Abstract
The battery thermal management system plays an important role in controlling the operating temperature of the battery pack, delaying the aging of the cell and improving the safety performance of the electric vehicle. The optimization of the structure and parameters of traditional battery cooling system often requires a large number of experiments and simulations to find the best design scheme, and high optimization cost and long optimization time often make the optimization technology route of “simulation experiment + intelligent optimization” difficult to achieve. A new technical route for parameter optimization of power battery air cooling system is designed in this paper. In the proposed technical route, the cooling effect of the representative design scheme is evaluated by simulation experiment, and the cooling effect of the non-representative design scheme is evaluated by fitness estimation. Compared with the traditional air cooling system optimization method, the optimization time of the design parameters of the maximum temperature, average temperature and maximum temperature difference of the battery box is shortened from 210,604 s, 210931 s, 210773 s to 45,884 s, 46722 s and 46,011 s, respectively. The temperature errors are 0.27 °C, 0.37 °C and 0.30 °C respectively. The simulation results show that the proposed technical route for optimization design based on fitness estimation can effectively reduce the optimization time of battery thermal management system and has engineering application value.
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