Presentation given at Advanced Automotive Batteries Conference 2012 in Orlando, FL. www.ansys.com/automotive

1. © 2011 ANSYS, Inc. February 28, 20121
Simulation and Virtual Product Development
of Advanced Automotive Batteries
Sandeep Sovani, Ph.D.
Manager, Global Automotive Strategy
ANSYS Inc, Ann Arbor, MI, USA
February 10, 2012

2. © 2011 ANSYS, Inc. February 28, 20122
Virtual Product Development
Concept & Design
Physical
Prototype
Production
Simulation-Driven
Product Development
Today’s norm for automotive product development

3. © 2011 ANSYS, Inc. February 28, 20123
Largest
Independent CAE simulation software company
Focused
Simulation is all we do.
Leading product technologies in all physics areas
Largest development team focused on simulation
Capable
2,000 employees
60 locations, 40 countries
Trusted
96 of top 100 FORTUNE 500 industrials
ISO 9001 and NQA-1 certified
Proven
Recognized as one of the world’s most innovative
and fastest-growing companies*
Independent
Long-term financial stability *BusinessWeek, FORTUNE
About ANSYS A Simulation Software Company

4. © 2011 ANSYS, Inc. February 28, 20124
Fluid DynamicsStructural Mechanics
ANSYS Simplorer
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About ANSYS
Products – Advanced Physics Solvers

5. © 2011 ANSYS, Inc. February 28, 20125
Simulation in Automotive Product Development
Used extensively
Cars and Light
Trucks
Heavy Trucks
And Buses
Off-Highway,
Construction
Motorsports
Two Wheelers
Railways
Other Ground
Transportation

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Three key differences
Batteries simulation is very different from
traditional automotive simulations
Multi-Scale
Multi-Physics
Multi-Parameter

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Current Distribution,
EMI/EMC, Abuse
Thermal Mgmt
Durability, NVH,
Impact, Abuse
NVH
Tight coupling between
multiple fields
Multi-Physics
Battery Image Reference: http://a.img-
zemotoring.com/media/news/2010/11/renault-battery-pack.jpg

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Multi-Physics
Multiple physics solvers and seamless interconnections

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- Newman & Tidemann (1993);
- Gu (1983) ;
- Kim et al (2008)*
J
)()( TfUYJ np
Cathode Anode
Current Current
ip= Current Vectors
at Cathode plate in= Current Vectors
at Anode plate
J = Current Density
J (t, x, y, T )
Cathode Anode
Current Current
ip= Current Vectors
at Cathode plate in= Current Vectors
at Anode plate
J = Current Density
J (t, x, y, T )
Transfer current
U and Y are derived from experimentally
obtained polarization curve, dependent on
Depth of Discharge (DOD) & Temperature
A model based on the work of:
* Reference: U. S. Kim, C. B. Shin , C. S. Kim, “Effect of electrode configuration on the thermal
behavior of a lithium-polymer battery”, Journal of Power Sources 180 (2008) 909–916.
Example 1Multi-Physics

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Geometry & Mesh
Temperature Current Density
Example 1Multi-Physics

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Temperature DistributionCurrent Density Distribution
Structural Deformation, Fatigue Life
Electro-Thermal-Structural Fatigue of Bus Bars
Multi-Physics Example 2

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Multi-Scale
Multi-Physics
Multi-Parameter

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Phenomena at one level affect those at other levels and
need to be simulated in simultaneous co-simulation
Electrode
Level
•Electrode layout
•Manufacturing
process
development
•Aging
Molecular
Level
•Material
innovation
•Material
selection
Cell Level
•Charging, dischar-
ging profiles
•Heating
•Safety under abuse
•Swelling,
deformation
Pack Level
•Thermal Mgmt
•BMS Logic
•Safety
•Durability
•NVH
•EMI/EMC
Powertrain and
Vehicle Level
•System Integration
SmallScale
LargeScale
Multi-Scale
Tight inter-coupling between multiple scales

