Real-time Modeling of Battery Pack Temperature for Thermal Limit Prevention in Electric Race Vehicles

Abstract

As the automotive industry moves towards reducing CO2 emissions, battery powered electric vehicles are becoming a commercial reality. Though Lithium ion battery technology has significantly improved with recent research and development efforts, batteries still suffer from fundamental thermal limits that can decrease vehicle longevity, durability, and safety. Currently, methods exist to model temperature behavior of individual cells and heavy computational resources can be used to predict battery pack temperatures. This study develops a computationally fast simulation tool that provides real-time prediction of the temperature of a battery pack. Unlike the methods currently available, this simulation tool is based on an accurate and robust electrochemical-thermal model for a Lithium ion battery pack that predicts the temperature distribution across the cells during current cycling operations with real-time computation capabilities. Starting from a pre-existing electrochemical-thermal model developed for individual cells, a predictive battery temperature model characterizing thermal losses and heat transfer parameters of full battery packs was created, verified, and tuned. The properties of the battery pack, such as battery chemistry, spatial cell arrangement, and electrical layout, can then be altered in the model to perform design experiments comparing differing pack parameters. The developed model is a useful tool to study the dynamic behavior of any vehicular battery pack, to inform pack cooling design, and to be used in advanced temperature management systems to control and predict battery temperature.