[PPT] - and New Features Overview xEV simulations require estimates of PowerPoint Presentation

SLIDE 1

Using Battery Design Studio for Battery Simulation and New Features

SLIDE 2

xEV simulations require estimates of battery electrical and thermal behavior. BDS cell design process.

– Physical cell description – Fitting model parameters

Model Improvements

– NTGP – RCRTable – DISTNP

Conclusions

Overview

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SLIDE 3

xEV Drive Cycles

3 Time (s) SOC Speed

D. Prokhorov, Neural Networks, Vol. 21, Issues 2–3, March–April 2008, pp. 458–465

SOC is relatively constant but speed varies

ver wide

range.

Speed (Km/hr) SOC All Electric Range Blended Modes

“The drive cycle represents a typical work-home commute which starts in a suburban area, characterized by UDDS, then continues on a highway, simulated by HWFET, and finally arrives to downtown urban area, UDDS.”

M. Shams-Zahraei et al. J. Power Sources 216 (2012) 237-248

SOC and speed vary over wide range. Challenge: Model electrothermal behavior of battery.

SLIDE 4

Selected Simulation Models in Battery Design Studio

Page 4

 

         

2 6 5 4 3 3 2 2 1

DOD a DOD a a Y DOD a DOD a DOD a a U U V V Y J

n p

         

(1) J. Newman and W. Tiedemann, J.

Electrochem. Soc. Vol. 140, No. 7, July 1993 pp.

1961-1968. (2) H. Gu, J. Electrochem. Soc., Vol. 130 No. 7 1983 pp. 1459-1464. (3) U. S. Kim, Ch.B. Shin, C.-S. Kim, J. Power

Src. 189 (2009) 841-846

(1) T. Fuller, M. Doyle, J. Newman, J.

Electrochem. Soc. 141 (1994) 1-10

(2) Battery Design LLC, “BDS Documentation”

M. Verbrugge and R. Conell, J.
Electrochem. Soc. 149 (2002) A45-A53

Cell Design

DISTNP

HEV/PHEV Module/Pack

RCR

EV Module/Pack

NTG

Solves transport, kinetics, equations Quick response for frequent charge/ discharge like HEV/PHEV energy storage Simple, easy to create model , and best for simple discharging thermal analysis

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SLIDE 5

BDS Cell Design Process

Pa Page e 5

Physical Cell Description

Coin, cylindrical pouch, prismatic
Gives size, weight, equilibrium voltage,

capacity, bill of materials, etc.

Fit Model Parameters

circuit, physics
Allows simulation of performance

Use and/or Distribute

Text Battery Model (tbm)

5

SLIDE 6

Button cell
Active

materials

Additives
Electrolytes
Separator

Materials Developers

Model selection
Electrodes, incl.

tabbing

Separator
Spiral cylindrical,

prismatic, stack

Cell Designers

Series/Parallel

cells

CFD with heat

transfer

Module/Pack Developers

System

simulation

End Users

tbm tbm

TBM files bridge the design process for batteries

Batt ttery ery De Design ign Studi dio STAR-CCM CCM+

sim (tbm)

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SLIDE 7

Simple Cell – useful for coin cell simulation

Sp Spring ring Spac acer er Lith ithiu ium m foil, il, 1.587 875 5 cm dia ia Separa arator,

r, 1.9 cm dia

ia, 100 0 um Cathode, hode, 1.27 7 cm dia ia Stain inles less s steel el lid lid Stain inles less s steel el cas ase 1 M LiP iPF6/ 6/EC:DE C:DEC C (1:1 1 volum lume) e) 7 Materials developers typically use coin cells Key properties

Density
Voltage
Surface area
Diffusion coeff.

SLIDE 8

Fitting solid-phase diffusion coefficient of lithium nickel cobalt aluminum oxide

8 Pulse experiments done in coin cells can be used to fit solid-phase diffusion coefficients of active materials.

Y. Li (FMC), Star Global Conference 2012 Amsterdam

SLIDE 9

Electrolyte Models

AEM computed property sets from K. Gering

9 EC EC3_E _EMC MC7_Li 7_LiFSI SI EC3 C3_EMC MC7_LiPF6 7_LiPF6 EC3 C31_PC10 C10_D _DMC MC59_LiPF6 9_LiPF6 EC2 C23_PC21 C21_D _DMC MC56_05L 6_05LiDFOB_ iDFOB_05L 5LiPF6 iPF6 EC EC32_D _DEC2 EC23_DMC24 3_DMC24_EP2 _EP22_LiPF6 _LiPF6 EC3 C38_DM DMC31 C31_E _EMC MC31 31_05L _05LiPF6_ iPF6_05L 5LiFSI iFSI EC3 C31_EMC4 EMC46_DE 6_DEC23_ C23_Li LiFSI SI EC3 C31_EMC4 EMC46_DE 6_DEC23_ C23_Li LiPF6 F6 EC3 C39_EMC3 EMC30_DMC 0_DMC30 30_LiPF6 _LiPF6 EC1 C15_EMC6 EMC64_ 4_GBL GBL21 21_L _LiFSI iFSI PC5 C58_DM DME42_ E42_Li LiTFS FSI PC PC58_D _DME42_LiCF ME42_LiCF3S 3SO3 O3 Electrolyte properties available in next release of BDS.

