ,

10−= (3.22) 

The module terminal resistance, mod Rterm , calculation in Eq. 3.23 is shown as an example of how the 

terminal and interconnect resistances are calculated for the module and battery pack. The size of 

the terminals and thus their resistance are determined from a calculation based on a predetermined allowable rate of temperature rise for the conductor. This approach is explained in 

more detail in subsection 3.4.3. 

 ( )

mod

2

mod

term term

term term

term N

r

H

R

σ π

= (3.23) 
19 

3.4.2 Potential and Current Distribution in the Current Collection Foils 

The designed current collection system was evaluated using a numerical simulation package. 

Equations 3.24-3.26 were solved for a steady state, isothermal, and 1-D simulation. Here, the 

conductivity, σj, is the effective conductivity of 1⁄2 of the foil (the other half carries the current 

from the opposite side). The bulk conductivity value, σj

0

, is multiplied by the thickness of the 

conductor, Lj/2, to lower the dimension of transport. 

 

( ( ) ( ))

echem

ocv pos neg

n

ASI

U x x

I

− Φ ,1 − Φ ,1

= (3.24) 

 ( ) pos pos n ∇ ⋅ ∇Φ = −I σ ,1

 (3.25) 

 ( ) neg neg n ∇ ⋅ ∇Φ = I σ ,1 (3.26) 

 

The boundary conditions were set for both ends of each foil. The tab ends of the foils were set to 

a specified voltage and the opposite ends of the foils were restricted to a no flux condition. The 

simulation was performed using the foils defined in our battery design: 12 micron thick copper 

foil and 20 micron thick aluminum. The cell length was 20 cm, the ASIechem was 30 ohm cm2, and 

the Uocv and Vcell were set to 3.72 and 3.57 V respectively. Figure 3.5 shows the current and 

potential distribution in the foils and in the cell resulting from the simulation. The cell potential 

along the length of the foil varies only by 1.5 mV from maximum to minimum difference. The 

0.4 % variation in voltage results in a 0.9 % variation in current density. This verifies the current 

density is uniform along the length of the foil. This is also obvious from the linear relationship of 

current with foil height in Fig. 3.5. The assumption of constant current density was tested in cell 

heights up to 100 cm and found to be satisfactory. The assumption should be reasonable as long 

as the ASIechem is at least twice the value of ASIcc. The simulated resistance of the foils is found 

to raise the ASIechem by 0.7 for an ASIpower of 30.7 ohm cm2. Additionally, the numerical result 

verified that H/3 is the correct equivalent length to represent the ASIcc for the cell. This may also 

be found analytically, Eq. 3.27-3.29, if you assume an even current distribution as we have 

shown is a reasonable assumption. 

 

 ( )

2 2

,1

2

H x

I

V

pos

n Φ pos = cell + −

σ

 (3.27) 

 















Φ = − xL I x

neg

n

neg 2

2

,1

σ

 (3.28) 

 















= + +

Φ − Φ

+ = ∫

pos neg

cell

H

n

pos neg

echem cc

H

I

V

dx

H I

ASI ASI

σ σ

1 1

3

1

2

0

,1 ,1

 (3.29) 
20 

Figure 3.5 The change in current and potential within the positive and negative foils. The current 

collection design results in a uniform current distribution along the length of the foil. 

3.5690

3.5700

3.5710

3.5720

3.5730

3.5740

3.5750

0 0.2 0.4 0.6 0.8 1

x/H

Positive foil and cell potential, V

-0.0060

-0.0050

-0.0040

-0.0030

-0.0020

-0.0010

0.0000

Negative foil potential, V

Cell

Positive foil

Negative foil

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0 0.2 0.4 0.6 0.8 1

x/H

Foil current per width, A/cm

0.00486

0.00487

0.00488

0.00489

0.00490

0.00491

0.00492

Current density, A/cm2

Negative foil

Positive foil

current density
21 

An analogous problem has been solved by Euler and Nonnemacher and then communicated 

repeatedly by Newman et al.

21, 22 The analytical solution they presented may be used after a 

slight alteration to dimensionalize the current density to the geometry of our concern, Eq. 3.30 

and 3.31. This solution was reached assuming linear polarization behavior and is valid for cases 

where the current density varies along the height of the current collector foil. Thus, this approach 

is a more general solution than the one we use in the design model. 

 

( )













































+ +

+

+

=

− Φ − Φ

+ =

v v

v

H

I

U neg

pos

pos

neg

neg pos

ocv pos neg

echem cc sinh

2 cosh

ASI ASI 1

2

,1 ,1

σ

σ

σ

σ

σ σ

(3.30) 

 















= +

ASI echem pos neg

H

v

σ σ

1 1

2

2

 (3.31) 

3.4.3 Determination of Module Terminal, Battery Terminal, and Module Inter-connect Size 

An important factor for setting the resistances of a module terminal, battery terminal, or module 

interconnect is the allowable rate of temperature rise in the conductor at full power. We set the 

acceptable rate of temperature rise, dT/dt, at 0.2 °C/sec or a 2 °C rise for a 10-sec power burst 

under adiabatic conditions. The heating rate, q, is then used to determine the mass, m, of the 

terminal required for the designed battery in Eq. 3.32. Since the heating rate may also be 

determined by Eq. 3.33, we may determine the cylindrical terminal radius and mass by assuming 

a length, Hterm. In this way, the size of the module terminal is redesigned during each simulation 

to meet the specified power requirements and allowable temperature rise, Eq. 3.34. The mass of 

the conductor is found to be inversely proportional to the allowable temperature rise. 

 

dt

dT

q = mCp (3.32) 

 ( )2

pos

term term

term IA

A

H

q

σ

= (3.33) 

 

− 2/1













=

dt

dT Aterm IApos ρ termσ termCp

 (3.34) 

3.5 Calculation of Battery Dimensions 

The goal of the model is to quantify how the various components of a specific battery design 

sum to make the mass and volume of the battery pack. In this way, a true energy and power 

density can be calculated as well as the exact materials requirement to meet this design. 
22 

Summing the mass of the components is relatively straight forward. Determining the total 

volume that contains the components and required free volume is not as obvious. The exact 

calculations used in the design model are detailed below for the cell, module, and battery pack. 

3.5.1 Cell Dimensions 

The number of layers in each cell is approximated in Eq. 3.35 by accounting for the compression 

factor, Xcomp, and the individual thicknesses of the current collector foils, Lfoil, electrodes, Lpos

and Lneg, separator, Lsep, and container, Lcont. Xcomp is usually taken to be 0.97. The Li-ion battery 

chemistries this model was designed for are assumed to undergo negligible volume change on 

the cell level. No effort was made to address possible changes in electrode volume upon cell 

discharge or charge. 

 

(2 )

2

sep neg pos

pos

foil

neg

foil

neg

cell cont foil

layers comp L L L L L

L L L

N X

+ + + +

− +

= (3.35) 

The Nlayers approximation is necessary as the cell thickness is a user defined parameter. The 

aspect ratio of the cell is also user defined; therefore, solving for the width also determines the 

height of the cell as seen in Eq. 3.36. The width is calculated from the number of layers and the 

aspect ratio, H/W. The factor of 2 enters the denominator as both sides of the foil are assumed to 

be coated. 

 

layers

pos

pos

N

W

H

A

W

2

= (3.36) 

 

Having determined the width and height of the electrode, the rest of the cell dimensions are 

relatively straightforward, Eq. 3.37 and 3.38. The width of the cell, Wcell, is 8 mm wider than the 

positive electrode to allow for the larger separator area and pouch seals. The pouch seals are 

folded up, pressing along the inside wall of the module casing. The height of the cell, Hcell, is the 

height of the positive electrode in addition to the distance for the terminals and connections to 

the foil tab, Lterm,cnt. Our assumed design requires 15 mm for this distance. The volume of the cell 

is the product of the three dimensions. 

 = + 8 Wcell Wpos (3.37) 

 Hcell H pos Lterm,cnt = + 2 (3.38) 

3.5.2 Module Dimensions 

The module dimensions are defined by Eq. 3.39-3.41. The height and length of the module are 

both just 2 mm wider than the cell dimension. The width of the module is related to the total 

thickness from all of the cells with allowance for a SOC controller at one end. 

 2 H mod = Wcell + (3.39) 
23 

 2 Lmod = Hcell + (3.40) 

 ( 1) 1 Wmod = Lcell Ncell / mod + + (3.41) 

3.5.3 Battery Pack Dimensions 

The battery pack volume includes all of the modules, spacing for connections between modules, 

channel for the cooling air to flow, Hair, thickness of the module compression plates, Lcomp, and 

the battery pack jacket, Ljack (Eq. 3.42-3.44). Ljack includes a 10 mm thick insulation layer 

sandwiched between two aluminum walls for the container. The thickness of the aluminum wall 

increases from 1 to 1.5 to 2 mm as the battery volume increases from < 20 L to < 40 L to larger 

dimensions. The layout of the modules, number per row, Nmod/row, and number of rows, Nrow, is 

also included. The final volume of the battery is the product of the three dimensions. The space 

left for connections between modules, Lgap, is a function of the number of rows of modules. Lgap

is equal to 8, 10, or 20 depending if there is one, two, or four rows of modules. Three rows of 

modules are not allowed as the positive and negative terminal for the battery would be on 

opposite ends and thus not very practical. A number greater than four rows of modules is deemed 

unnecessary. 

 Hbatt H Hair Ljack 2 2 = mod + + (3.42) 

 Lbatt N rowW Hair Lcomp Ljack 2 2 = mod/ mod + + + (3.43) 

 Wbatt Nrow L Lgap Ljack 2 = mod + + (3.44) 

3.6 Additional Considerations 

A few situations may arise that require a change in the calculation method. These situations are 

addressed in the subsections below. The inclusions of these calculations into the model allow for 

a more realistic depiction of limitations often encountered by cell manufactures. 

3.6.1 Maximum Electrode Thickness 

A practical limitation exists for the maximum achievable electrode thickness. This limitation 

may be set by manufacturing capabilities, ionic and electronic current transport within the porous 

electrode, or aging characteristics related to adhesion to the current collector. When the 

maximum electrode thickness, Lmax, has been reached on either the positive or negative electrode, 

the electrode area equation is modified as shown in Eq 3.45. The electrode thickness, Ltgt, is the 

largest electrode thickness, negative or positive, calculated at the targeted fraction of the OCV 

[V/U]. 

 pos

L tgt

pos A

L

L

A

max

max

= (3.45) 
24 

The area of the electrode is now determined by the cell capacity requirement to meet the battery 

energy demands and not the target voltage at maximum power. As a consequence, the battery 

pack will operate at a higher [V/U] than originally selected by the battery designer. The new 

[V/U] may then be calculated from Eq. 3.46 which is the solution to the quadratic found in Eq. 

3.47. 

 ( )

















= + − 











cells pos

batt power

cell cell

cell N A

P ASI

U U

U U

V

4

2

1 2

 (3.46) 

 

cell cells pos

batt power

cell cell V N A

P ASI

V = U − (3.47) 

The maximum electrode thickness has a large impact on the energy density and cost of cells 

designed for high energy and range. Nelson et al. demonstrated this concept in 2009 assuming a 

100 micron maximum electrode thickness.11,17 In 2010, Santini et al. relaxed this assumption to

300 micons; although, the thickest electrode discussed in the paper was a 225 micron graphite 

electrode in the LMO-Gr EV with 100 mile range.12 In conversations with manufactures, 100 

microns appears to be the general electrode thickness used for EV type cells at the present time. 

However, Santini et al. has shown substantial increases in energy density and decreases in cost if 

larger electrode thicknesses may be utilized. The challenges to achieving thick electrodes, in 

addition to those already mentioned, relate to fast charging while avoiding lithium metal 

deposition, removing gases formed during formation cycling, wetting the full porosity of the 

electrode, achieving defect free coatings, and drying the thick electrode at high rates. Our 

opinion is that the successful cell manufacturers will engineer ways to overcome these 

challenges to increase energy density and lower cost. 

