Parametric optimization for liquid cooling microchannels of AUV’s battery thermal management system

Autonomous underwater vehicles (AUVs) play an important role in ocean exploration. When an AUV works for a long time and discharges at a high rate, the heat of the battery cannot be dissipated due to the narrow and closed working space of the battery module, thus causing a sharp rise in temperature and restricting the safety of the AUV. Therefore, it is very crucial to solve the heat dissipation problem of the battery module in AUV. In this study, a surrogate model is proposed based on the genetic algorithm for parametric optimization, which uses the strategy of microchannel liquid cooling. The optimization design mainly includes establishing a parameterized model and numerical simulation to solve the temperature field, using Latin hypercube sampling to complete the selection of design of experiment points, generating a response surface through the Kriging surrogate model, and using a multi-objective genetic algorithm for solving candidate points under constraint conditions. It can be concluded that the optimized parameters play a certain role in reducing the temperature of the whole battery module and reducing the volume of microchannel. The results show that the temperature field is especially sensitive to the parameters W₁, H₂, and v₁. When the corresponding parameters are W₁ = 3.59 mm, H₁ = 17.93 mm, H₂ = 4.98 mm, and v₁ = 0.02 m/s, the temperature reaches the limit, and the volume of the whole cooling scheme is the smallest. Compared with the initial design point, the maximum temperature is reduced by 0.66 K, and the volume is reduced by 1.84%. In addition, the optimized parameters enable the battery module to reach a lower equilibrium temperature in a shorter time, thereby enhancing the safety and stability of the battery module. This study provides a feasible reference scheme for the heat dissipation of battery modules in the future.