Control Enabling Solutions with Ultrathin Strain and … · · 2015-04-10Control Enabling...

Imagination at work.

2015 Annual Meeting – Open Session April 1, 2015

Control Enabling Solutions with Ultrathin Strain and Temperature Sensor System for Reduced Battery Life Cycle Cost

© 2014 General Electric Company - All rights reserved

2

Team

Aaron Knobloch - Principal Investigator

Jason Karp Chris Kapusta Yuri Plotnikov David Lin

Brian Engle – Automotive Vertical Ldr Rob Twiney – GM Advanced Sensors Dave Geer – Principal Engineer

Dave Villella – Test Engineer Ron Martonik – Product Manager

Anna Stefanopoulou – Michigan Lead Jason Siegel Bogdan Epureanu

Charles Monroe Krishna Garikipati Nassim Samad Ki Yong Oh Howie Chu

Zhenlin Wang

Dyche Anderson – Ford Lead Arnold Mensah-Brown Ramzi Chraim

Tommy Coupar Xinfan Lin Bruce Blakemore


3

Program Overview

Multi-parameter in-situ cell monitoring to

increase operating window and improve SOH

Observability Integration & Controls Development

Ultra-thin Temp & Expansion Sensor

Development

Thermal Electrochemical

Mechanical

Estimation / Limits • State of Power • State of Charge

• State of Health

Multi-Physics Models

Data & Model Fusion

Pack Integration & Validation

Characterize Cells

Develop Sensors

Swelling due Li-Intercalation (top) & Thermal Expansion

(bottom)


Program Summary & Value Proposition


5

Expected System Benefit

Test Case – 5 Amp-hr Panasonic Cell for HEV Applications

Real-time Dynamic Model-based Power Limits

Temp & Expansion Sensor

Prediction Estimation

Po

we

r

State of Charge

Cold Temp Limits Room Temp Limits

Cycle OperatingWindow - Centered at

High SOC


Low SOC

Widened State of Charge Operating Range

20% Reduction in pack size while maintaining life at higher throughput


6

Enabling Sensor Technologies

Thin film RTD

• Thin (<100mm) – locate

anywhere on surface

• Develop arrays

• Accuracy

• Time response

• Enables lower cost battery

packaging

Eddy Current

• Not able to measure

expansion today

• Small / cost effective

• Can measure between cells

• Potential correlation to

battery health, SOC, …

36 point Temperature Array Leverages high volume, low

cost Flex manufacturing

Benefits Competitive Technologies

Thermistors

• Thick (>1mm)

• Limited locations

• Slower

• Lower accuracy

• Higher installation costs

Strain Gages:

• Drift, low signal level

• Temp effects

Load Cells:

• Thick (>1/4”)

• Not cell specific

Integrated Expansion & Temperature Sensor


7

Fusion of Sensor Data and Models

Thermal Mechanical

-Thermal and Intercalation swelling, sensor response, and porosity change.

Electrochemical (ECM or DFN)

𝑇

𝑇

𝑆𝑂𝐶

𝜀, 𝜖

Modeled Pack Temp

Free and Constrained Swelling

0 20 40 60 80 100 120

0

10

20

30

40

50

60

70

80

Width(mm)

He

igh

t(m

m)

0.000

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

103.5

H1

H5

Enhanced SOC Estimation

with Measured Expansion

Measured Temp


8

Model Based Power Limit

• Improved battery core temperature estimation using thin film temperature sensor -> 2 minute faster convergence rate.

• Model based power limiting strategy enables faster warmup to full power, and wider SOC operation.

• Dynamic power limits can be more conservative when necessary for health and safety.

• At low temperatures (-5oC), battery utilization (Whr throughput per cell) can be increased up to 26%.

