Modeling and Analysis of the Battery Packs and Modules in A123 Systems
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The document outlines A123 Systems' engineering simulation capabilities for battery pack and module development, detailing various modeling and analysis techniques, such as random vibration fatigue analysis and finite element analysis (FEA). It discusses challenges faced during testing, including fatigue life estimation of metal components and the use of different modeling approaches to predict dynamic behavior accurately. Conclusively, A123 employs Altair's Hyperworks suite for effective simulation, correlating analysis results with empirical data to improve battery module design.
Modeling and Analysis of the Battery Packs and Modules in A123 Systems
- 1. Modeling and Analysis of the Battery Packs and Modules in A123 Systems Binshan Ye & Shawn Zhang A123 Systems, Inc.
- 2. 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
- 3. A123 Engineering Simulation Capability A123 Systems Engineering Simulation CFD and Thermal Management Battery Life Analysis Finite Element Analysis Cooling Concept Linear Statics and Battery Life Estimation Development and Modal Frequency Software Development Validation Random Vibration and Module and Pack Level Fatigue Thermal and Flow Analysis Battery Life Analysis Mechanical Shock and Thermal/Electrical Battery Electrical Drop Analysis Coupling (Joule Heating) Performance Simulation Nonlinear Statics Thermal Analysis for Electronics Cell R&D and External Supplier
- 4. 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.
- 5. 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
- 6. Random Vibration Analysis on Battery Pack
- 7. Battery Pack Vibration Analysis • A123 conducts random vibration stress and fatigue analysis 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
- 8. Example – Random Vibration Analysis • A prototype battery pack had a test failure on mounting 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 frame
- 9. 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 it cannot accurately quantify the fatigue life • The fatigue properties for the metal components were unknown • Project timing and budget won’t allow performing material test to obtain the fatigue properties
- 10. Correlating the Fatigue Properties • nCode DesignLife was used to evaluate the fatigue life 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 results Material Stress Life Curve Vibration Fatigue Analysis Engine
- 11. Result Comparisons • With correlated fatigue properties, the analysis identified 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 90% of required life 10% of required life 3 RMS stress : 55% of material σuts 3 RMS stress: 72% of material σuts Fatigue life: 90% of the required life Fatigue life: 10% of required life
- 12. 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 pack went through random vibration test without fatigue issue Infinite 65 lives
- 13. Prismatic Cell material Property Characterization
- 14. 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 complex structure of the module (cells, heat sinks, and bands) • The first few modal frequencies of the module model should meet the test results
- 15. Two Module Modeling Approaches • Homogenized model • Detailed model • Cell, heat sink, compliance pad are • Each component is modeled in detail with homogenized into blocks corresponding material properties • End plate is modeled with shell • End plate is modeled in detail with shell elements as one plane sheet elements • Module bolt is modeled with beam • Module bolt is modeled with beam elements elements • All materials are isotropic • Pro and Cons: • Pros and Cons: • Can better predict module dynamic • Can be quick modeled and use very behavior little CPU time • Long modeling time due to complexity of • Accuracy is compromised due to the module simplification • High CPU and memory costs
- 16. Hybrid Module Modeling Approach Z Z X Y • Endplate modeled in detail by shell element • Bolt was modeled by beam element with rod section • Cell, heat sink, cell compliance pad, band were homogenized into a 3-d orthotropic material • Local coordinate system was used for the orthotropic material modeling
- 17. 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 from test were used in FEA model correlation • Homogenized orthotropic material was formulated using the following engineering constants
- 18. Characterizing the Material • Goal was to adjust E1, E2, E3, G12, G13, G23 to correlate 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 • 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 frequencies more closely
- 22. Results Correlations Table-1: Relative Deviations of Estimated Modal Frequencies from Test Results under free-free condition Free-free BC 1st Mode 2nd Mode 3rd Mode Large module 0.6% .48% 0.% Medium module 3.3% 2.7% 1.5% Small module .27% 5.9% 2.8% Table-2: Relative Deviations of Estimated Modal Frequencies from Test Results under fixed condition Fixed BC 1st Mode 2nd Mode 3rd 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% -- --
- 23. Illustration of Typical Module Mode
- 24. 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 condition • The hybrid module model was more skewed to large size 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 analysis can be quickly modeled and still achieve good analytical results
- 25. Concluding Remarks • A123 has a broad range of engineering simulation capabilities to support battery pack/module development activities • Altair’s HyperWorks Suite and HWPA are the best cost-effective tools to match A123’s FEA simulation requirements