3.6.2 Accounting for Parallel Cell Arrangements 

The user of the design model may wish to use a parallel arrangement of cells within the larger 

series arrangement of the battery pack. Several motivations exist for a parallel cell arrangement. 

For example, a battery supplier may wish to only produce cells of a specific capacity. The 

manufacturer may only have the equipment to produce a certain size cell or they may encounter 

engineering design problems for very large cells ( > 60 Ah). Thus, a cell group composed of 

parallel connected cells may be necessary to meet the energy requirements while staying within 

battery pack voltage and current requirements. 

When the user chooses to have cells connected in parallel, the design model calculation includes 

the appropriate factors necessary to account for changes in the resistance, volume, and mass of 

the battery. The end result is a lower energy density for the battery from including the cell group 

interconnects and additional inactive material for each cell. Furthermore, the thickness of the 

cells is reduced to 6 mm to better suit the smaller cell format. 
25 

4. Modeling of Battery Pack Manufacturing Cost 

4.1 Approach 

The manufactured cost of a battery pack is calculated with input from the design information 

generated in modeling the cell and battery pack performance. The design modeling determines 

the annual materials and purchased items requirements. The manufacturing cost is then added to 

these materials costs, along with a warranty cost, to reach the unit cost of a single battery pack. 

The manufacturing costs for the designed battery are scaled from a baseline plant. The baseline 

plant was designed for a battery of intermediate size and production scale so as to establish a 

center-point for other designs. The baseline plant accounts for the size, speed, number of units, 

direct labor, and depreciation of the capital cost for each processing step. These costs are 

adjusted to meet the requirements for a plant producing the battery under study. The process 

expenses are summed with the additional costs of operating the manufacturing facility. These 

costs include launch costs, working capital, variable overhead, general, sales, administration 

(GSA), research and development, depreciation, and profit. 

In this analysis, all costs are evaluated for 2020 when large battery manufacturing plants are 

built. All dollar values are brought back to 2010 with allowance for inflation. Some materials 

and battery manufacturing costs are lower than recent values, where we judged that processing 

improvements for high volume production of materials would reduce costs. 

The baseline manufacturing plant was calculated for an annual production rate of 100,000 

batteries. The cost model accounts for different scales of manufacture by recalculating the costs 

of each individual step in the manufacturing process. The changes in capital and operating costs 

will change the calculated unit cost of the battery pack. However, the parameters were 

determined to provide reasonable estimates for manufacturing rates of 20-500 % of the baseline 

rate. Thus, for a plant that is far different in size from the baseline plant, for instance a pilot plant 

having an annual production of only 5,000 battery packs per year, the estimate from this study 

would be expected to be less accurate than if determined in a study dedicated to that purpose. 

To simplify the cost calculations, it was assumed that all hardware items for the cells, modules 

and battery will be purchased from a vendor specializing in similar products. The costs for these 

items were estimated to be a fixed value plus an additional value proportional to the weight of 

the item, which is calculated during the battery design. In mature manufacturing plants in 2020, 

toward which this study is directed, some items which are assumed to be purchased in this study 

might actually be internally manufactured from raw materials. This would increase the number 

of processing steps needed in our manufacturing simulation and thus complicate the cost 

calculations. Assuming that some parts would be purchased if they would actually be produced 

from raw materials would tend to underestimate capital and labor costs and overestimate 

purchased items expenses. However, the net effect would be a very small change to the overall 

unit cost of the battery pack. 
26 

4.2 Materials Costs and Purchased Items 

The end battery pack cost depends significantly on the cost of both the active and inactive 

materials that compose the design. In this subsection, the assumed material costs and the rational 

behind them are presented. While we state suggested materials costs, the user of the cost model 

may enter any value that they desire. 

4.2.1 Battery Specific Materials Cost 

The largest contributions to the materials cost of the battery are from the following components: 

positive and negative electrode active material, separator, electrolyte, and current collector foils. 

The choice of the materials often defines the size and performance of the battery as well as the 

cost. Many different variations of materials are possible in the Li-ion family of chemistries. 

However, we have chosen to focus on the different available positive electrode materials with 

less attention on the negative electrode. This reflects the current research and manufacturing 

activities. The separator and the electrolyte are also both active areas of development. However, 

the following battery designs are based on a single electrolyte and separator combination. 

Including the cost and effect of additives and enhanced separators is beyond the scope of this 

work. The user is always able to modify the dimensions, cost, and ASI that may be required to 

account for changes in these materials. 

The price of specific battery materials is of some debate. The values presented in Table 4.1 

compare our suggested costs to those reported recently in the open literature. Our values, as well 

as the others in the table, are derived from conversations with material, cell, and original 

equipment manufacturers. The sources are commonly anonymous and the accuracy of the values 

is generally unknown. We present the comparison of published values so that the user of the cost 

model may appreciate the accepted range of values for commonly used materials. 

4.2.1.2 Positive Electrode Active Materials 

The cost of positive electrode materials is driven to a large extent by the cost of the raw materials 

from which it is made. The archetype Li-ion positive electrode material, lithium cobalt oxide 

(LCO), was the original material commercialized in Li-ion batteries for consumer electronics. 

LCO has many excellent characteristics but is not considered a viable choice for use in Li-ion 

batteries for automotive applications. One of the largest drawbacks of LCO, other than safety 

concerns, is the cost of the cobalt. While tolerable in the consumer electronics market, the cost is 

too high for use in an automobile battery. Many other materials are in a commercially viable 

state of development and are currently utilized in Li-ion batteries produced today (Table 4.1).3,6

The relative advantages and disadvantages of each material will not be discussed here. 

The amount of cobalt and nickel, as well as ease of manufacture, controls the end price for a 

positive electrode material. For example, the NMC-441 is less expensive than the NMC-333 as 

the cobalt quantity is significantly reduced. The market price for cobalt and nickel metal varies 

dramatically from year to year. Reducing the quantities of these materials will reduce the 
27 

 ANL TIAX CARB Material Chemistry Abbreviation unit 2010 2010 2007 Manganese spinel cathode Li1.06Mn1.94O4 LMO $/kg 10 12 - 16 - 20 8 - 10 Phospholivine cathode LiFePO4 LFP $/kg 20 15 - 20 -25 16 - 20 Layered oxide cathode LiNi0.80Co0.15Al0.05O2 NCA $/kg 36 34 - 40 - 54 28 - 30 Layered oxide cathode Li1.05(Ni1/3Mn1/3Co1/3)0.95O2 NMC-333 $/kg 40 40 - 45 -53 22 - 25 Layered oxide cathode Li1.05(Ni4/9Mn4/9Co1/9)0.95O2 NMC-441 $/kg 33 - - Li & Mn rich layered cathode xLi MnO 2 3·(1-x)LiNi Mn y Co z 1-y-zO2 LMR-NMC $/kg 25 24 - 31 - 39 - Layered oxide cathode LiCoO2 LCO $/kg - - 30 - 40 Graphite anode C6 Gr $/kg 19 17 - 20 - 23 - Titanate spinel anode Li4Ti O5 12 LTO $/kg 12 9 - 10 - 12 - Electrolyte 1.2 M LiPF6 in EC:EMC $/kg 19 18.5 - 21.5 -24.5 - Separator PP/PE/PP $/m2 2 1 - 2.5 -2.9 - Current collector foil Copper $/m2 3.00 - - Current collector foil Aluminum $/m2 0.80 - - Table 4.1 Details of stated costs for cathodes, anodes, electrolyte, and separator.3,6
28 

positive electrode material price and price volatility. Researchers at TIAX LLC have treated this 

variation and shown the significant effect on end battery cost.10 The average metal prices for the 

last 20 years is 48 $/kg and 15 $/kg for cobalt and nickel respectively. These numbers are based 

on historical prices for the metals as collected by the United States Geological Survey (USGS).23

The metal prices are best used as indicators for how the intercalation material cost will relate 

when compared to one another. The fact these materials are not earth abundant means they will 

not benefit as much as other materials from increased scales of production. 

In general, earth abundant elements should be the dominate transition metal used if a low 

positive electrode cost is desired. Both iron and manganese are abundant and inexpensive 

transition metals for intercalation materials. Comparison of the iron phosphate, LFP, to 

manganese spinel, LMO, reveals how processing costs contribute to the end price of a material. 

LMO is relatively easy to manufacture. In contrast, LFP requires a reducing atmosphere and a 

carbon coating step to reach the end product. The increased complexity in the manufacturing 

process is realized in the price. However, one could argue that the manufacturing cost will 

decrease with increased knowledge from larger scales of production. 

4.2.1.2 Negative Electrode Active Materials 

While multiple negative electrode materials exist for Li-ion batteries, carbon materials in the 

form of graphite and/or hard carbon are still used in the vast majority of commercial cells. 

Graphite offers the greatest energy density while hard carbon is said to enable high rate 

capability with decreased risk of lithium plating (an undesired side reaction) during high charge 

rates. We have chosen synthetic graphite as a generic carbon electrode in our model. The price of 

graphite is much better understood than that of most of the positive electrode materials. 

However, significant differences in cost and performance will exist between synthetic, natural, 

and coated-natural graphite. The method of production and necessary heat-treatment will control 

the end cost. Graphite, although in different purity grades or microstructure forms, is used in 

many industries. This is in stark contrast to the positive electrode materials. 

The lithium titanate electrode, LTO, offers an interesting option compared to graphite. Unlike 

graphite, LTO operates within the stability window of the electrolyte. The higher electrode 

potential dramatically reduces or eliminates the formation of the solid electrolyte interphase 

(SEI). As a result, nanoparticle-based LTO may be implemented without concerns of increased 

side reactions with the electrolyte. The reduced dimensions increase the available surface area 

for reaction while simultaneously shortening the diffusion length. Both of these factors combined 

with the lack of SEI dramatically reduce the impedance of the electrode. 

4.2.1.3 Electrolyte and Separator 

The electrolyte used in this model is based on a lithium hexafluorophosphate salt, LiPF6, 

dissolved in a carbonate based solvent system. The carbonate solvent system is a blend of 

ethylene carbonate, EC, and a linear carbonate such as ethyl methyl carbonate, EMC, or dimethyl 

carbonate, DMC. Other chemical additives may be used to lower the capacity and power fade of 

the battery over time. Polymers may be added to the electrolyte as either a minor or major 
29 

component. This is not discussed in any further detail in this work. The price of $16/L, about 

$19/kg, is only for the base electrolyte (i.e. no additional additives). 

The separator is typically a porous membrane based on polypropylene (PP) and sometimes 

includes a polyethylene (PE) middle layer. PP and PE are very inexpensive raw materials and 

thus the suggested cost of $2/m2 is in large part due to the manufacturing process required to 

form the porous network in the membrane. As competition and scale of manufacture increase, 

the prices of the separator may fall closer to $1/m2

. However, the cost of improved technology 

may offset some of this cost reduction, so we have retained our cost estimate of $2/m2. 

As safety is a major concern for Li-ion batteries, the separator plays a key role in isolating the 

oxidant from the fuel. If the two charged electrodes contact each other (short), then a run-away 

reaction is possible. Separators have been designed to “shut-down” or melt at key temperatures. 

The middle PE layer is the shut-down feature in our proposed separator. Ceramic coatings have 

also been used to ensure structural integrity. Many other approaches are being developed to 

increase the safety of Li-ion batteries. The user of the cost model should account for the 

increased technology in the price and dimensions of the separator as needed. 