(New) US06 Drive Cycle Benefits

Prediction Estimation


Key Learnings & Results


10

Charge sustaining pulses • 20, 39, 50A • Fan on, fan off

Experiment

Comsol

Reduced TEM

Electro-Thermal Model Validation

0 5 10 15 20 25 30 3527

28

29

30

31

32

33

Surface temperatures [oC]

Te

mp

era

ture

[oC

]

0 5 10 15 20 25 30 3527

28

29

30

31

32

33

Te

mp

era

ture

[oC

]

COMSOL

ECM

Experiment

0 5 10 15 20 25 30 3527

28

29

30

31

32

33

Te

mp

era

ture

[oC

]

Sensor Index

20A excitation

39A excitation

50A excitation

• Performed observability analysis

for optimal sensor placement.

• Thin film sensor enables faster core temp estimation over existing measurement location (side vs top of cell )

• Less than 2oC modeling error in pack cell temperature predictions

over a 35oC operating range

Finite element and reduced order pack models validated against vehicle drive cycle data.

Reduced

20A excitation

39A excitation

50A excitation

Samad, N., e.t. al. DSCC 2014-6321, 2014.


11

Swelling (Free)

Swelling (Constrained)

Response at GE Sensor location

Thermal (∆T=10°C)

[μm]

Intercalation (∆SOC=100%)

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Sw

ellin

g (

mm

)

SOC

Thermal

Li-ion intercalation

0 1 2 3 4 5 6T

Li Intercalation Swelling

Oh, e.t. al. J. Power Sources, 267(0):197 - 202, 2014.

T 6oC <=> SOC 100%

Thermal Swelling

0.0 0.2 0.4 0.6 0.8 1.0

0

20

40

60

80

100

Sw

ell

ing

(mm

)

SOC

Model

prediction Measured data

6oC

0 20 40 60 80 100 120

0

10

20

30

40

50

60

70

80

[mm]

0.000

5.000

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

51.00H

eig

ht(

mm

)

Width(mm)

3oC 9oC

Thermal Free Swelling


12

0 100 200 300 400 500 6003

3.5

4

4.5

Vo

lta

ge

(V

)

0 100 200 300 400 500 6001000

1200

1400

Fo

rce

(N

)

0 100 200 300 400 500 6000.3

0.4

0.5

SO

C

Plant V only V+F

0 100 200 300 400 500 600-0.02

0

0.02

0.04

0.06S

OC

err

or

Time (sec)

SOC Estimation

0 100 200 300 400 500 6003

3.5

4

4.5

Vo

lta

ge

(V

)

0 100 200 300 400 500 6001000

1200

1400

Fo

rce

(N

)

0 100 200 300 400 500 6000.3

0.4

0.5

SO

C

Plant V only V+F

0 100 200 300 400 500 600-0.02

0

0.02

0.04

0.06S

OC

err

or

Time (sec)

Similar Convergence Rate

0 1000 2000 3000 4000 5000 60003

3.5

4

4.5

Vo

lta

ge

(V

)

0 1000 2000 3000 4000 5000 60001000

1200

1400

Fo

rce

(N

)

0 1000 2000 3000 4000 5000 60000.3

0.4

0.5

SO

C

Plant V only V+F

0 1000 2000 3000 4000 5000 6000-0.02

0

0.02

0.04

0.06S

OC

err

or

Time (sec)

Estimation Quality Improved

Mohan S., e.t. al. DSCC 2015, in preparation

U.S. Utility Patent Application No. 62/043,519

The relation among temperature, SOC, current

and force enables the use of measured for in

SOC estimation.


13

SOC Estimation

Mohan S., e.t. al. DSCC 2015, in preparation

U.S. Utility Patent Application No. 62/043,519 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.2

0.4

0.6

0.8

1

SOC

No

rma

lize

d V

oc

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.2

0.4

0.6

0.8

1

No

rma

lize

d F

orc

e

0.31 0.36 0.41 0.46 0.51 0.56 0.61 0.66 0.71-0.02

-0.015

-0.01

-0.005

0

0.005

0.01

Estim

atio

n e

rro

r

V only

V+F

0.31 0.36 0.41 0.46 0.51 0.56 0.61 0.66 0.710

500

1000

1500

Actual SOC

Vis

ita

tio

n N

o.

