Efficient Battery Development
"The ability to analyze all characteristics of a battery pack/module within a single environment and ensure the correct overall performance is a key driver in reducing prototype/testing cost and ensuring reliability of batteries in the industry."
Gaetan Damblanc
CD-adapco’s battery modelling technical lead
Project members
Problem definition
This study looks at a multiphysics approach using CAE to help improve and optimise a Li-ion battery pack. The present studied battery pack is a complex system from Behr, in which several interactive physics are involved:
- The electrochemical behaviour of the Li-ion battery cells under electrical load
- The thermal and fluid effect of the liquid coolant in the cooling plates
- The different heat transfer mechanisms in the solids, fluids and solid/fluid contact areas.
Changes in one of these will affect the other two and the main challenge was to be able to predict accurately in a timely and cost effective manner such a complex system using simulation.
Challenge
- Coupling of a thermal fluid- 3D model of the complete lithium-ion battery module (consisting of multiple cells, cooling circuit, housing) with an electrothermal circuit model for the Li-ion cell performance prediction
- Verification and validation of the coupled simulation and numerical models using experimental results
Objective of simulation:
- Cell temperature prediction, Cooling optimization, thermal management, energy management, thermal runaways
Solution
The proposed methodology is able to evaluate the battery pack requirements concerning thermal and electrical performance, temperature and state of charge inhomogeneity. The proposed study has confirmed that simulation of Li-ion batteries can be used for:
- Cost reduction (e.g. coolant design optimization)
- Reliability studies (e.g. taking into account cell to cell variations due to manufacturing process by variation of thermal and electrical material properties)
The model accuracy on cell and module level has been evaluated by means of validation experiments. The simulation and experimental results show good quantitative and qualitative agreement. The computed error in validated tests lies within 10%.