4.2.1.3 Current Collector Foils 

The current collector foils are based on copper metal for the negative electrode and aluminum for 

the positive electrode. However, the LTO anode material, because of its high voltage relative to 

lithium, enables the use of aluminum as the negative electrode current collector. The price of 

these foils is based on raw materials and manufacturing costs. The foils are 12 microns and 20 

microns thick for the copper and aluminum current collectors respectively. The foils used in 

batteries have additional requirements beyond the cheapest product available. Surface treatments 

are often necessary to promote adhesion of the electrode to the foil surface. In addition, alloying 

of the foil may be necessary to achieve the required material properties for long life. 

The raw material contributions to the foil price will vary with the volatility of the market price 

for the metals. Figure 4.1 displays the metal ingot price contribution on a $/m2

 basis. These 

numbers are based on historical prices for the metals as collected by the USGS.23

The values for both aluminum and copper tend to vary significantly over the time period 

examined. The price for copper is more volatile and always more expensive than aluminum. 

Analysis of Figure 4.1 reminds the user of the cost model that cost quotes are only valid for a 

short period. As the market price for raw materials changes, so will the price for the finished 

product. 

Conversations with manufacturers and suppliers lead us to take a price of 3.00 and 0.80 $/m2

 for 

battery grade copper and aluminum foil respectively. We point out that the current metal ingot 

price is only a small contribution to the end foil price being about 15 % of the aluminum foil 

price and 25 % of the copper foil price. Thus, a doubling of the ingot prices would only 

moderately increase the foil prices. The aluminum foil is produced by rolling of thicker stock 

foils into thinner and thinner sheets. On the other hand, copper foil is more likely to be produced 

through an electrodeposition process. 
30 

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1985 1990 1995 2000 2005 2010

Year

Metal Ingot Cost in 2010 $/m

2

Copper

Copper 20 yr avg

Aluminum

Aluminum 20 yr avg

Figure 4.1 Metal ingot cost contribution to the current collector foils over a 20 year period. The 

average for that period is also shown. All costs are in 2010 US$. 

4.2.1.4 Additional Electrode Components 

The binder and conductive additive in the positive and negative electrodes add a small but real 

cost to the battery. The conductive additive, more common for the positive electrode, was priced 

at 6.80 $/kg for a high purity and moderate surface area carbon black material. The binder, 

perhaps PVDF or CMC based, is assumed to be 10 $/kg. The N-Methyl-2-pyrrolidone (NMP) 

solvent for the PVDF binder is estimated to be 3.20 $/kg. Most of the NMP is recovered after 

evaporation and recycled as discussed in section 4.3.3. Only the small amount lost in processing 

need be replaced. No cost is assumed for water. 

4.2.2 Purchased Items Cost 

Table 4.2 lists the purchased items for the cell module and battery jacket. The cost of a SOC 

controller for each cell, or group of parallel cells, is $1.80 plus a small factor for the cell capacity 

(Ah), which allows for higher cell balancing currents for larger cells. The other components cost 
31 

a fixed amount plus an additional factor, which is proportional to their mass, mi. The cell 

negative terminal and parallel cell group connection are both made from nickel plated copper 

sheet and thus have the same cost equation. 

Table 4.2 Cost equations for purchased items 

Component, i Cost Equation, $/unit Cost per unit 

SOC controller 1.80 + 0.005C cell or parallel cell group 

Cell positive terminal 0.10 + 4mi cell 

Cell negative terminal 0.10 + 5mi cell 

Cell container 0.10 + 5mi cell 

Parallel cell group connection 0.10 + 5mi parallel cell group 

Module terminals 0.75 + 4mi module 

Balance of module (casing) 1.00 + 3mi module 

Battery enclosure & cooling 50.00 + 7mi battery pack 

4.3 Baseline Manufacturing Plant 

The baseline plant is designed to produce 100,000 NCA-Gr baseline battery packs per year. The 

baseline battery pack produced by the plant has sixty, 40-Ah capacity cells, providing a total 

pack power of 50 kW and total energy of 8.7 kWh. The battery will power 24.4 miles of vehicle 

travel at 70% of the pack energy and 250 Wh/mile. The schematic diagram of the plant (Fig. 4.2) 

is designed to illustrate the flow of materials through the plant and the relative floor areas for the

processing steps rather than representing a realistic plant layout. The overall manufacturing rate 

of 100,000 battery packs per year is achieved by operating for three shifts at the equivalent of 

300 days per year of fully effective production. There will be more than 300 days of operation, 

but some days will have less than 100% effectiveness. The exceptions to three-shift operation are 

the Receiving and Shipping sections, which are active for only two shifts per day. The cost 

factors for the individual manufacturing steps in the baseline plant are summarized in Table 4.3 

and discussed in detail in the sections that follow. Most of the operations are carried out with 

normal factory atmosphere, but the cell assembly process steps are completed in a dry room 

atmosphere. 
32 

Figure 4.2 Baseline lithium-ion battery manufacturing plant schematic diagram. Manufacturing 

rate: 100,000 NCA-Gr battery packs per year, 50-kW pack power, 40-Ah capacity, 60 cells per 

battery. Operating year: 300 days with three 8-h shifts (two shifts for receiving and shipping) 

4.3.1 Receiving and Shipping 

These operations require the moving equipment and storage facilities common to any such 

factory facilities. The Receiving section handles slightly less than 6,000,000 kg of materials per 

year and also has facilities to handle and store some of the electrode materials in a dry 

atmosphere. The Shipping section is required to enclose the battery packs in crates, which 

requires some automated equipment and more labor than is required for Receiving. Shipping also 

handles about 400,000 kg of scrap each year, which is broken down and prepared for shipping in 

the Rejected Cell and Scrap Recycle section. The estimated resources needed for the Receiving 

and Shipping sections are shown in the table below.

 Rate Factor Direct Labor Capital Equip.* Plant Area, m2

Receiving 

 Off-loading 

 Moving 

 Storage

870,000 kWh/y 3 per shift 3.60 mil$ total 

 0.60 

 1.20 

 1.80 

600 

Shipping 870,000 kWh/y 6 per shift 5.0 mil$ total 600 

*Total cost including installation 

The areas in this diagram for each processing step are approximately proportional to 

the estimated plant areas in the baseline plant.

Shipping

Cell and 

Scrap 

Recycling

Receiving

Control 

Laboratory

Assembly Route

Battery Pack 

Assembly 

and Testing

Module 

Assembly

 Formation 

 Cycling

Current 

Collector

 Welding

Enclosing 

Cell in 

Container

Electrolyte Filling

and Cell Closing

Cell Stacking

Solvent 

Evaporation

Positive

Negative

Electrode 

Coating

Positive

Negative

Electrode 

Slitting

Vacuum 

Drying

Electrode Materials 

Preparation

Positive

Negative Calendering

Solvent 

Recovery

Air 

Locks

ChargeRetention 

Testing 

Final 

Cell 

Sealing

Dry Room

Materials 

Handling

Outdoor dry-room air 

processing equipment
33 

No./shift Hours/yr p Factor $MM p Factor m2 p Factor

Receiving (two-shift operation) 869,420 kWh energy 3 14,400 0.4 3.60 0.6 600 0.5

Materials preparation Positive electrode 1,712,524 kg active material 3 21,600 0.5 4.00 0.7 400 0.6

 Negative electrode 1,208,957 kg active material 3 21,600 0.5 4.00 0.7 400 0.6

Electrode coating Positive electrode 8,169,835 m2 cell area 4 28,800 0.5 6.00 0.8 (0.2)* 500 0.8

 Negative electrode 8,169,835 m2 cell area 4 28,800 0.5 6.00 0.8 (0.2)* 500 0.8Solvent recovery 2,309,021 kg NMP 2 14,400 0.4 3.00 0.6 150 0.6

Calendering Positive electrode 8,169,835 m2 cell area 1 7,200 0.5 1.00 0.7 150 0.6

 Negative electrode 8,169,835 m2 cell area 1 7,200 0.5 1.00 0.7 150 0.6Materials handling# 8,169,835 m2 cell area 4 28,800 0.7 1.50 0.7 600 0.6Electrode slitting 8,169,835 m2 cell area 4 28,800 0.5 2.00 0.7 200 0.6Vacuum drying 8,169,835 m2 cell area 2 14,400 0.5 1.60 0.7 200 0.6Control laboratory 869,420 kWh energy 4 28,800 0.5 1.50 0.7 200 0.6

Cell Assembly in Dry Room Cell stacking 6,315,789 total cells 6 43,200 0.7 5.00 0.8 (0.3)** 400 0.8

 Current collector welding 6,315,789 total cells 6 43,200 0.7 5.00 0.8 400 0.8

 Enclosing cell in container 6,315,789 total cells 4 28,800 0.5 3.00 0.7 400 0.6

 Electrolyte filling, and cell sealing 6,315,789 total cells 6 43,200 0.5 6.00 0.7 600 0.6

 Dry room control and air locks 2,000 m2 operating area# 2 14,400 0.4 20.00 0.6 75 0.4

Formation cycling 6,315,789 total cells 8 57,600 0.7 30.00 0.8 (0.3)** 1,500 0.8

Final cell sealing 6,315,789 total cells 2 14,400 0.5 7.50 0.7 300 0.6

Charge retention testing 6,315,789 total cells 3 21,600 0.4 4.75 0.7 600 0.6

Module assembly 6,000,000 finished cells 6 43,200 0.5 6.00 0.7 400 0.6

Battery pack assembly and testing 100,000 battery packs 6 43,200 0.5 6.00 0.7 (0.3)*** 600 0.6

Rejected cell and scrap recycle 6,315,789 total cells 5 36,000 0.7 2.50 0.7 400 0.6

Shipping (two-shift operation) 869,420 kWh energy 6 28,800 0.5 5.00 0.7 600 0.6

Total 95 662,400 135.95 10,325

#One-third of the space for materials handling is within the dry room.

*The baseline capital cost electrode coating, Co, is based on the evaporation of the baseline annual solvent weight (Rso). For batteries requiring 

different solvent evaporation rates Rs, the cost is multiplied by ratio of rates raised to the 0.2 power. Thus, Cost = Co*(R/Ro)^0.8*(Rs/Rso)^0.2.**The baseline costs of the capital equipment for cell stacking and formation cycling is for 40-Ah cells. To correct the baseline cost (Co) for cells 

of different capacity, the cost is multiplied by the capacity ratio, (Cap)/ 40 Ah, raised to the 0.3 power. Thus, Cost = Co*(R/Ro)^0.8*(Cap/40)^0.3. 

***The baseline cost of the capital equipment for battery assembly is for a battery with four modules. To correct the baseline cost for a different number of modules (Mod), the cost is multiplied by the ratio of modules, (Mod)/4 raised to the 0.3 power. Cost = Co*(R/Ro)^0.7*(Mod/4)^0.3.

Annual Baseline Rate (Ro)

Direct Labor Cap. Equipment Plant Area

Table 4.3 Summary table of the baseline plant 
34 

4.3.2 Electrode Materials Preparation and Delivery to Coating 

The electrode materials, which consist of active material, carbon (if necessary), binder and 

binder solvent, are well mixed in small batches in portable tanks. At the design production rate 

in the baseline plant, each shift requires three tanks each holding about 1000 liters of positive 

electrode material mix and three tanks each holding about 900 liters of negative electrode 

material mix. The section must be capable of exceeding this design rate of production by at least 

25% to catch up in case of unscheduled downtime in Materials Preparation or in some of the 

section immediately following that section. The tanks of prepared materials are moved to the 

Coating section and pressurized to push the coating paste into the coating mechanism. The 

estimated resources needed are the following: 

Materials Prep. Rate Factor Direct Labor Capital Equip.* Plant Area, m2

Positive 

Materials 

 Storage tanks 

 Mixing tanks 

 Moving equip.

