Structure optimization of liquid-cooled lithium-ion batteries based on particle swarm algorithm

Abstract

If lithium-ion batteries are used under high temperature conditions for a long time, it will accelerate the aging of the battery, and the excessive temperature difference will also affect the consistency of the battery. The cooling system of the battery can make the battery work more safely, and it is important to optimize the heat dissipation of the Lithium-ion battery. It is difficult for batteries to improve the overall performance by optimizing only a single factor. Based on orthogonal analysis and response surface, the thermal performance of the cell was analyzed with five factors, such as runner thickness, runner width, inlet temperature, inlet flow rate, and ambient temperature. A particle swarm algorithm was used to optimize the parameters of the variables, and the best cooling performance can be obtained with the optimized parameters. Using this optimization method, the overall temperature of the cell can be reduced and the uniformity of temperature distribution can be improved. The strategy can be widely applied to improve the structure of the cell and reduce the analysis time.