Multiphysics CAE Analysis of Battery Packs

【 Background 】

       With the rapid development of electric vehicles, the battery module — which stores electrical energy — has become a key technology. As battery energy density continues to increase, concerns about heat dissipation and safety also grow. Currently, the battery system faces three major challenges:

1. Crash safety issues (structural mechanics)

2. Cooling and thermal management issues (fluid mechanics)

3. System-level applications (systems engineering and control analysis)

       These three challenges involve different physical domains, requiring multi-physics solutions to properly evaluate battery safety performance. In response to this need, Altair developed a battery analysis module that integrates various physics solvers to create a comprehensive multi-physics solution for battery packs.

【 Results 】

1. Based on micro-scale models, established equivalent homogeneous mechanical and electro-thermal properties, then applied these homogenized results to macro-scale models to further validate mechanical and thermal responses.

2. Validated averaged material mechanical properties with experimental data, identified the relationship between short-circuit and strain, and developed a mathematical model for power loss after short-circuit.

3. Successfully applied the validated cell model for multi-physics simulation.

4. Simulation results match experiments very well. This enables reliable prediction of battery thermal runaway after crashes, improving EV safety and supporting future development.

5. For thermal management under normal operation, CFD simulation with UDF-based heat generation and anisotropic materials successfully predicted battery pack temperature rise, assisting in thermal system design.

6. For system-level analysis, romAI was used to build reduced-order dynamic system models based on AI and classical control theory. These were successfully applied to system-level battery pack simulations, enabling accurate prediction of battery power behavior affected by driving patterns, mileage accumulation, and state of charge—greatly improving EV range estimation during development.

【 Technical Features 】

1. Automated tools for rapid micro-scale model creation, enabling efficient material homogenization workflows.

2. The entire battery pack module is built using HyperWorks solvers and OEM-developed material subroutines. This creates a streamlined one-platform workflow without requiring third-party solvers, reducing learning effort and software procurement cost for customers.