Estimation quality improved by a adding

force measurement - more prominent in

SOC range between 30~50%

The relation among temperature, SOC, current

and force enables the use of measured for in SOC

estimation.


14

3-Cell Degradation Testing • Established baseline degradation

– 25oC cell temperature ( -10oC ambient air)

• Open loop US06 power profile, no controls (yet).

• Conclusion: Lower capacity loss at lower SOC.

• Next steps: compare degradation effects for closed loop power limiting and

wider SOC window on downsized pack.

Using 3-fixtures to assess capacity loss

56k equivalent miles driven

33% 50% 66%

50% SOC

high preload


15

Power Limits, Downsizing, and Degradation

• Shift to lower SOC operation for reduced degradation

and more charge acceptance (regen braking) at -5oC.

(New) US06 Drive Cycle


16

Power Limits, Downsizing, and Degradation

# of times algorithm would limit power deliver/acceptance, i.e. Energy left on the table <==> FE.


Validation Plan & Performance Targets


18

Status of Proof of Concept – Demonstration Pack

Sensor-Pack Integration

Gen 1 Open Loop UM Model Complete Q1 2015

Baseline U-M 3 Cell Rig

56k miles Complete Q1 2015

Demonstration Pack Operation

Validate Expected Benefits Start Q2 2015

Confirm functionality

• Verify sensor fit • Test software / find bugs • Confirm accuracy of

model estimates

Operation

• Integration • Examine target SOC window • Sensor accuracy & perf • Confirm accuracy of model

estimates

Verify model & control

• Hardware in the loop simulation

• Impact on degradation on validation conditions


19

Benefit Demonstration & Validation

Instrumented Pack Control Pack

GE Sensors & UM Controls Wider Operating Window

Ford Controls

Wider Operating Window

• Use existing test profiles, adjusting SOC ranges • Two cycles “high”, two cycles “low” • Adjust between cycles if significant drift in

center point • Run for c. 30,000 mi equivalent minimum • Capacity & power tests every month – examine

degradation

P

ow

er

State of Charge

Cold Temp Limits Room Temp Limits


High SOC


Low SOC

Widened State of Charge Operating Range


20

Expected Performance Benefits • Improved state of charge and power capability estimation • Improved power availability at low temperatures • Pack may be downsized (fewer cells or smaller cells)

AMPED

Full Pack (76 cells) – 2014MY Reduced Pack (60 cells) same total power

-21% +27%

Increased Utilization (Wh throughput per cell)

105s *

Faster Warmup

+23%

Cell Count Reduction +25C Cold (-5C)

*Results for scaled US06 battery power

profile at 25oC.


Summary


22

Summary

• Proven

– Temperature sensor + physics based model enables more accurate and faster (2x) prediction of core temperature

– Developed SOC estimation based on force / expansion – more sensitive (in 30-50% SOC range) than typical voltage based measurements

– Demonstrated integration of sensors & open loop control with Ford pack

– Simulated validation performance based on improved state estimation

• Ongoing

– Verify validation windows on 3 cell rig and developmental pack

– Development of closed loop control with expansion/force input

– Instrument and run validation pack to demonstrate benefit

• Challenges Addressed

– Cell SOC estimation

– SOH measurements / battery lifetime

– Model to extract maximum power capability and throughput with long life


23

Program Next Steps

• Examining sensor performance on other cell types

(soft pouch, larger size)

• Commercialization of sensors & model-based

algorithms


24

Acknowledgement & Disclaimer

Acknowledgment: The information, data, or work presented herein was funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Award Number DE-AR0000269.

Disclaimer: The information, data, or work presented herein was funded in part by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

Control Enabling Solutions with Ultrathin Strain and … · · 2015-04-10Control Enabling...

Documents

Transcript of Control Enabling Solutions with Ultrathin Strain and … · · 2015-04-10Control Enabling...