1,710,000 kg/y 

active material 

3 per shift 4.0 mil$ total 

 2.00 mil$ 

1.00 

1.00 

400 

Negative 

Materials 

1,210,000 kg/y 

active material 

3 per shift 4.0 mil$ total 400 

*Total cost including installation 

4.3.3 Electrode Coating on Current-Collector Foil 

The positive and negative electrode structures are formed by coating both sides of the current 

collector foil. In the baseline plant, the coating lines are 1.5 meter wide continuous roll-to-roll 

coating processes carried out at a line speed of 10 m/min. The first set of coating and drying 

stations coats one side of the current collector foil, drives off the solvent in a heated oven, and 

turns the foil over while transferring it to a second set of stations. The second set of coating and 

drying stations applies and dries the remaining coating before the coated foil is wound into a 

large roll at the end of the line. The negative and positive coating lines are very similar. 

However, some of the negative material is coated only on one side to provide the electrodes at 

the end of the cell stacks. For the baseline plant, a total of 8,170,000 m2

/y of coating (annual cell 

area) is required for the positive electrode (slightly more for the negative electrode), which 

allows for the 5% loss of cells expected to fail testing and inspection. A larger area of foil than 

the coated area must be fed to the coaters to allow for the part of the foil that is not coated so as 

to provide tabs for welding to the terminals (about 10%) and to allow for trimming losses during 

electrode slitting (8%). Also, about 30% excess coating capacity must be provided to allow for 

unscheduled downtime. Only one coating line is needed for each electrode type to meet these 

needs. If one coating line breaks down, the other coating line may change over temporarily to 

coat the other electrode material. 

The oven sections of the coating line are designed to dry coatings about 100 microns thick at the 

coating speed of 10 m/min. A thicker coating will require longer ovens at additional capital cost 

which is provided in the adjustment of costs discussed in section 4.4. For the same annual area 

throughput, a coating line that coats both sides with a 300-micron coating would cost $7,500,000 
35 

rather than the $6,000,000 cost for the 100-micron coater. The binder solvent for the positive 

electrode in the baseline plant is NMP, which must be recovered by condensation and recycled. 

About 0.5% of the binder solvent is combusted with a thermal oxidizer and must be replaced. For 

the negative electrode the binder is water, which need not be recovered. The estimated resources 

to meet these needs are the following: 

Electrode Coating Rate Factor Direct Labor Capital Equip.* Plant Area, m2

Positive Electrode 

 

 Uncoated area 

 Width of coater 

 Coating speed 

 Number of coaters 

 Maximum rate 

 Excess capacity

8,170,000 

m

2

/y cell area 

4 per shift 6.0 mil$ total 

18% 

1.5 m 

10 m/min 

One 

13,000,000 m2

/y 

30% 

500 

Negative Electrode 8,170,000 

m

2

/y cell area 

4 per shift 6.0 mil$ total 500 

Solvent Recovery &

Oxidation 

1,527,000 kg 

NMP/y 

2 per shift 3.0 mil$ total 150 

*Total cost including installation 

4.3.4 Calendering 

The materials leaving the coating lines may be stored on large rolls (see next section). However, 

typically the materials leaving the coaters would go directly to the calendering process in which 

the coatings are compressed by rolling to meet the specified void volume fraction, which will 

later be filled with electrolyte. The calendering equipment must match the output of the coating 

equipment producing 8,170,000 m2/y of cell area with a maximum rate of 13,000,000 m2 of foil 

per year to meet contingencies as in coating. The estimated resources to meet these needs are the 

following: 

Calendering Rate Factor Direct Labor Capital Equip.* Plant Area, m2

Positive Electrode 8,170,000 

m

2

/y cell area 

1 per shift 1.0 mil$ total 150 

Negative Electrode 8,170,000 

m

2

/y cell area 

1 per shift 1.0 mil$ total 150 

*Total cost including installation 

4.3.5 Inter-Process Materials Handling

For all processes (Fig. 4.2), work in progress must be transported and occasionally stored to 

permit nearly-continuous operation of the equipment. Storage areas must be provided both inside 

and outside of the dry room. Raw materials must also be moved to the processing sites, which for 

those in the dry room means through a separate air lock for materials transfer. One-third of the 
36 

total space for Inter-Process Materials Handling is within the dry-room for the baseline plant and 

also for all other plants. The estimated resources to meet these needs are the following: 

Materials Handling Rate Factor Direct Labor Capital Equip.* Plant Area, m2

 8,170,000 

m

2

/y cell area 

4 per shift 1.5 mil$ total 600 

*Total cost including installation 

4.3.6 Electrode Slitting 

The coated electrode foils are slit into strips between the coated sections and then into individual 

electrodes as shown in Fig. 2.2. The estimated scrap loss of foil for this process is about 8%. The 

estimated resources to meet these needs are the following: 

Electrode Slitting Rate Factor Direct Labor Capital Equip.* Plant Area, m2

 8,170,000 

m

2

/y cell area 

4 per shift 2.0 mil$ total 200 

*Total cost including installation 

4.3.7 Final Electrode Drying 

In the absence of electrolyte, no harm is done by exposing the electrodes to normal factory air; 

however, the electrodes must be dried by heating under vacuum prior to cell assembly. 

Maintaining extremely low moisture conditions during cell assembly is believed to be very 

important in achieving long battery life. The final drying step coupled with dry room conditions 

ensures a minimal quantity of moisture will exist in the final product. The pertinent processing 

rate in determining the resources necessary for drying is the total amount of active materials 

processed per year (other electrode materials are approximately proportional), which for the 

baseline plant is 2,950,000 kg/y or 3,275 kg/shift. The individual electrodes exiting from the 

electrode slitting process are separated into stacks by polarity, loaded into vacuum drying ovens, 

dried for several hours, and unloaded directly into the dry room. The estimated resources to meet 

these needs are the following: 

Electrode Drying Rate Factor Direct Labor Capital Equip.* Plant Area, m2

Dryer capacity 

Number of dryers 

Maximum rate 

2,950,000 kg/y 

active material 

2 per shift 1.6 mil$ total 

600 kg/shift 

8 

4,320,000 kg/y 

200 

*Total cost including installation 

4.3.8 Control Laboratory 

The purpose of the control laboratory is to ensure that the raw materials and the electrodes being 

fabricated meet specifications. Laboratory personnel collect or supervise collection of samples 

and carry out analyses. The estimated resources to meet these needs are the following: 
37 

 Rate Factor Direct Labor Capital Equip.* Plant Area, m2

Control Lab 869,000 kWh/y 4 per shift 1.5 mil$ total 200 

*Total cost including installation 

4.3.9 Cell Stacking 

The cells are assembled in four steps, which are carried out in a dry room. The first of these steps 

is cell stacking. The primary rate factor that determines the cost for all steps in cell assembly is 

the number of cells assembled per year. For cell stacking an additional cost factor is the capacity 

of the cells; large cells usually require more electrodes of larger area and thus a more capable, 

faster cell stacking machine. The method used to determine the extra costs of stacking equipment 

in detailed in Table 4.3. The capacity of the cells is deemed to have only a minor effect on the 

other steps in cell assembly and is not taken into account for those steps. The electrodes are 

inserted in a folded separator sheet, the positive electrodes tabs protrude on one side and the 

negative electrodes tabs on the other. As in other parts of the plant, excess capacity is provided to 

allow catching up after unscheduled downtime. The estimated resources to meet these needs for 

the baseline plant are the following: 

Cell Stacking Rate Factor Direct Labor Capital Equip.* Plant Area, m2

 Stacking rate 

 Number of units 

 Maximum rate 

6,320,000 cells/y 6 per shift 5.0 mil$ total 

4 cells/min 

5 

8,640,000 cells/y

400 

*Total cost including installation 

4.3.10 Current Collector Welding 

The current collector tabs for the negative and positive electrodes are welded to their respective 

terminals by ultrasonic welding. This procedure achieves a connection of near-zero resistance 

and avoids overheating the electrodes during the welding process. The estimated resources to 

meet these needs are the following: 

Tab Welding Rate Factor Direct Labor Capital Equip.* Plant Area, m2

 

 Cell rate 

 Number of units 

 Maximum rate 

6,320,000 cells/y 6 per shift 5.0 mil$ total 

4 cells/min 

5 

8,640,000 cells/y

400 

*Total cost including installation 

4.3.11 Enclosing Cell in Container 

The aluminum foil in the pouch container is sufficiently thick (100 microns default thickness) to 

permit the use of stiff, pre-shaped pouch halves. The pouches are assumed to be purchased as 
38 

finished parts. Each cell is enclosed in these containers, which are then partially sealed prior to 

injecting electrolyte. The estimated resources to meet these needs are the following: 

Enclosing cells Rate Factor Direct Labor Capital Equip.* Plant Area, m2

 Cell rate 

 Number of units 

 Maximum rate 

6,320,000 cells/y 4 per shift 3.0 mil$ total 

4 cells/min 

5 

8,640,000 cells/y

400 

*Total cost including installation 

4.3.12 Electrolyte Filling and Cell Sealing 

At this station, the cells are evacuated, filled with electrolyte and temporarily sealed. The 

estimated resources to meet these needs are the following: 

Filling & 1st Seal Rate Factor Direct Labor Capital Equip.* Plant Area, m2

 Cell rate 

 Number of units 

 Maximum rate 

6,320,000 cells/y 6 per shift 6.0 mil$ total 

4 cells/min 

5 

8,640,000 cells/y

600 

*Total cost including installation 

4.3.13 Dry Room Management 

Excellent dry-room atmosphere is required for lithium-ion cell assembly. A maximum dew point 

temperature of –40 °C is maintained in the room. The load on the dry-room drying apparatus is 

determined by diffusion of water vapor through the walls, entry of air through the air locks, the 

number of workers in the room, and the need to admit some fresh air to limit the build up of 

contaminants such as electrolyte solvent vapor. These load factors are approximately a function 

of the room area. Because of the importance of the proper functioning of the dry room, two 

workers are on duty at all times to monitor its performance. The equipment for circulation and 

purification of the dry air will be located outside of the plant building, adjacent to the dry room. 

The estimated resources to meet these needs are the following: 

 Operating 

Area 

Direct Labor Capital Equip.* Air Locks, m2

Dry Room 2,000 m2 2 per shift 20.0 mil$ total 75 

*Total cost including installation 

4.3.14 Formation Cycling, Final Cell Sealing and Charge Retention Testing 

Formation cycling is expensive because it takes considerable time and each cell must be 

monitored separately. For plants to be operated in 2020, we expect some improvements from 

present day operations because of the urgency to improve and thus save cost. We project that the 

entire formation cycling and testing can be done in two shifts. These operations consist of 
39 

charging the cell, discharging to full depth to measure capacity and impedance, followed by fully 

recharging the cells. These tests will be carried out in large temperature controlled cycling units 

that test 500 cells simultaneously, monitor each cell and automatically identify failed cells. The 

capital cost of the cycling equipment is primarily a function of the annual number of cells to be 

tested, but to a lesser extent on the capacity of the cells. 

The short-term testing described above does not detect cells that have self-discharge rates that 

are slightly above normal, which could lead to catastrophic failures later. To detect such defects, 

the cell charge is topped off and the cells are stored for two weeks and then checked for loss of 

charge. Most of the test period is spent in large racks in compact arrays, without electronic 

monitoring. Incidentally, the two-week long self-discharge testing requires less floor space than 

for formation cycling, which lasts only two shifts.

The final cell sealing occurs between the formation cycling and charge-retention storage test. 

Gas generated during formation cycling may accumulate in the reservoir space that was created 

during the temporary sealing step. This gas is removed by creating the final seal below the 

reservoir and trimming off the unwanted portion. 

