Webinar: Electro-thermal Coupled Model for 48V Li-on Battery Pack Using Reduced Order Thermal Model
Learn how ANSYS powerful tools and technology can be used to develop better battery management systems (BMS)
Numerical thermal simulations are powerful tools for battery pack and battery module development by predicting thermal performances and guiding design iterations.
3D commercial software with multiphysics modeling is able to provide detailed solutions on battery cells and power electronics cooling. However, it is usually time-consuming and not compatible with the models of battery management systems (BMS).
Alternatively, engineers were seeking to build a 0D/1D thermal model, for example a thermal network, for reducing computational overheads. Meanwhile, such a thermal network approach typically has case-by-case fidelity and requires a vast number of human labors on manual parameter tuning and optimization.
The Reduced Order Model (ROM) is a systematic methodology to build such a thermal model. It is realized by state space model, which is fitted to have the heat transfer function calculated from 3D results.
A ROM can be generated via a well-defined automatic process in ANSYS TwinBuilder with well-controlled accuracy. A ROM can then be exported into a functional mock-up unit (FMU) and shared or utilized by various systems accepting FMUs.
In this presentation, an electro-thermal coupled battery model for an A123 liquid-cooled 48V Li-on battery pack is developed. The electrical part in the coupled model uses the equivalent circuit model (ECM) approach due to its speed and accuracy. The thermal part in the coupled model uses the ROM approach.
Compared with the common thermal network approach, the ROM approach demonstrates higher level accuracy and convenience. The coupled model, as part of a BMS, is then simulated in Matlab Simulink.
The capability of the coupled model on developing derate function in battery state of power (SoP) algorithm is demonstrated. It is shown that current derate caused by battery overheating is accurately captured under a dynamic drive cycle current profile. Such a ROM-based electro-thermal coupled model proves to be a powerful tool for BMS development.
Register for this webinar to learn:
- How to reduce computational overheads with compatibility with many models of battery management systems (BMS)
- How the Reduced Order Model (ROM) approach demonstrates higher level accuracy and convenience
- How ANSYS TwinBuilder provides a well-defined automatic process
Presenters:
Yufeng Liu
CFD/Thermal Engineer
A123 Systems LLC
Yufeng Liu is a CFD/Thermal Engineer at A123 System LLC, MI. Yufeng has been working at A123 for three years on thermal and CFD analysis for battery CAE engineering.
Yufeng has been actively involved in supporting multiphysics numerical simulations of A123 48V mild hybrid and HV battery pack applications. More recently, he has been focusing on development of efficient electro-thermal coupling modeling for battery thermal management. Yufeng holds a MSc degree in Mechanical Engineering from the University of Connecticut.
Xiao Hu
Principal Engineer
ANSYS Inc.
Xiao Hu is a principal engineer at ANSYS Inc. Xiao has spent a combined 19 years of his career at ANSYS and Fluent Corporation working with customers in the modeling and simulation of powertrain related applications.
More recently, he has been focusing on applications involving batteries for HEV and EV including battery electro-thermal coupling and electrochemistry modeling. Xiao has a PhD in mechanical engineering from Purdue University.
