基于克隆选择差分进化算法的永磁同步电机参数辨识

Parameter identification of PMSM based on differential evolution immune clonal selection algorithm

针对永磁同步电机(PMSM)多参数高精度辨识的问题,提出了一种克隆选择差分进化(DE-ICSA)算法,将其运用于永磁同步电机的多参数在线辨识。算法通过对差分进化算法与免疫克隆选择算法进行混合优化,提高了种群多样性,加强了局部和全局的搜索能力。通过仿真实验表明:相较于差分进化算法与粒子群优化(PSO)算法,所提算法能同时辨识定子电阻、dq轴向电感和转子磁链等电磁参数,并且具有较好的收敛性和可靠性。

Aiming at the problem of high-precision identification of multi-parameter identification of permanent magnet synchronous motor(PMSM),a differential evolution immune clonal selection algorithm(DE-ICSA)is proposed,which is applied to the multi-parameter identification of permanent magnet synchronous motors.This algorithm improves the diversity of the population and enhances the local and global search capabilities through the hybrid optimization of the differential evolution algorithm and the immune clone selection algorithm.Simulation experiments show that,compared with the differential evolution algorithm and the particle swarm optimization algorithm,the algorithm can simultaneously identify electromagnetic parameters such as stator resistance,dq-axial inductance and rotor flux linkage,and has better convergence and reliability.