Research on Thermal Management Control Methods Based on PID Algorithm

This study aims to explore the application of integrated thermal management systems in pure electric vehicles by comparing traditional PID controllers with fuzzy controllers to optimize system performance. Using AMESim software, an integrated thermal management system model was constructed, encompassing the passenger cabin air conditioning system, battery pack thermal management system, and motor thermal management system. A control strategy based on logic threshold control principles was designed. Simulations were conducted under WTVC conditions to compare the temperature response and system efficiency of PID control and fuzzy control in different environmental conditions. The results show that fuzzy control has better control effects and energy efficiency compared to traditional PID control, meeting the cooling, heating, and thermal comfort needs of each subsystem. Additionally, the study investigated the impact of motor waste heat utilization on battery preheating. The results indicate that, under winter cold start conditions, waste heat utilization can accelerate battery heating, reduce heating time, and improve driving range. The proposed integrated control strategy and fuzzy control method provide new technical support and references for the design of thermal management systems in pure electric vehicles.