SLIDE 10

Comparison of Gering’s computed properties with literature values

L. Valøen

en and d J. Reimer imers, , J. Ele lectroch rochem em. . Soc., ., 152 152 (5 (5) ) A882- A891 1 (2005 005) 10 EC EC31_ 1_PC PC10_DM 0_DMC59 C59_LiPF6 _LiPF6

SLIDE 11

Electrolyte Models

Tabular Input

11 Experimental values for electrolyte properties can be directly entered in tabular form.

Available in BDS 8.02.010

SLIDE 12

Physical Cell Description: Stacked Plate Cells

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SLIDE 13

Physical Cell Description: Spirally-Wound Cells

Tabbed electrode

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SLIDE 14

Physical Cell Description: Spirally-Wound Cells

Multi-tabbed electrode

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SLIDE 15

Physical Cell Description: Spirally-Wound Cells

Edge Collector with clamp

15 Available in next release of BDS.

SLIDE 16

NTG Model – Parameter Fitting with Polynomials Polynomial fits introduce significant error.

16

SLIDE 17

NTG Model – Parameter Fitting with Bezier Curves Bezier curves conform to parameter values exactly. Parameter input is simplified since only values need to be provided.

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SLIDE 18

Compa mparis rison n of data a and d fitt itted (NTG TG model) del) voltage ltage behav havior ior for cell ll with ith 100 0 micr icron

n thic

ick k catho hode de coat ating. ing. Compa mparis rison n of data a and d fitt itted (NTGP TGP mode del) l) voltage ltage behav havior ior for r cell ll with ith 100 0 micr icron

n thic

ick k catho hode de coat ating. ing.

NTGP model improves fit to data when discharge or charge capacity depends on rate.

NTGP Model: Peukert Effect

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SLIDE 19

RCRTable – an enhanced RCR model

Enhan ancemen cements s provided

vided by

RCRTa RTable ble

Enter

er mode del l par arame ameters ers at specific ecific SOC values lues dir irectly ectly, no need ed to fit it to polynomials lynomials

Use

e lin linear ar in interp rpola lati tion

n for

tempera perature ure depen penden dence ce

Pola

lari riza zation ion res esist istan ance ce can n depend pend on curre rrent nt (rat rate e or Tafel el effec ect)

War

arburg burg im impeda dance nce  Capabilit pability to fin ine tune e fits its to to data RCR R model del is is u useful eful for r sim imula ulati ting ng perform rforman ance ce of H HEV batteri eries es

Para

rame meters ers are e a funct ction ion of SO SOC repr pres esented ented by polyno lynomials mials

Para

rame meters ers depend pend on tempera peratures ures via ia Arrh rhen enius ius relat lation ion

M. Verbrugge and R. Conell, J.
Electrochem. Soc. 149 (2002) A45-A53

Rs Rp

RC RCR R Model

OCV C= C=/Rp C= C=/Rp Rs Rp,1

,1 RW

RC RCRT RTable Model

OCV 19

SLIDE 20

RCRTable: Rate Dependent Resistance

                       

1 , 1 ,

exp 1 i i i i R R

p p

Current, A Resistance, mOhms 50 2.122 100 1.473

Cell resistance decreases with increasing current

Rp,1 = Polari larisat ation ion res esis istan ance Rp,0 = Polari larisat ation ion res esis istan ance at zero ero curren urrent i1, i0 = Adjus ustable able para ramet eter ers

20

SLIDE 21

RCRTable Model: Warburg Effect

c

d

V B d W W p p

e e t A R R R R    

1 ,

Cell resistance increases with time.

Rp,1 = Polari larisat ation ion res esis istanc nce RW = = Warbu rburg rg imped pedanc ance Ad & & Bd are re coef

efficien

icients Voc

c is related

lated to the he OCV curv rve

C= C=/Rp Rs Rp,1

,1 RW

OCV 21

SLIDE 22

Sei growth by solvent reduction is one

dominant aging mechanism in Li-ion batteries:

increase in cell resistance
irreversible consumption of

available Lithium

deterioration in:
capacity
rate capability
experimental investigations have

shown a sqrt(t) dependency

a new SEI growth feature was

implemented in BDS using a diffusion based transport model after Ploehn et

al. (J. Echem. Soc. 151(3) A456 (2004))
feature available for Li_Pouch_dist1D

in release 8.02 but will be available for

ther Dist models (in STAR CCM+ as

well)

Source: arXiv:1210.3672 [physics.chem-ph]a

DISTNP Model: SEI Growth

22

M. Inaba, Y. Iriyama, T. Abe, Z. Ogumi, Electrochim.

Acta 47 (2002) 1975-1982

SLIDE 23

New SEI growth parameters in the particle menu

nm nm

W.cm cm2

23 15C 15C 30C 60C 30C 60C

SLIDE 24

Notes on the required input data

Initial SEI thickness specified by user Values taken from Ploehn paper Model on or off

Running with the ‘long report’ or ‘solid- phase profiles’ option produces a very large *.pr2 file (circa 2GB in this case) 24

SLIDE 25

Run time is considerably effected by frequency of report in .prg file Changed to 1 day, which expedites the aging run time and file size

25

SLIDE 26

After simulation is run, ‘aged’ tbm file can be found in the BDS Results directory Thickness is increased compare to original and this tbm file could then be used in STAR-CCM+ BSM to represent an aged cell

Run a capacity test on both new and aged tbm files to see effect 26 Capacity Fresh Aged

SLIDE 27

BDS provides models to simulate electrothermal behavior of batteries useful for design of automotive batteries. BDS provides pathway for materials suppliers to provide design parameters to cell developers, and cell developers to provide cell models to pack developers. BDS enables physical cell descriptions that accurately represent actual designs. New features of BDS BDS allows modeling of tabbing arrangements for spirally-wound cells. BDS provides electrolyte property systems to aid in physics-based simulation of lithium-ion cells. BDS provides accurate representation of parameter dependence for NTG and RCR models on state of charge. BDS allows simulation of impedance growth to due SEI growth.