Structure optimization of permanent magnet spherical motor utilizing improved Particle Swarm algorithm

Abstract

The improved particle swarm optimization (PSO) algorithm is used to optimize the structure of permanent magnetic spherical motor with four pairs of rotor poles. The objective is to maximize peak value of output torque and peak value of magnetic flux density. Seven variables are selected which are rotor radius, rotor core radius, the longitudinal angle and the latitudinal angle of single rotor pole, coil length, coil angle. Firstly, the magnetic field model and torque model of optimization is built. Based on the two models above, the objective function is deduced. Then the spherical motor is optimized based on the improved PSO algorithm. Finally, the optimization results indicate that the optimal structure parameters are obtained. In a word, Improved PSO algorithm shows great advantage in the optimal design of motor.