Evolutionary Soft Actor-Critic Based Integrated Thermal Management Strategy for Battery Electric Vehicles

In the pursuit of decarbonization within the transportation sector, battery electric vehicles (BEVs) have emerged as a pivotal solution due to their zero-emission characteristics. However, the thermal management systems of BEVs have become a critical bottleneck, particularly under extreme temperatures, where dual energy loads from battery cooling and cabin air-conditioning reduce driving range by up to 37%. To address this issue, this study proposes a soft actorcritic (SAC) based integrated thermal management strategy (TMS). By integrating the stochastic strategy optimization of SAC with thermodynamic principles, the proposed TMS efficiently manages the synergistic operation of battery-motorcabin loops. To enhance the global search efficiency of SAC, the cross entropy method (CEM) is introduced, thereby avoiding local optima. Simulation results demonstrate that proposed evolutionary SAC-based TMS outperforms conventional rule-based and other DRL-based TMSs, achieving a 22.78% reduction in energy consumption and superior temperature control of the battery, motor, and cabin.