Multi-Objective Optimization Analysis of Oil Pump Motor Based on NASG II Algorithm

This paper aims to improve the conversion efficiency of the motor while increasing the motor torque and performs multi-objective optimization of the motor to achieve the best results. Aiming at the traditional genetic algorithm is easy to cause local convergence, poor data target diversity, late convergence of the calculation speed is slow and other problems. In this paper, NASG II algorithm is adopted to take the pump motor as the research object, and Maxwell and Workbench are used for joint simulation. The base variables are total permanent magnet width, spacer width, slot width, slot depth, slot shoulder height, magnetic bridge thickness, permanent magnet thickness, distance from rotor inner diameter to magnetic bridge, magnetic bridge width, and the reference variable is bridge width. Efficiency and torque are the optimization objectives and the optimum solution at the Pareto frontier point is selected using the distance between superior and inferior solutions (TOPSIS) method for the 83Kw high power built-in V-rotor motor. In this paper, the stator and rotor structural parameters are taken as optimization variables and sensitivity analysis is carried out to obtain the effect of each variable on the output torque and efficiency of the motor. The results show that by this optimization method, the motor torque is increased from 173.3Nm to 183.1Nm, an increase of 5.7%, and the motor efficiency is increased from 97.1% to 97.9%, an increase of 8%