Model-Based Design of LFP Battery Thermal Management System for EV Application

Abstract

This study uses an equivalent circuit model (ECM) and real-time data to model lithium iron phosphate (LFP) batteries to accurately represent their thermo-electrical behavior. In particular, the focus is on a thermal management perspective in high-performance electric vehicles (EVs). The ECM-based battery management system, which effectively captures the non-linear behavior of Li-ion batteries, is developed to optimize the safety, lifespan and overall performance of the EV battery management system. The ECM-based battery model is validated using real-time drive cycle data to enhance the understanding of battery management systems, contributing to improved overall performance and reliability. In addition, advanced estimation algorithms, such as the extended Kalman filter, are integrated to further improve the predictive capabilities of battery parameters. Battery terminal voltage prediction with an average RMSE error of 0.015% is achieved, highlighting the critical role of ECMs and advanced numerical simulation methods in optimizing the performance of automotive battery management systems. The achieved results provide important guidance for model-based design validation and functional development of battery management for mobility applications.

Keywords

• equivalent circuit model
• extended Kalman filter
• air-cooled battery thermal management system
• model-based design of Li-ion batteries
• online battery parameter estimation