 

The estimated resources to meet these needs are the following: 

 Rate Factor Direct 

Labor 

Capital Equip.* Plant Area, 

m

2

Formation Cycling 

 Cell capacity 

 Number of cyclers 

 Cells per cycler 

 Length of test 

 Testing capacity 

6,320,000 cells/y 8 per shift 30.0 mil$ total 

40 Ah 

35 

500 

2 shifts 

7,875,000 cells/y

1500 

Final Cell Sealing 6,320,000 cells/y 2 per shift 2.0 mil$ total 300 

Charge Retention 

 Testing rack capacity 

 Racks per stack 

 Number of racks 

 Length of test 

 Testing capacity 

6,320,000 cells/y 3 per shift 4.75 mil$ total 

500 cells 

5 

750 

14 days 

8,040,000 

600 

*Total cost including installation 

4.3.15 Module and Battery Assembly 

Approximately 5% of the cells are expected to fail the formation cycling and charge-retention 

tests and these are sent to the Rejected Cell and Scrap Recycle section. The accepted cells 

(6,000,000 finished cells per year) are assembled into modules by attaching the terminals 

through laser welding or mechanical joining with spring loaded devices. Electronic circuit packs 

are attached that occupy about the same volume as a cell. These operations are carried out at four 
40 

automated stations each capable of handling about 280 cells per hour. For the module design 

being cost estimated in this model, the module is enclosed in an air-tight aluminum container by 

double seaming. The processing rate that determines the cost of module assembly is the number 

of finished cells that must be handled per year. 

The finished modules are assembled into battery packs with the aid of automated stations. The 

total cost of these stations is dependant mainly on the number of battery packs to be assembled 

per year (100,000 for the baseline plant), but to a lesser extent on the number of modules per 

pack. After assembly, the packs are moved to testing stations where they are discharged as a final 

check of impedance and to lower the state of charge to a level suitable for shipping. The 

estimated resources to meet these needs are the following: 

 Rate Factor Direct 

Labor 

Capital Equip.* Plant Area, 

m

2

Module Assembly 

 Number of stations 

 Cells/h/station 

 Capacity 

6,000,000 cells/y 6 per shift 6.0 mil$ total 

4 

280 

8,060,000 cells/y 

400 

Battery Pack Assembly 

 Modules/pack 

 Number of stations 

 Packs/h/station 

 Capacity 

100,000 packs/y 4 per shift 3.0 mil$ total 

4 

3 

6 

130,000 packs 

300 

Battery Pack Testing 100,000 packs/y 2 per shift 3.0 mil$ total 300 

4.3.16 Rejected Cell and Scrap Recycle 

Scrap is generated in preparing the electrodes and by the rejection of 5% of the cells that go 

through formation cycling and charge-retention tests. This scrap is gathered and packaged for 

shipment for recycling of the materials having value. No credit is taken for the value of the scrap 

in this model except that the costs of gathering, sorting, packaging and shipping are understated 

by about that value. The main factor in determining the cost of scrap recycle is the number of 

cells rejected, which have to be disassembled to recover the scrap, a labor intensive process. The 

yields of materials in the various processing steps are shown in Table 4.4. 

Table 4.4 Materials yields during electrode and cell fabrication 

Material Material

Mixing 

Coating Electrode

Slitting 

Cell 

Stacking

Electrolyte

Filling 

Total 

Positive Electrode 99 95 99 99 92.2 

Negative Electrode 99 95 99 99 92.2 

Positive Current Coll. 99 92 99 90.2 

Negative Current Coll. 99 92 99 90.2 

Separator 98 98.0 

Electrolyte 94 94.0 
41 

The estimated resources needed for scrap recycle are the following: 

 Rate Factor Direct 

Labor 

Capital Equip.* Plant Area, m2

Scrap Recycle 

 Scrap rate 

6,320,000 cells/y 5 per shift 2.5 mil$ total 

441 kg/shift 

400 

4.3.17 Baseline Plant Summary 

The processing rates and the primary cost factors for the baseline plant are summarized in Table 

4.3. The main cost-determining rate of processing for each step is shown in the second column. 

The requirements for direct labor, capital equipment and plant area, which are shown in detail in 

the subsections above, are summarized in the table. It is seen that the plant requires a total of 95 

workers per shift, $130,450,000 worth of capital equipment, and 10,325 square meters of plant 

area to manufacture the baseline battery at a rate of 100,000 battery packs per year. 

4.4 Adjustment of Costs for Rates Different than those of the Baseline Rates 

As noted in Table 4.3, there are many processing rates that must be considered in addition to the 

overall number of battery packs manufactured per year. Each of these rates affects the costs of 

one or more steps in the process and may have no effect upon the costs of other steps in the 

process. For instance, when the user of the model increases the power of the battery packs 

without increasing the number of cells or their capacity, the model increases the area of the cells 

and decreases the electrode coatings thicknesses. Such changes would result in an increase in the 

cost of the coating equipment, the floor area occupied by the equipment, and in the direct labor 

for that step in the process. It would have no effect on the cost of mixing the materials to be 

coated because the amounts of these materials per battery back are unchanged under the assumed 

conditions. 

The general approach to cost estimation of multiplying a known cost by the ratio of processing 

rates raised to a power has also been applied to the capital cost of individual items of 

equipment.24

C = Co(R/Ro)

p

 (4.1) 

Here, Co is the capital cost of an installed equipment item designed for the baseline processing 

rate, Ro. The power factor, p, relates the capital investment cost and the processing rate for the 

manufacturing step. 

 

If the value of p were 1.0, it would imply that the cost of the equipment item, or the equipment 

items if there are several in parallel, would be directly proportional to the processing rate. 

However, the value of p for the cost of equipment is frequently about 0.6 to 0.7 for many 

manufacturing process steps because the equipment is larger for the higher processing rates and 

its cost is less than if it were directly proportional to the processing rate. For process steps 
42 

requiring the addition of many identical pieces of equipment for scale up, such as may be true for 

formation cycling of battery cells, the value of p may be as high as 0.9. The value of p is unlikely 

to reach 1.0 because the equipment cost includes installation, for which there is some savings 

even in installing multiple units of the same processing capacity. The relationship between cost 

and processing rate for two-fold and three-fold rate changes is illustrated in Table 4.5. 

Table 4.5 The effect of processing rate (R) on cost for various scale factors 

C/Co = (R/Ro)

p

 Cost Ratio, C/Co

Scale Factor, p R/Ro = 2 R/Ro = 3 

0.25 1.19 1.32 

0.3 1.23 1.39 

0.4 1.32 1.55 

0.5 1.41 1.73 

0.6 1.52 1.93 

0.7 1.62 2.16 

0.8 1.74 2.41 

0.95 1.93 2.84 

1.0 2.00 3.00 

Similar equations have been applied for determining the effect of processing rate on the annual 

hours of labor and the plant area required for a manufacturing step. In general, the value of p is 

low for the labor equation, usually only 0.4 to 0.5, because only a relatively small addition to the 

labor crew permits operation of larger equipment or of operating several more units of the same 

processing capacity.24 The value of p for the plant area required for a processing step is slightly 

less than that for equipment. The floor area required for larger equipment or for more equipment 

items of the same size is proportionately less than the increase in the processing rate because of 

the more efficient use of the space occupied by the equipment and the savings in aisle area. 

The value of the scale factors (i.e. p factors) for labor, capital equipment, and floor area were 

estimated for each of the processing steps (Table 4.3). The scale factors selected for the direct 

labor requirement are usually only 0.4 to 0.5, which indicates considerable unit cost reduction for 

increasing the plant throughput. 

For most processing steps, increasing the processing rate beyond that in the baseline plant would 

result in a decision to increase automation or use faster equipment to mitigate the costs of higher 

levels of throughput. Decreasing the processing rate would have the opposite effect. Some steps 

in the process such as cell stacking, welding of current collectors, and formation cycling do not 

appear to be easily automated beyond the level intended in the baseline plant and, thus require a 

higher value for the scale factor of 0.8. This higher scale factor results in achieving fewer 

reductions in the cost per battery pack with increasing production volume. Additionally, a higher 

p factor results in a less severe penalty for lower production scale for an individual step in the 

process. 
43 

There are five steps for which the cost of the capital equipment is affected by other factors than 

the main processing rate for the process step. These are discussed in the footnotes at the bottom 

of Table 4.3. For these steps, the costs that have been adjusted for the changes in the processing 

rate from the baseline rate are further adjusted to take into account the other cost factors. The 

cost of the coating equipment is adjusted for the amount of solvents to be driven off of the 

positive and negative electrodes; thicker coatings need longer, more expensive ovens to drive off 

the additional binder solvent or the coater most be operated at lower speeds. The cost of the cell 

stacking equipment and that of the formation cycling equipment, for which the main cost factor 

in both cases is the number of cells to be fabricated annually, are also adjusted for the capacity of 

the cells; larger cells require more expensive equipment. The cost of the capital equipment for 

battery assembly is primarily a function of the number of cells in the battery, but it is also a 

function of the number of modules that must be interconnected. This dependence is accounted 

for in the model with an additional multiplying factor. 

A breakdown of the baseline plant capital equipment costs listed in Table 4.3 is illustrated in Fig. 

4.3. The largest costs for capital equipment are for formation cycling and testing, cell assembly 

in the dry room and electrode coating. These capital costs are likely to be dominant in any 

lithium-ion battery plant in the near future. 

Receiving and shipping

Materials preparation

Electrode coating

Calendering

Materials handling

Electrode slitting

Vacuum drying

Control laboratory

Cell assembly in dry room

Formation cycling and testing

Module and pack assembly

Rejected cell and scrap recycle

Figure 4.3 Breakdown of installed capital equipment costs for the baseline plant 

4.5 Plant Investment Costs 

In this model, the calculated investment costs are defined as those directly related with building 

and operating the plant (Table 4.6). Other costs that may require investment, such as research 
44 

and development, are added separately to the unit cost of the battery. The largest investment cost 

is for the installed capital equipment. Each cost item for the battery under design is adjusted from 

the estimate of the baseline plant. The plant cost is done in a similar way with a cost of $1,500 

per square meter ($140/sq. ft) including land and utilities. Launch costs include plant start-up, 

employee training and materials that are lost or recycled in early stages of production, beyond 

the normal amounts. Launch costs are estimated to be 5 % of annual materials costs plus 10 % of 

annual direct labor and variable overhead (Section 4.6). Working capital is needed to cover the 

costs of payroll, receivables, and the inventories of raw materials, work in progress and finished 

product. These working capital costs are partially offset by bills that are payable. We estimate 

the working capital to be 15 % of the annual variable costs. 

Table 4.6 Battery pack manufacturing investment costs 

Investment Costs Description Method of Calculation 

Capital Equipment Equipment costs including 

installation 

Estimates of costs for each 

processing step at baseline rates 

adjusted for actual rates. 

Plant Floor Space Space includes aisles and space 

for unfinished processing 

inventory plus land and utility 

costs. 

Estimates of costs for each 

processing step at baseline rates 

adjusted for actual rates. 

Launch Costs Plant start-up, training, out-ofspec product. 5% of annual materials cost, 

10% of direct labor plus 

variable overhead. 

Working Capital Cash to meet payroll, 

receivables, inventories of raw 

materials and of unfinished and 

finished product, minus 

payables. 

15% of annual variable costs. 

4.6 Unit Costs for Battery Pack 

The unit costs of the battery pack are calculated as summarized in Table 4.7. 

4.6.1 Variable Costs 

The costs of the materials and purchased items are based on the costs discussed in section 4.2, 

and the annual amounts of materials are adjusted for the yields of materials (section 4.3) and 

yield of cells. The direct labor is the sum of the labor cost for each step in the process, which are 

each calculated for the baseline plant and adjusted for the rate associated with the battery under 

study. Variable overhead is the cost of indirect materials and labor, utilities, and plant 

maintenance. It is estimated to cost 60 % of direct labor costs. 
45 

4.6.2 Fixed Expenses 

Fixed expenses include General, Sales, and Administration (GSA), research and development, 

and depreciation. The cost of GSA includes the plant office, taxes on income and property, cost 

of sales and insurance. It is estimated by the model as 25 % of direct overhead plus 35 % of 

depreciation. Research and development (R&D) must be carried out to ensure that the battery 

packs that are produced in the plant and the means of production continue to be competitive in 

the world market with respect to performance and price. The greater the investment in the plant 

and its equipment, the greater is the need to be successful in the R&D effort. Thus, the 

expenditure has been set at 50 % of the depreciation expense. Depreciation expense provides 

funding available for future investment in this plant or another venture to replace deteriorating 

plant and equipment. The equipment and plant are depreciated at straight-line rates for 8-year life 

(12.5 % per year) and 20-year life (5 % per year). 

