Battery Thermal Management for Fast Charging based on Nonlinear Model Predictive Control

Abstract

Thermal management of the battery during fast charging is crucial for charging time, energy consumption and safety. To address this challenge, this paper introduces a novel battery thermal management strategy for fast charging of battery electric vehicles based on nonlinear model predictive control (NMPC). First, a control-oriented model is parameterized using measurement data of a state-of-the-art battery electric vehicle (BEV). The optimal thermal management strategy for fast charging under a wide range of conditions is then calculated. Based on the optimization results, battery temperature thresholds as functions of the state of charge are used as references within the real-time capable controller. The controller's performance is subsequently tested using a validated high-fidel-ity simulation model. Compared to the baseline rule-based strategy, the NMPC can save up to 51% in auxiliary energy consumption at medium and high ambient temperatures through efficient cooling, while reducing charging time by up to 4.5% at low ambient temperatures through aggressive heating.