14. © 2011 ANSYS, Inc. February 28, 201214
Enabling comprehensive multi-scale simulation:
DOE-NREL CAEBAT Project
Electrode
Level
Molecular
Level
Cell Level Pack Level Powertrain and
Vehicle Level
SmallScale
LargeScale
Multi-Scale
Universities and
Research Institutes
Commercial
Simulation Software
Companies
ESim
One of the 3 teams in CAEBAT

15. © 2011 ANSYS, Inc. February 28, 201215
Multi-Scale
Two key needs for multi-scale simulation:
1. Co-Simulation
Simultaneous simulation of a component and
a system
E.g. cell and module co-simulation
2. Model Order Reduction
Representing a component with a simplified
model to faster system simulation

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Battery Electrical
Model
Cell 4
Cell 5
Cell 6
Cell 1
Cell 2
Cell 3
Battery Cooling Flow
and Thermal CFD
Model
Heat
Dissipated
Temperature
Multi-Scale
Electrical-Thermal-Fluid Co-Simulation
Example 1

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Heat
Dissipated
Temperature
Heat dissipation
Discharge curve
Temperature contours
Multi-Scale
Electrical-Thermal-Fluid Co-Simulation
Example 1

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A sample step
response
Multi-Scale
LTI Model Order Reduction
Example 2
Module Geometry (CAD)
Simulation Model
3D Flow Simulation Result
Thermal step load (heat release) is
applied to each cell and the
response of the entire cooling flow
field is recorded

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Multi-Scale
LTI Model Order Reduction
Example 2
A foster network model is created using the step responses

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Multi-Scale
LTI Model Order Reduction
Example 2
Simulation run
time reduced
from many hours
to few seconds,
without loss of
accuracy making
is possible to
simulate very
long transient
cycles.

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• 60 Cells connected in matrix pack
• Packs are connected in matrix to final
configuration
5
cells
Multi-Scale
Module Models incorporated into Pack Model
Example 2

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Powertrain and
Vehicle Level
System
Integration
Multi-Scale
Pack Model is integrated into Powertrain Model
Example 2

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Multi-Scale
Multi-Physics
Multi-Parameter

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Multi-Parameter
• Multitude of design variables in batteries
• Simulation is the only feasible way to handle
a large number of variables for –
• Robust design
• Optimization

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Property
SD/
Mean
Metallic materials, yield 15
Carbon fiber composites 17
Metallic shells, buckling 14
Junction by weld 8
Bonded insert, axial load 12
Honeycomb, tension 16
Launch vehicle , thrust 5
Transient loads 50
Thermal loads 7.5
Deployment shock 10
Acoustic loads 40
Vibration loads 20
Fluid flow 3
FatigueFluids
Structural
(thermal)
Geometry
Structural
(deformation)
±??%
Potential
Failure?
Multi-Parameter
Protection against potential failure
Robust Design

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Input with Variations
• Gap Thickness
• Cell Resistance
• Flow Rate
• Six input
parameters:
– tgap
– tgap
– R
– R
– Frate
– Frate
Ref: Valhinos et al, “Improving Battery Thermal Management Using Design for Six Sigma Process”, 20th Electric Vehicle
Symposium, Long Beach, CA (November 15-18, 2003)
Multi-Parameter Robust Design Example

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Outputs – variation
• Max temperature
• Differential temperature
• Pressure drop
Six output parameters:
• Tmax
• dT
• dP
• Tmax
• dT
• dP
Three Upper Specification Limits (USL)
Ref: Valhinos et al, “Improving Battery Thermal Management Using Design for Six Sigma Process”, 20th Electric Vehicle
Symposium, Long Beach, CA (November 15-18, 2003)
Multi-Parameter Robust Design Example
Potential
Failure

28. © 2011 ANSYS, Inc. February 28, 201228
Channel Inlets
Multi-Parameter Optimization Example
Task:
Optimize the manifold shape
to ensure flow uniformity
across channel inlets
Simulation accomplished this
task automatically with shape
morphing

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Initial
Geometry
Final
Geometry
Multi-Parameter Optimization Example

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• Simulation is key to battery development
• Battery simulation poses three challenges
1. Multi-physics
2. Multi-scale
3. Multi-parameter
• Several useful simulation solutions are
commercially available today
• Ongoing work is further addressing
simulation challenges
Summary