模型预测控制在电池二次冷却系统中应用研究

This paper proposes control strategy based on Model Predictive Control (MPC) algorithm for the secondary cooling system of train battery. The study focuses on designing MPC and Proportion Integration (PI) control strategies for the battery secondary cooling system, and compares their control effects on the battery cooling rate. Under the battery charging and discharging conditions of 20 A and 30 A, the MPC control strategy achieves stable battery temperature in 37 s and 63 s, respectively, while the PI control strategy achieves stable battery temperature in 280 s and 500 s, respectively. The results show that compared with the PI control strategy, the MPC control strategy can significantly accelerate the battery cooling rate, and the control system has better robustness and adaptability.