Lithium-ion battery packs' discharging results in significant heat generation, which leads to safety issues and negative impact during the application of electric vehicles. Previous studies focused more on the configurations and design of cell packs/modules with a cooling system to control the battery cell's temperature. However, temperature differences are more difficult to control to ensure thermal uniformity. Maximum pressure is a significant parameter that affects energy consumption and the cost of the cooling system. This study proposed a comprehensive approach to design an efficient mist cooling system, which considered both maximum temperature and temperature standard deviation. This design method generates candidate design points by Latin Hypercubes Sampling and design of experiments (DOEs); effects of some significant parameters of the cooling structure on the cooling efficiency are evaluated by sensitivity analysis. Surrogate models are then selected and optimized by the multi-objective optimization approach to acquire an optimal scheme of the mist cooling structure. The optimized results showed that the optimized mist cooling battery module has better thermal performance with a lower cost. This approach can be used in the battery pack design process to control the temperature rise and temperature distribution, and energy consumption of the cooling system.