The short primary permanent magnet synchronous motor with auxiliary pole type could theoretically achieve the mutual offset of auxiliary pole detent force and armature detent force by optimizing the motor structure,so as to achieve the purpose of reducing the high thrust fluctuation while maintaining high thrust.However,the characteristics of permanent magnet synchronous linear motor(PMLSM)with many parameters to be optimized and electromagnetic nonlinearity increased the difficulty and workload of optimization design.In order to enhance the optimization and design efficiency,a novel Pareto ant colony optimization algorithm(Pareto ACO)was proposed.The variable pheromone volatility coefficient was adopted instead of the traditional fixed volatility coefficients,which resulted in faster global exploration and local search.By compared the results with similar multi-objective algorithms regarding the three test functions,the performance of Pareto ACO was superior.The Pareto ACO algorithm was used to carry out multi-objective optimization of the structural dimensions of slots,auxiliary poles,and permanent magnets for short primary permanent magnet synchronous linear motors with auxiliary pole type.The optimization results show that the algorithm can effectively save the permanent magnet material and reduce the thrust fluctuation,and finally the experiment verifies the effectiveness of the algorithm.
关键词
永磁同步直线电机/帕累托蚁群优化算法/可变信息素挥发系数/多目标优化/定位力
Key words
PMLSM(permanent magnet linear synchronous machine)/Pareto ACO/variable pheromone volatility coefficient/multi-objective optimization/detent force
维普
万方数据