Table 4.7 Unit cost of battery pack 

Variable Costs Description Method of Calculation

Materials and Purchased 

Items 

All materials and purchased 

items in finished product and 

lost in processing. 

Based on prices of materials, 

cost equations for purchased 

items and yields. 

Direct Labor Labor costs for operations and 

immediate supervision. 

Estimates of costs for each 

processing step at baseline rates 

adjusted for actual rates. 

Variable Overhead Indirect materials, labor, 

utilities, plant maintenance 

60% of direct labor cost. 

Fixed Expenses 

General, Sales, and 

Administration (GSA) 

Plant office, taxes on income 

and property, cost of sales and 

insurance expenses. 

25% of direct labor and variable 

overhead plus 35% of 

depreciation. 

Research and Development On-going research needed to 

upgrade product and maintain 

competitive position. 

50% of depreciation 

Depreciation Provides funds for new 

investments to replace those in 

current equipment and plant. 

12.5% of capital equipment cost 

plus 5% of plant floor space 

cost. 

Profit Return on invested capital after 

taxes. 

5% of total investment costs. 

Warranty Funds set aside for reimbursing 

customers for battery pack 

failures. 

5.6% added to price based on 

present worth of projected 

payments. 
46 

4.6.3 Profits 

The profit goal for this type of venture varies with the financial structure of the company, 

especially regarding long-term debt. For the model, the profit is set to provide a 5 % return on 

the total investment, which is an approximate average for mature manufacturing as vehicle 

battery production is expected to be in 2020. 

4.6.4 Battery Pack Warranty Costs 

If a battery module or an entire pack fails, the replacement will cost much more than the original 

price paid by the OEM. It is important that such events are rare, but provision must be made to 

reimburse the vehicle owner, especially in the early years of the projected battery life. The extra 

costs of replacing the battery will result from labor for testing and replacing the battery, 

inventory costs for stocking replacement batteries, and servicing the battery controller if the new 

battery is slightly different than the old battery. It is likely that the battery manufacturer will be

responsible for the cost of the new battery, which we assume will be equal to the cost of the 

original battery. The other costs of replacing the battery, to the extent that they are covered by 

the warranty, are assumed here to be covered by the automobile manufacturer and the dealer. 

The goal for average battery life is 15 years and a warranted life of 10 years, with full 

replacement in the first five years and shared cost of replacement for the last five years seems 

appropriate. The vehicle owner would pay an increasing share of the cost from between 0 % at 5 

years to 100 % at 10 or more years. With these assumptions, the cost to the battery manufacturer 

will be equal to the present worth of the future costs of the new battery or modules as provided in 

the warranty. The rate of battery failure will vary over the life of the battery with a slightly 

higher rate early in life, then a low failure rate followed by a gradually increasing failure rate. 

For purposes of calculation we assume a failure rate of 1.0 % per year throughout the warranty 

period. With an internal rate of return of 8 % and calculated on a monthly basis, the present value 

of the future costs would be about 5.6 % of the price of the battery before adding the warranty 

cost. 

4.7 Summary of Baseline Battery Cost 

The spreadsheet version of the model, which is discussed in more detail in sections 5 and 6, 

provides a summary sheet which is illustrated in Table 4.8 for the cost of the baseline battery and 

that of two others. This breakdown of the battery costs, with a brief summary of the design 

values, illustrates the effects of the cost factors. The second battery has twice the power of the 

baseline battery and the third battery has the same power as the baseline battery, but twice the 

capacity. The number of cells is the same for each battery. The energy storage is slightly higher 

for the battery with double power because the voltage would be slightly higher during the 

discharge to determine capacity. The battery with double the capacity has fewer electrodes which 

are longer and wider, because the cell thickness in maintained, resulting in higher resistance in 

the current-collector structure. The higher impedance lowers the voltage during the discharge 

capacity measurements and results in slightly less than twice the energy storage of the baseline 

battery. 
47 

Baseline Double Power Double Capacity

Calculated Battery Parameters

Battery energy storage, kWh 8.7 8.8 17.1 

Battery power at 80 % OCV, kW 50.0 100.0 50.0 

Required battery power, kW 50.0 100.0 50.0 

Capacity, Ah 40 40 80 

Number of cells 60 60 60 

Battery weight, kg 69.2 55.8 96.9 

Battery volume, L 42.0 35.9 58.3 

Vehicle electric range, miles 24.3 24.6 47.9 

Investment Costs

Capital equipment cost including installation, mil$ 149 130 152 

Building, Land and Utilities

 Area, m2

 12,193 10,325 11,744 

 Cost, $/m2

 1,500 1,500 1,500 

 Building investment, mil$ 15 18 18 

Launch Costs 13 10 15 

Working capital, mil$ 36 28 42 

Total investment, mil$ 216 184 227 

Unit Cost of Battery Pack, $

Variable Cost

Materials and Purchased Items 

 Cell materials 1,864 1,350 2,232 

 Cell purchased Items 75 75 90 

 Module and battery 234 228 276 

 Total 2,173 1,652 2,598 

Direct Labor

 Electrode processing 52 36 40 

 Cell assembly 31 31 31 

 Formation cycling, testing and sealing 17 17 17 

 Module and battery assembly 16 16 16 

 Rejection and recycling 6 6 6 

 Receiving and shipping 8 8 11 

 Control laboratory 5 5 7 

 Total 135 119 128 

Variable Overhead 72 81 77

Total Variable Cost 1,843 2,389 2,803

Fixed Expenses

General, Sales, Administration 107 122 121

Research and Development 85 98 99

Depreciation 171 195 199

Total Fixed Expenses 364 415 419

Profits after taxes 92 108 113

Total unit cost per battery not including warranty, $ 2,299 2,912 3,335

Summary of Unit Costs, $

Materials 1,864 1,350 2,232 

Purchased Items 309 303 366 

Direct Labor 135 119 128 

Variable Overhead 81 72 77 

General, Sales, Administration 107 122 121 

Research and Development 85 98 99 

Depreciation 195 171 199 

Profit 108 92 113 

Warranty 163 129 187 

Price, $ 3,075 2,428 3,522 

Table 4.8. Summary of results for cost of baseline battery and that of similar batteries 

with double the power and double the capacity of the baseline battery
48 

Doubling the power does not add as much cost to the materials and purchased parts as doubling 

the cell capacity. Most of the labor costs for the three batteries are similar with the major 

difference being for the labor cost for electrode processing. The double power battery requires 

greater labor costs principally for coating the larger electrode area. Capital equipment and 

depreciation costs are higher for both the high power and high capacity battery packs. The 

increases in capital equipment cost for the high-power battery are for coating, calendering, 

materials handling and vacuum drying equipment. For the high-capacity battery, the main 

additional capital equipment costs are for the materials mixing, binder solvent recovery, cell 

staking and formation cycling steps in the process.

Overall, doubling the power of the battery increases the cost by only 27 %. Doubling the 

capacity of the cells increases the cost by 45 %, considerably more than for doubling the power. 

Alternatively, doubling the number of baseline cells and modules within a larger battery jacket 

(two rows of modules instead of one, twice the voltage, energy, and power) would increase the 

cost by 83 %. 

The summary of unit costs for the baseline battery pack, which is shown at the bottom of Table 

4.8, is illustrated in Fig. 4.4. The materials and purchased items are the largest costs for the 

battery. For larger levels of production, these costs are even more dominant because the scale 

factors for these items are close to one. 

Figure 4.4 Breakdown of unit costs for baseline battery with total price to OEM of $2428. 

56%

12%

5%

3%

4%

4%

7%

4% 5%

Materials

Purchased Items

Direct Labor 

Variable Overhead 

General, Sales, Administration

Research and Development

Depreciation

Profit 

Warranty
49 

5 Description of the Spreadsheet Model and Instructions for Use 

5.1 Background 

Historically, the model has been based on Microsoft® Office Excel spreadsheets. The flexibility 

afforded by a spreadsheet approach has been extremely useful to the development of the 

calculations. Until now, the model had been in a constant state of development. Changes to 

parameters and equations were made rapidly and frequently. The publication of this report 

represents the first time a version of the model will be “frozen” for open distribution to the 

public. Advances will continue to be made with the model, such as those discussed in the last 

section of this report. However, distributions of the revised model will be made in an orderly 

fashion rather than the continuous improvement approach taken over the last number of years. 

5.2 Instructions 

The following subsections are a brief explanation of how one may operate the spreadsheet based 

model. The user is advised to save the original document separately as a back-up copy. 

Corruption of the calculation is possible and will likely occur during use by someone unfamiliar 

with the model. 

5.2.1 Enabling Calculation 

This Microsoft® Office Excel workbook requires the use of iteration. To enable this feature, go 

to the “Tools” drop-down menu and select “Options.” On the calculation tab, check the box next 

to “Iteration” and change the maximum number of iterations to 1000 (Figure 5.1). Also ensure 

the calculation is set to automatic and not manual. If the iteration is not turned on, the software 

will present an error complaining about circular references. 

Figure 5.1 Iteration must be enabled for the spreadsheet model to function. 
50 

5.2.2 System Selection Worksheet 

The cell chemistry is selected by copying the system designated at the top of a column, for 

instance NCA-G in cell F3, pasting it into cell E3 (Figure 5.2). Any of the values in row E can be 

overridden by entering the desired value in column L. The selection of the cell chemistry also 

includes the associated prices at the bottom of the page. These prices can also be overridden by 

entering the desired values in column L. A full screen shot of the system selection worksheet is 

in Figure 5.3. 

Figure 5.2 The specific cell chemistry for the battery design is selected on the System Selection 

worksheet. Any value may be overridden by entering a value in column L. 

 

5.2.3 Battery Design Worksheet 

The Battery Design worksheet designs five or more batteries for any type of electric-drive 

vehicle (Figure 5.4–5.6). The calculated designs are specific for the end batteries requirements 

specified by the user. From the result, the amounts of materials and the purchased items required 

for manufacture are easily available to be used in the manufacturing cost calculations found on 

subsequent worksheets. Although a cell and module format is assumed, the exact format 

(prismatic, pouch, can, etc) of the battery does not have a dominant effect on the cost for a set 

cell chemistry system. Our experience teaches us that the amounts of electrode materials and the 

number, capacity and electrode area of the cells, are the determining cost factors. Nevertheless, a 

specific design format was selected and is shown on the Cell Design worksheet to provide a basis 

for calculating the entire cell and battery related costs. 
51 

Figure 5.3 System Selection worksheet 
52 

Figure 5.4 Top portion of Battery Design worksheet. 
53 

Figure 5.5 Middle portion of Battery Design worksheet 
54 

The Battery Design worksheet automatically receives input from the System Selection 

worksheet. These values are shown in purple (Figures 5.4 and 5.6) and must not be altered on the 

Battery Design worksheet. As explained above, cell chemistry values may be adjusted on the 

System Selection worksheet. The operator provides battery design input in the aqua colored cells 

(Figures 5.4 and 5.6). It is expected that the default values for the cell design (lines 27 to 30) and 

the thickness of the battery insulation (line 57) should serve well for most batteries. The battery 

input parameters on lines 50 to 54 (Figure 5.4) and lines 141 to 143 (Figure 5.6) are the only 

input values that the operator is required to provide to study a group of batteries. An important 

variable is the type of vehicle battery, (microHEV, HEV-HP, PHEV, or EV) on line 48 in Figure 

5.4. One performs the selection by typing the name of the vehicle battery type in cell F48. While 

the correct spelling is important, capitalization is not. This selection automatically determines the 

state of charge at which full power is designated (thus, the open-circuit voltage and ASI for full 

power) and the length of the power burst (2 seconds for microHEV and 10 seconds for all 

others). 

