Surrogate based multi-objective design optimization of lithium-ion battery air-cooled system in electric vehicles

An effective and efficient lithium-ion Battery Thermal Management System (BTMS) design can significantly improve the performance of the battery pack. However, it is difficult to achieve an effective design of BTMS as there are several parameters from multidisciplinary fields that are needed to be optimized simultaneously. Thus, to solve this multi-objective optimization problem, a new type of finned forced air-cooled BTMS is designed. An optimization design method based on the surrogate is then proposed. This method decomposes the BTMS optimization problem into three subproblems such as thermodynamic problem, fluid dynamics problem, and mechanical structure problem. The optimization goal is to minimize the average battery temperature, the standard deviation of battery temperature, and the pressure drop of the BTMS system. Besides, the lightweight design of the heat dissipation system structure is also discussed. Finally, the optimal design involving multiple conflicting objectives in BTMS is generated by Multi-objective Genetic Algorithm (MOGA). From set of solutions, an optimal solution is selected. The optimized BTMS find a balance between cooling efficiency, system volume and power consumption.