Optimization design of an AUV's motor with counter-rotating rotors based on the collaborative multi-objective particle swarm algorithm

An autonomous underwater vehicle (AUV) in design requires a new motor with counter-rotating rotors which should have a high efficiency and a small mass, and can be operated for a relatively long time in a closed space where the temperature rise must be considered. An electromagnetic-thermal coupling analysis model and an improved multi-objective particle swarm optimization (MOPSO) algorithm based on the Pareto optimal are used for the design of the motor. Firstly, an analytical model is applied for the calculation of the air gap magnetic field, an equivalent thermal network analysis is used to calculate the motor's temperature rise, and the interaction between the electromagnetic field and the thermal field is considered. Secondly, the computational fluid dynamics (CFD) method is used for calculating the convection heat transfer coefficient of the rotating parts of the motor and the AUV shell to solve the problem of the inaccurate equivalent thermal resistance. Finally, the efficiency and the mass are set as the optimization objectives, the temperature rise and the geometric condition are designated as the constrains. Then the results of a two sub-groups collaborative MOPSO algorithm is compared with the results of the standard multi-objective optimization algorithm NSGA-II. The Pareto front shows that the method can obtain a solution set that is closer to the true Pareto front with good distribution. The experimental results of the prototype show that all the indices including power, speed, efficiency and mass meet the requirements, and the temperature rise after 5 hours' full-load is satisfied.