The cell capacity (lines 141 to 143 in Figure 5.6) can be set in any of three ways: (1) directly 

specifying the capacity (Ah) on line 141, (2) specifying the total battery energy on line 142 or (3) 

specifying the electric range of the vehicle (miles). Only one of the three lines should be filled in 

and the others should be blank. The model will follow the directions of the top-most line with 

non-zero values. 

The number of batteries manufactured per year is selected on line 59 in Figure 5.4. Changing this 

value from the default value of 100,000, which is the manufacturing rate for the baseline plant, 

will change the manufacturing cost. 

If it is desired to study more than five batteries in the same workbook it is only necessary to add 

additional columns by copying the battery 5 column to the right as many times as desired. Care 

should be taken that the appropriate values are maintained when the cells are copied over. The 

aqua colored cells are typically the source of any problems. The same column additions most 

also be done for the worksheets on Summary of Results and Manufacturing Cost Calculations. 

5.2.4 Remaining Worksheets 

The cost calculations are done on the Manufacturing Cost worksheet and the results for the 

model are shown on the Summary of Results worksheet (Figure 5.7). No parameters need to be 

entered on these worksheets by the operator; all of the input for these worksheets is from the 

Battery Design and the Cost Input worksheets. Tables for presentations or for preparing graphs 

of the data can be assembled at the bottom of either the Battery Design or the Summary of 

Results worksheet. These tables can be transferred to a blank worksheet for more complex 

studies. For instance, results for different cell chemistries can be copied and pasted (special 

paste, values and numbers formats) to a blank worksheet. Preparing a chart has been illustrated 

in the initial configuration by graphing the data tabulated at the bottom of the Battery Design 

worksheet. The X-axis description will have to be adjusted if the cell capacity is selected by one 

of the alternative methods. On the last two worksheets, the cell design and the baseline plant are 

sketched. 
55 

Figure 5.6 Bottom portion of Battery Design worksheet 
56 

Figure 5.7 Summary of Results worksheet 
57 

5.3 Battery Design Format Requirements 

As the battery design is based off an assumed format (Section 2), certain design requirements are 

necessary to ensure the modeled battery is physically realistic. For a battery based on a single 

module, no additional restrictions are required. However, most batteries for transportation 

applications will use multiple modules. For these applications, the following rules should be 

followed by the user of the model. An even number of cells should compose each module and an 

even number of modules should compose each battery pack. These two requirements are to 

ensure the electrical connections are in the appropriate places in the final battery pack. Finally, 

the dimensions of the resulting battery pack should be examined. Some final designs may benefit 

from changing the cell aspect ratio, H/W, to fit the end-use application. One example would be, 

to change the height of the battery pack. Also, for a set number of cells in the pack, changing the 

number of modules, thus cells per module, allows for adjustment of the pack dimensions. 

5.4 Troubleshooting and General Advice 

The spreadsheet iterates to find the solution and this sometimes causes error messages to appear 

after an entry is changed. These errors can usually be removed by first correcting any erroneous 

entries (non-numeric, two decimal points, etc.). Then the cells may be reset to default values by 

entering a “0” (i.e. zero) in the restart cell, F149 in Figure 5.6. Finally, entering a “1” in F149 

restarts the iteration process leading to a successfully converged answer. 

At some point, a user will ask the model to design a battery that is outside the bounds of what is 

allowable for the selected cell chemistry. The most common error is when too large of a P/E ratio 

is requested. Two different physical limitations are approached with increasing P/E ratio. First, 

the electrode thickness is shrinking. At some point, the value will become unrealistic and 

eventually approach 0 crashing the calculation. At the same time, the C-rate for the active 

material is approaching the limiting C-rate defined in the Cell Chemistry Worksheet. As this 

value is approached, the ASI will increase to larger and larger values, which thus demands 

smaller and smaller electrode thicknesses. Eventually, the calculation will crash. 

Common sense approaches to resolve these issues are to use lower designed power or higher 

designed energy. The C-rate and electrode thickness are easily viewed in the model output. 

These are found on the Battery Design worksheet in row 120 for the C-rate and rows 81 and 82 

for the electrode thickness. Therefore, the user may try designs of increasing P/E ratios and 

watch to see how the electrode thickness and C-rate is changing. Different cell chemistries will 

have different sensitivities to the P/E ratio depending on the defined limiting C-rate and 

calculated ASI for power. What is possible with the LMO-G system will not always be possible 

with the NCA-G system. P/E ratios that satisfy the expression in Eq. 5.1 generally result in 

successful battery designs. Higher P/E ratios are allowable in some situations. Note that selecting 

the microHEV design doubles the allowable C-rate since only two second pulses are used. The 

limiting C-rate, rC,lim, may be found in cell E48 on the System Selection worksheet and is carried 

over to row 71 in the Battery Design worksheet. 

1.35

C lim,

r

E

P

< (5.1) 
58 

6. Illustrated Results

The model may be used to study the effects of battery parameters on the performance and the 

manufactured cost of the designed battery packs. A few examples are given below for the effects 

of various parameters on battery pack volume, weight and cost. 

6.1 Number of Cells in Series 

For a set battery pack power, the number of cells in the pack has substantial effects on the price 

of the pack, the pack voltage and the maximum current. These effects are illustrated (Figure 6.1) 

for LMO-Gr PHEV20 batteries (providing 20-mile electric range) with 60-kW power. The price 

of the battery increases by 26% in changing the number of series-connected cells in the pack 

from 32 to 96. The change in the maximum current would also affect the cost of the motor and 

the electronic converter and controller, but in the opposite direction. As a result of these 

offsetting effects on the total cost of the electric drivetrain, a study needs to be done to determine

the optimum current at maximum power as a function of the total battery pack power and other 

parameters (see the Future Work section). 

0

500

1,000

1,500

2,000

2,500

0 20 40 60 80 100 120

Number of Cells per Pack

Price to OEM ($)

0

200

400

600

800

1,000

Pack Current (A) and Voltage (V)

Price

Max Current

Voltage

Figure 6.1 The effect of the number of series-connected cells for LMO-Gr, 60-kW, PHEV20 

packs with 7.14 kWh total energy (70% useable). 

6.2 Battery Packs for HEVs 

Lacking a definitive study on the cost of the entire drivetrain to establish the appropriate 

relationship for battery current, voltage and power, Equation 6.1 is employed in the HEV 
59 

examples that follow. Equation 6.1 strikes a balance between very high current and a large 

number of cells, to aid in selecting the number of cells for a battery of 25 to 150 kW of pack 

power: 

Battery Current at full Power (A) = 1.5 x Power (kW) + 200 (6.1) 

The number of cells required to match this relationship will differ for each cell chemistry to 

match the cell open-circuit voltage and impedance of the cell. Also, the selection of the current 

by this means is only approximate because the voltage is not continuous being defined in terms 

of a discrete number of cells, which must be an even number for the module design in the model 

except for single-module battery packs. 

Low-powered (25-kW) battery packs for HEVs need to deliver only about 0.15 to 0.25 kWh of 

energy or a total of about 0.6 to 1.0 kWh. Thus, a cell chemistry that is capable of a high P/E 

ratio is paramount for these batteries in achieving minimum cost. Some battery chemistries 

perform much better under these conditions than others as illustrated in Fig. 6.2. The number of 

cells in these single-module HEV battery packs varies from 33 to 52 to provide a maximum 

current at full power of 238 ± 2 A, in agreement with Eq. 6.1. It is apparent that the NMC-Gr and 

NCA-Gr systems studied here are not as well suited to very high P/E requirements as the other 

systems. 

0

5

10

15

20

25

30

35

40

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

Total Pack Energy (kWh)

Area-Specific Impedance, ohm-cm

2

NMC-Gr

NCA-Gr

LFP-Gr

LMO-Gr

LMO-LTO

Figure 6.2 Cell area-specific impedance (ASI) for various cell chemistries for 25-kW HEV 

battery packs delivering full power at about 238 A for 2 sec at 80% OCV 
60 

HEV battery packs of about 0.4 kWh of useable energy may be utilized for high power-assist 

applications. High-powered HEV battery packs of 40 to 100 kW may be required to deliver 

maximum power for up to 10 seconds. Also, they may be required to deliver moderate power to 

drive the vehicle electrically at 30 to 50 mph. This latter requirement would also require more 

useable energy than for the standard HEV battery pack. For this illustration of high-powered 

HEV battery packs, we have set the energy requirement at 1.6-kWh total energy and 0.4-kWh 

useable energy. For a moderate-weight sedan with an average energy requirement of 0.25 

kWh/mile, the battery pack could power the vehicle for 1.6 miles before being recharged. The 

battery pack could then be recharged in 1.2 minutes at a rate of 20 kW or at a higher rate if 

desired. 

A comparison of some of the characteristics of LMO-LTO, LFP-Gr, and LMO-Gr battery packs 

with power capabilities of 25-kW to 100-kW and with 1.6 kWh total energy is shown in Fig. 6.3. 

As the power of the battery pack is increased, we have increased the number of cells so that both 

the voltage and the current increase as determined by the relationship of Eq. 6.1. The unevenness 

in the plotted lines for pack volume results from changes in the number of modules and the 

dimensions of the packs. The volumes for these high-powered battery packs (Fig. 6.3) as well as 

their weights (not shown in Fig. 6.3) are all well below the USABC targets for 25-kW battery 

packs even though most of the battery packs are much more powerful than 25 kW. 

0

5

10

15

20

25

0 20 40 60 80 100 120

Battery Pack Power (kW)

Battery Pack Volume (L)

0

100

200

300

400

500

600

700

800

900

1000

LMO-LTO

LFP-Gr

LMO-Gr

Pack OCV

Max Current

Voltage (V) and Current (A)

Figure 6.3 Volume, voltage and maximum current for 1.6-kWh lithium-ion battery packs as a 

function of pack power for packs delivering full power for 10 sec at 80% OCV and 50% SOC. 

Battery packs have 10-mm insulation thickness. 
61 

Many factors affect the costs of manufacturing lithium-ion battery packs. For batteries of high 

P/E, the chief factors are cell chemistry and pack power as shown in Fig. 6.4, where the prices 

are plotted for the same batteries as shown in Fig. 6.3, with the addition of the NCA-Gr system. 

In our attempt to provide high power with a minimum amount of electrode materials with the 

NCA-Gr system, the area-specific impedance (ASI) became very high as the power was 

increased resulting in large cell areas and high costs (Fig 6.4). The LMO-Gr system has a 

significant cost advantage over the other systems in this illustration. These battery chemistries do 

not have the same probability of meeting the life goal of 15 years, but work is underway 

throughout the world to meet this need for all of these systems. 

0

500

1,000

1,500

2,000

2,500

0 20 40 60 80 100 120

Battery Pack Power (kW)

Price of Battery Pack to OEM ($)

NCA-Gr

LFP-Gr

LMO-LTO

LMO-Gr

Figure 6.4. Battery pack price to OEMs at 100,000 packs per year manufacturing rate for 1.6-

kWh lithium-ion battery packs as a function of pack power for the same battery packs as in Fig. 

6.3 with the addition of the NCA-Gr system. 

