Modeling and Analysis of the Battery Packs and Modules in A123 SystemsBinshan Ye & Shawn Zhang
A123 Systems, Inc.
Outline
• Overview of CAE capacity in A123
• CAE Modeling and Analysis Examples
• Random vibration fatigue analysis with HWPA program (DesignLife)
• Cell material properties characterizing with HyperStudy
• Concluding Remarks
A123 Engineering Simulation Capability
A123 Systems
Engineering Simulation
CFD and Thermal Management
Cooling Concept Development and
Validation
Battery Life Analysis
Battery Life Estimation Software Development
Finite Element Analysis
Linear Statics and Modal Frequency
Validation
Module and Pack Level Thermal and Flow Analysis
Thermal/Electrical Coupling (Joule Heating)
Thermal Analysis for Electronics
Battery Life Analysis
Battery Electrical Performance Simulation
Random Vibration and Fatigue
Mechanical Shock and Drop Analysis
Nonlinear Statics
Cell R&D and External Supplier
Pack and Module Level FEA Analysis
• Linear Statics and modal frequency analysis• Modal frequency analysis
• Foot/knee load, handle load, and lifting assistance analysis
• Topology/topography/shape/gauge optimization
• Random vibration stress and fatigue analysis• RMS stress calculation
• Fatigue life calculation for metal parts
• Mechanical shock, pothole, and drop analysis
• Nonlinear and contact analysis • Snap-in/pull-out force estimation
• Jack loading analysis
• Bolt assembly, module pressure plate, etc.
FEA Tools Used in A123 Systems
• Altair HyperWorks Suite• Radioss/Bulk
• Radioss/Block
• OptiStruct
• HyperStudy
• LS-DYNA3D
• ABAQUS (Implicit/Explicit)
• Access to other software through HyperWorks Partner Alliance License• nCode DesignLife
• Key to Metals
• Others
• Altair PBS Pro
Random Vibration Analysis Random Vibration Analysis
on Battery Pack
Battery Pack Vibration Analysis
• A123 conducts random vibration stress and fatigue a nalysis according
to customer specifications or industrial standards
• Approach• Use Radioss/Bulk to calculate RMS stresses from the PSD profiles
• Estimate fatigue life using nCode DesignLife if necessary
SAE J2380 PSD Profiles
Example – Random Vibration Analysis
• A prototype battery pack had a test failure on moun ting brackets during
random vibration test
• The analysis team was involved to identify the root causes of the
failures and find the solution in a limited time fr ame
Challenges
• A few locations on mounting brackets showed fatigue cracks
• Initial random vibration stress analysis showed the failure locations
have high RMS stress during vibration events, but i t cannot
accurately quantify the fatigue life
• The fatigue properties for the metal components wer e unknown• The fatigue properties for the metal components wer e unknown
• Project timing and budget won’t allow performing ma terial test to
obtain the fatigue properties
Correlating the Fatigue Properties
• nCode DesignLife was used to evaluate the fatigue l ife of metal
components:• The stress-life properties were estimated in DesignLife based on material specs
• Random vibration fatigue engine was used to estimate the fatigue life of the metal
components
• The fatigue properties and analysis parameters were then adjusted to correlate
the analysis results with test resultsthe analysis results with test results
Vibration Fatigue Analysis EngineMaterial Stress Life Curve
Result Comparisons
• With correlated fatigue properties, the analysis id entified all test failure
locations:• The failure locations have relatively high RMS stresses comparing to material specs
• The fatigue lives in these locations are lower than the requirement
� 3 RMS stress: 72% of material σuts
� Fatigue life: 10% of required life� 3 RMS stress : 55% of material σuts
� Fatigue life: 90% of the required life
10% of required life90% of required life
Improve the Design Through Analysis
• Based on the analysis results, new design concepts were proposed:• Change the shape of the components
• Add reinforcement brackets
• Change welding patterns
• New pack design passed the random vibration fatigue analysis
• These design changes were implemented and the new p ack went
through random vibration test without fatigue issue
Infinite 65 lives
