Optimization of Cooling Strategy for Lithium Battery Pack Based on Orthogonal Test and Particle Swarm Algorithm

This paper describes the design and optimization of a cooling strategy based on a battery cooling system with indirect liquid-cooled plate heat exchange. The performance of the battery cooling system was analyzed using single-factor thermal simulation analysis. A cosimulation platform was built, and the rule-based multiparameter control strategy was used to design the heat dissipation logic, which was verified in the cosimulation platform. To improve the heat dissipation performance further, an orthogonal test (OT) was used to analyze the effects of different control parameters on each performance index during the battery discharge process, and the optimal combination of control parameters under a balanced multiobjective strategy was obtained. The results of the particle swarm optimization (PSO) algorithm with different weight coefficients were introduced for comparison. It was found that the OT and PSO can keep the temperature difference within the safe range. The maximum temperature was reduced by 3.57 and 4.10 K, respectively, and the average output power was increased by 11% and 9%, respectively, which indicates that the OT maintained good performance despite the significant workload reduction. The feasibility and reliability of the battery thermal management system control strategy optimized using OT were verified.