Electric Vehicle Enhanced Fast Charging Enabled by Battery Thermal Management and Model Predictive Control

Abstract

This paper explores the synergy between battery thermal management (BTM) in an electric vehicle (EV) and battery charging. A model predictive control (MPC) based approach is proposed to minimize the energy used for BTM during the drive and fast charging stages and the estimated charging time while enforcing constraints imposed on state-of-charge (SOC), power, and thermal conditions of the battery. An adaptive strategy is developed to adjust the weight of the two competing objectives in the MPC cost function to manage the trade-off between BTM energy consumption and charging time. The sensitivity of the proposed MPC-based BTM strategy to uncertainties in the fast charging station availability is also investigated. Our results show that a 12.3% of decrease in the charging time could be achieved by optimally performing BTM at the cost of negligibly higher BTM energy usage in the case study conducted.