Optimization of a Dual-Channel Water-Cooling Heat Dissipation System for PMSM in Underwater Unmanned Vehicles Using a Multi-Objective Genetic Algorithm

To minimize the temperature of the propulsion motor and reduce flow loss in the water-cooling structure during the operation of an underwater unmanned vehicle, this paper employs a multi-objective genetic algorithm to optimize the dimensions of the inner and outer dual-channel water-cooling structure as well as the flow rate of the cooling water. Firstly, the influence of design variables on response variables was examined through sensitivity analysis. Subsequently, a model sample library for simulating the coupled temperature and flow fields of the motor was constructed, and a response surface model between the variables was developed. Finally, appropriate sample points were selected from the Pareto solution set to verify the validity of the optimization results through CFD simulation and error analysis. The sensitivity analysis results indicate that the cooling water flow rate had the greatest impact on both the maximum motor temperature and the flow losses of the water-cooling structure, with values of 77.79% and 99.84%, respectively. On the other hand, the optimal design parameters for the four dimensions of the channel and the cooling water flow rate were obtained. Compared with the initial dimensions of the water-cooling structure, the maximum temperature of the motor decreased from 332.86 K to 331.46 K. Simultaneously, the flow loss of the water-cooling structure decreased from 100.02 kPa to 59.58 kPa, with a maximum reduction rate of 40.43%. The optimization effect of the motor cooling system is significant, which provides valuable insights for system design under the premise of ignoring multi-objective interactions.