Prismatic Cell material Prismatic Cell material
Property Characterization
Challenges for Battery Module Modeling
• Modal frequency is critical for battery
pack design, and battery modules
play a significant role
• Cell property largely unknown
• Ideally, we would like to use a simple
homogenized model to represent the homogenized model to represent the
complex structure of the module
(cells, heat sinks, and bands)
• The first few modal frequencies of the
module model should meet the test
results
Two Module Modeling Approaches
• Homogenized model
• Cell, heat sink, compliance pad are
homogenized into blocks
• End plate is modeled with shell
elements as one plane sheet
• Module bolt is modeled with beam
elements
• Detailed model
• Each component is modeled in detail with
corresponding material properties
• End plate is modeled in detail with shell
elements
• Module bolt is modeled with beam
elements
• All materials are isotropic
• Pros and Cons:
• Can be quick modeled and use very
little CPU time
• Accuracy is compromised due to
simplification
• Pro and Cons:
• Can better predict module dynamic
behavior
• Long modeling time due to complexity of
the module
• High CPU and memory costs
Hybrid Module Modeling Approach
Y
Z
X
Z
• Endplate modeled in detail by shell element
• Bolt was modeled by beam element with rod section
• Cell, heat sink, cell compliance pad, band were hom ogenized into a 3-d
orthotropic material
• Local coordinate system was used for the orthotropi c material modeling
Characterizing the Material
• Three modules were tested with free-free and fixed BC• Large size module, medium size module, and small size module
• For free-free boundary condition, the first 3 modes from test were used
for FEA model correlation
• For fixed boundary condition, the first 5 modes fro m test were used in
FEA model correlationFEA model correlation
• Homogenized orthotropic material was formulated usin g the following
engineering constants
Characterizing the Material
• Goal was to adjust E1, E2, E3, G12, G13, G23 to cor relate both the
mode shapes and frequencies with test results.
• Observations during initial evaluation: • Some Eii, Gij, and vij have strong influence to long and medium size modules’
modal frequencies;
• Other Eii, Gij, and vij have significant effect to small module modal frequencies• Other Eii, Gij, and vij have significant effect to small module modal frequencies
• The remaining Eii, Gij, and vij have little effect to the first 3 modal frequencies at
all. In that case, they are assigned to zero, leading to a simple material matrix
• Material parameters were first manually adjusted to match modal
shapes in order.
• Then HyperStudy was used to match first 3 frequenci es more closely
Modal Correlation
• HyperStudy
Modal Correlation
• HyperStudy
Modal Correlation
• HyperStudy
Results Correlations
Free-free BC 1st Mode 2 nd Mode 3 rd Mode
Large module 0.6% .48% 0.%
Medium module 3.3% 2.7% 1.5%
Small module .27% 5.9% 2.8%
Table-1: Relative Deviations of Estimated Modal Frequencies from Test Results under free-free condition
Fixed BC 1 st Mode 2nd Mode 3 rd Mode 4th Mode 5th Mode
Large module 4.5% 10.7% 1.6% 2.1% 0.3 %
Medium module 1.5% 9.5% 8.1% 17.5% 24.2%
Small module 0.1% 7% 8.1% -- --
Table-2: Relative Deviations of Estimated Modal Frequencies from Test Results under fixed condition
Illustration of Typical Module Mode
Summary of Hybrid Module Model
• This hybrid module model was a compromise among all 3 size modules,
with deviation within 5% in free-free boundary cond ition
• The hybrid module model was more skewed to large si ze modules
because for small size modules, the first frequency is very high already,
making them less sensitive to external vibration.
• By using such approach, a battery module for pack a nalysis can be • By using such approach, a battery module for pack a nalysis can be
quickly modeled and still achieve good analytical r esults
Concluding Remarks
• A123 has a broad range of engineering simulation ca pabilities to
support battery pack/module development activities
• Altair’s HyperWorks Suite and HWPA are the best cos t-effective tools to
match A123’s FEA simulation requirements