6.3 Battery Packs for EVs 

Lithium-ion batteries for PHEVs and EVs do not require a high P/E ratio or low ASI to meet 

their goals. The most important factors for performance are high specific capacity (mAh/g), high 

cell voltage, and high electrode density. To compare the performance of EV battery packs made 

from various Li-ion chemistries, we designed the packs to provide 150 kW of power at 80% 

OCV at a maximum current of 425 A, which is consistent with Eq. 6.1. Each pack consisted of 

four modules containing 28, 30, and 32 cells for the cell chemistries LMO-Gr, NMC-Gr, and 

LFP-Gr, respectively. These selections resulted in nominal (OCV) pack voltages of 429 to 443 V 
62 

and within 2 to 13 A of the targeted maximum current of 425 A (Eq. 6.1) for these 150 kW 

battery packs. On this basis, the NMC-Gr system has excellent power and energy density (Fig. 

6.5). The LMO-Gr system does well, despite only moderate specific capacity because of its high 

voltage. The LFP positive electrode has higher capacity than the LMO chemistry but is hindered 

by a lower cell voltage and greater electrode porosity resulting from the use of nanostructure 

particles. 

0

50

100

150

200

250

300

350

400

450

50 100 150 200 250

Electric Range, miles

Battery Pack Weight (kg) and Volume (L)

LFP (155 mAh/g)

LMO (100 mAh/g)

NMC (175 mAh/g)

Volume

Weight

Figure 6.5 Weight and volume of electric vehicle battery packs with lithium iron phosphate 

(LFP), lithium manganese-spinel (LMO) and lithium nickel-manganese-cobalt (NMC) positive 

electrodes versus graphite designed to deliver 150 kW of power at about 425 A. 

The LMO-Gr system appears to have the lowest price of the three systems in this illustration 

(Fig. 6.6). By experimenting with the parameter values, it was found that EV battery packs of the 

NMC-Gr type could match the low price of those in the LMO-Gr system. However, that would 

require that the specific capacity would be substantially increased and, more importantly, the 

cost of the NMC would have to be reduced to about $20/kg from $33/kg, perhaps by reducing 

the cobalt content and increasing the manganese level. 
63 

4,000

5,000

6,000

7,000

8,000

9,000

10,000

11,000

50 100 150 200 250

Electric Range, miles

Battery Pack Price to OEM ($)

LFP (155 mAh/g, $20/kg)

NMC (175 mAh/g, $33/kg)

LMO (100 mAh/g, $10/kg)

Figure 6.6 Battery pack price to OEM for LFP-G, LMC-G and NMC-G battery packs for same 

designs as in Fig. 6.5. 

6.4 Parallel-Connected Cell Groups and Electrode Thickness Limits 

The model also allows the user to create parallel cell groups and to set a maximum electrode 

thickness. The effect these two unique design factors have on cost are illustrated below in Figure 

6.7 for the LMO-Gr and NCA-Gr systems. In this illustration, the EV battery pack design 

parameters are 100 kW of power, 31 kWh of total energy, and 100 mile range. The nominal 

battery pack voltage (OCV at 50% SOC) is around 340 V. Two maximum electrode thicknesses 

of 100 and 200 microns are shown for the two cell chemistries. The thickness of the positive 

electrode is limiting the LMO-Gr chemistry while the thickness of the negative electrode limits 

the NCA-Gr chemistry. The LMO-Gr is the least expensive in all cases. However, the difference 

between the two chemistries lessens with smaller limiting electrode thickness. The costs will 

become even closer for lower designed P/E ratios. In general, thicker electrodes reduce the cost 

of the battery pack by lessening the amount of inactive materials used (separator, current 

collector, etc). Moving to 300 microns allows for greater savings in the LMO-Gr design but not 

the NCA-Gr design. However, a lower P/E ratio design for NCA-Gr would take advantage of 

electrode thicknesses greater than 200 microns. 

The cell capacity is shown for the NCA-Gr case limited to 100 microns. While the exact values 

will change with cell chemistry, they will all be similar. The cell capacity is reduced by one half 

as a single cell is added in parallel. This approach is commonly used by cell manufacturers and 
64 

OEMs that cannot reliably produce or successfully operate cells of high capacity for 

transportation applications (> 60 Ah). However, this approach also increases the price of the 

battery pack. In this example, the price is increased by ~ $500 when an additional string of cells 

is incorporated in a parallel arrangement. 

The model calculations show that the lowest cost battery pack will utilize thick electrodes and 

large capacity cells. In current practice, these two approaches have yet to be successfully 

implemented within the entire community. In the challenge of lowering costs, it is useful to point 

out the largest gains come from the initial advances (e.g. moving from 100 to 200 micron limit). 

After that point, the benefits are diminishing. 

2,000

4,000

6,000

8,000

10,000

12,000

0 1 2 3 4 5

Number of Parallel Cells

Battery Pack Price to OEM ($)

20

40

60

80

100

120

Cell Capacity, Ah

NCA 100 micron LMO 100 micron

NCA 200 micron LMO 200 micron

Cell capacity, Ah

Figure 6.7 Battery pack cost as a function of number of parallel cells and for different maximum 

electrode thicknesses. The cell capacity is also shown for the NCA-Gr limited to 100 micron 

electrode thickness. 

6.5 Effects of Manufacturing Scale on the Price of the Pack 

The effects of manufacturing scale come into the cost calculation even if the annual number of 

packs produced is unchanged, but the design is altered (e.g. power is increased). For a fixed 

design, the effect of changing the scale of operations depends on the fraction of the total price 

that is made up of materials costs. Unit materials costs change little with scale whereas the costs 

per pack for labor, capital and plant area may decline substantially with increasing production 

rates, especially at low production rates, Fig. 6.8. 
65 

y = 20771x-0.0862

y = 19490x-0.0906

5,000

5,500

6,000

6,500

7,000

7,500

8,000

8,500

9,000

9,500

0 100,000 200,000 300,000 400,000 500,000 600,000

Annual Manufacturing Rate (packs/y)

Price per Pack to OEM ($)

LMO-Gr, EV150 mile, 150 kW

NMC-Gr, EV150 mile, 150 kW

y = 10298x-0.1367

y = 7387.8x-0.2011

0

500

1,000

1,500

2,000

2,500

3,000

0 100,000 200,000 300,000 400,000 500,000 600,000

Annual Manufacturing Rate (packs/y)

Price per Pack to OEM ($)

LMO-Gr,PHEV20 mile, 60 kW

LMO-Gr, HEV-25 kW

Figure 6.8 The effects of manufacturing rate on the price calculated by the model for battery 

packs of various cell chemistries, power capabilities and vehicle types 
66 

The lines in the graphs are for the best-fit power relationships through the data with power 

factors of -0.086, -0.091, -0.137, and -0.201 from the top curve to that at the bottom. The least 

negative power factor is for the battery pack with the highest fraction of materials cost in the 

total pack cost. The more negative power factors result from a decreasing contribution of 

materials cost as a fraction of the total pack cost. These power factors for equations of the cost of 

a single unit can be converted to factors relating the total annual cost of manufacturing similar to 

Eq. 4.1 by adding 1.0 to each power factor. Thus the factors become 0.914, 0.909, 0.863, and 

0.799. These large factors show only a small to moderate effect of scale. When the power curves 

are compared to the points in each of the graphs of Fig. 6.8, it is apparent that the scale factors 

approach one as the scale increases. This is because the model assigns a value of 0.95 for the 

active materials and 1.0 for the balance of the materials. As the production level increases and 

the materials costs become a larger fraction of the total price of the battery, the scaling power 

approaches 1.0 and the effect of scale become very small. Likewise, the effect of scale on battery 

price is much larger for HEV batteries than for EVs because materials costs constitute a smaller 

portion of the total cost for HEV batteries. Increasing the production rate for HEV batteries will 

result in a more dramatic reduction in cost than increasing the production rate for EV batteries. 
67 

7. Future Work

7.1 Thermal Modeling 

The battery design format used in this report provides cooling to the battery pack by blowing air 

over the top and bottom of the modules. The heat is transferred through the stiff, aluminum 

pouch material to the module walls. An additional aluminum plate may be placed between cells 

to enhance heat transfer. This method of cooling will be sufficient for some battery applications, 

but other applications might require that the battery pack be over-designed to reduce heat 

generation. Over-design would include providing a battery pack of higher power than called for 

by the application or providing the power at a very high fraction of the open-circuit voltage 

(>85%OCV). 

We intend to develop an alternative battery design that provides liquid cooling directly to the 

cells inside the modules. Means of distributing a dielectric coolant to the interior of the modules 

will be studied. We will carry out thermal modeling studies on the heat generation during vehicle 

operation on various driving cycles and on the removal of heat from both air-and liquid-cooled 

battery packs. We intend to investigate the feasibility and cost of these options. The results of 

these studies will be incorporated into the model in a separate thermal modeling section. This 

work will be carried out in a cooperative effort with Argonne’s Transportation Technology R&D 

Center, which will perform vehicle simulation tests to determine the rate of heat generation in the 

battery pack. 

7.2 Optimum Battery Voltage for Minimum Drivetrain Cost 

For a set cell chemistry and set battery pack power, the cost of the pack increases as the number 

of cells and the pack voltage are increased (Fig. 6.1). The additional cost results primarily from 

the cost of additional state-of-charge equalization circuits and the additional number of cells 

needing formation cycling and testing. The increase in battery pack cost is almost linear with the 

increase in the number of cells. As the number of cells is decreased, the pack current at 

maximum power becomes very high and the cost of the balance of the drivetrain increases at an 

accelerating rate. Thus, there must be a number of cells and an associated pack current at 

maximum power for which the total cost of the drivetrain is at a minimum. This minimum would 

be for the current at full power for which the slope of the cost curve for the balance of the 

drivetrain versus current was equal to the negative of slope of the cost of the pack versus current. 

This optimum current will increase with the pack power because the slope of the cost-versuscurrent curve increases with increasing power and, therefore, the optimum current will also 

increase. 

To represent these phenomena in illustrating the model in Section 6, we used an equation (Eq. 

6.1) for selecting the current at full power as a function of the battery pack power. This equation 

is just an estimate and it does not provide for differences in the optimum current that would 

result from differences in cell chemistries, which are known to affect the battery cost versus 

power function. 
68 

A study is needed to determine the cost of electric motors and the electronic control equipment 

required for the vehicle and battery pack as a function of power and maximum current capability. 

Once appropriate cost curves are established, we will determine equations relating the optimum 

battery current to the desired battery power taking into account the battery chemistry. We intend 

to do this study with the cooperation of Argonne’s Transportation Technology R&D Center. 

7.3 Multipurpose Battery Manufacturing Plants 

Our cost modeling is based on the concept that a manufacturing plant is constructed to produce a 

single type of battery pack at a predetermined level of production. In practice, manufacturers will 

have to produce several types of batteries within the same manufacturing plant and the levels of 

production may fluctuate. We intend to investigate how this increased flexibility requirement 

will affect the various manufacturing costs. For example, the cell filling and sealing equipment 

may be required to handle cells of different dimensions. This would most likely increase the 

capital cost for this equipment. Alternatively, additional packaging and sealing lines might be 

needed. We intend to evaluate combinations of vehicle battery packs that are easily integrated 

into the same plant. The manufacturing cost will most likely increase after these considerations 

are built into the model. 

7.4 Stand-Alone Graphical User Interface for Model 

The spreadsheet program described here-in allows versatility in designing the battery and in 

calculating the costs, but like all complex spreadsheet programs it is not user-friendly to those 

unfamiliar with the details of calculation. In addition, the model is easily corrupted by a poor 

choice of input parameters. As a result, the final spreadsheet program will be converted to a 

stand-alone user-friendly application, primarily with the efforts of Ira Bloom. Visual Basic for 

Applications will be used to hard code in the model calculations and to also create the graphical 

interface. The new user interface should allow for a wide distribution of the model while 

maintaining the ability to change the vast majority of input parameters. The retention of this 

flexibility should make the model a valuable tool for those interested in batteries regardless of 

the specific material property or manufacturing cost structure the user seeks to analyze. 
69 

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