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

机译:改进粒子群算法的永磁球形电动机结构优化

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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.
机译:改进的粒子群算法(PSO)用于优化四对转子磁极的永磁球形电动机的结构。目的是使输出转矩的峰值和磁通密度的峰值最大化。选择七个变量,分别是转子半径,转子铁心半径,单个转子磁极的纵向角度和横向角度,线圈长度,线圈角度。首先,建立了优化的磁场模型和转矩模型。基于以上两个模型,推导了目标函数。然后,基于改进的PSO算法对球形电动机进行了优化。最后,优化结果表明获得了最佳的结构参数。总之,改进的PSO算法在电机的优化设计中显示出很大的优势。

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