EVS27 - Barcelona

From Accelerated Aging Tests to a Lifetime Prediction Model: Analyzing Lithium-Ion Batteries

Updating

parameters

Stress factors:

t, T, U, Q, DOD, ØU

Load profile +

Temperature profile

(I or P, T)

Initial

impedance

parameter

Fitted

aging

parameters

Lifetime

prognosis

18.11.2013

Johannes Schmalstieg1,3, Stefan Käbitz1,3,

Madeleine Ecker1,3, Dirk Uwe Sauer1,2,3

1 Electrochemical Energy Conversion and Storage Group, Institute for Power Electronics and Electrical

Drives (ISEA), RWTH Aachen University, Germany

2 Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Germany

3 Jülich Aachen Research Alliance, JARA-Energy, Germany

Why lifetime estimation?

18.11.2013 Johannes Schmalstieg

vehiclemy.com

topoften.com

- €

200 €

400 €

600 €

800 €

iPhone

- €

5.000 €

10.000 €

15.000 €

20.000 €

25.000 €

eSmart

2

Real life tests using application specific load profiles

Valid only for pre-defined scenario

Time consuming

Aging model

Accelerated aging tests

at defined conditions

Can be used for a wide

range of load profiles

Methods of lifetime estimation

18.11.2013 3Johannes Schmalstieg

Accelerated aging tests

18.11.2013 4Johannes Schmalstieg

calendar aging cycle agingcalendar aging cycle agingcalendar aging cycle aging

1C, 35 °C

Uniform capacity

aging

Two step fitting

1. Fit ∙ .

to single tests

2. Analyze on

voltage and temperature

influence

Calendar aging: Time dependency

18.11.2013 Johannes Schmalstieg 5

calendar aging cycle aging

50 °C

Calendar aging: Temperature + voltage dependency

18.11.2013 Johannes Schmalstieg 6

calendar aging cycle aging

Temperature dependency

matches Arrhenius equation

Analyse fit factor

∙ .

Cycle aging results

corrected by calendar

aging

Fit function

∙

Cycle agingCharge throughput dependency

18.11.2013 Johannes Schmalstieg 7

1C, 35 °C

calendar aging cycle aging

Cycle aging:Cycle depth + average voltage dependency

18.11.2013 Johannes Schmalstieg 8

calendar aging cycle aging

Holistic model

18.11.2013 Johannes Schmalstieg 9

Updating

parameters

Stress factors:

t, T, U, Q, DOD, ØU

Load profile +

Temperature profile

(I or P, T)

Initial

impedance

parameter

Fitted

aging

parameters

Lifetime

prognosis

calendar aging cycle aging

Impedance based electric

model

Lookup tables for parameters at

different temperatures and SOC

Simple thermal model

Electric-thermal model

18.11.2013 Johannes Schmalstieg

1 2 3 4 5 6 7

-4

-3.5

-3

-2.5

-2

-1.5

-1

-0.5

0

0.5

Re(Z) / mΩ

Im(Z) / mΩ

90% SOC

70% SOC

50% SOC

30% SOC

10% SOC

1,77 kHz1085mHz

610mHz

10

Heat transfer

resistance

Aging model

18.11.2013 Johannes Schmalstieg 11

Verification profile

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1

2

3

+10 °C

+20 °C

Verification

18.11.2013 Johannes Schmalstieg 13

Profile 1 Profile 2 Profile 3

+0°C

+10°C

+20°C

Commercial 18650 cell aged at accelerated conditions

Describe capacity loss and resistance increase by mathematical functions

Holistic model simulates calendar and cycle life

Current or power profiles can be applied

Ambient air temperature profiles are possible

Verification has a good match

A powerful tool to optimize BMS strategies and battery lifetime

Conclusion

18.11.2013 Johannes Schmalstieg 14

Thank you for your attention

This work has been developed in the projects “e performance” (13N10656) and “e

production” (16N12035), funded by the German Federal Ministry of Education and

Research.

18.11.2013 Johannes Schmalstieg 15

EVS27 - Barcelona

From Accelerated Aging Tests to a Lifetime Prediction Model: Analyzing Lithium-Ion Batteries

Updating

parameters

Stress factors:

t, T, U, Q, DOD, ØU

Load profile +

Temperature profile

(I or P, T)

Initial

impedance

parameter

Fitted

ageing

parameters

Lifetime

prognosis

18.11.2013

Johannes Schmalstieg1,3, Stefan Käbitz1,3,

Madeleine Ecker1,3, Dirk Uwe Sauer1,2,3

1 Electrochemical Energy Conversion and Storage Group, Institute for Power Electronics and Electrical

Drives (ISEA), RWTH Aachen University, Germany

2 Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Germany

3 Jülich Aachen Research Alliance, JARA-Energy, Germany

18.11.2013 Johannes Schmalstieg

Calendar aging: Time fitting

18.11.2013 Johannes Schmalstieg 18

18.11.2013 19Johannes Schmalstieg