现代电子技术2025，Vol.48Issue(10)：25-30,6.DOI:10.16652/j.issn.1004-373x.2025.10.005
基于带差分扰动的改进PSO的PMSM参数辨识
PMSM parameter identification based on improved PSO with differential perturbation
摘要
Abstract
In order to address the issues of slow speed and low accuracy in the parameter identification of permanent magnet synchronous motors(PMSM),a method of particle swarm parameter identification based on the combination of random sample mean learning strategy of adaptive inertial weight and differential perturbation is proposed.In this algorithm,all particles in ascending order are sorted based on their fitness,and the particles with fitness ranking before the current particle form a sample pool.The average behavior of k particles in the current particle sample pool can be randomly selected for learning,and an adaptive inertia weight based on logistic function is used to improve the convergence performance of the algorithm.A differential perturbation method is adopted and embedded into the improved algorithm to enhance the global search ability of the algorithm in the early search stage.The simulation results show that the parameter identification curve can converge when the number of iterations is around 50,and the identification error of four parameters including stator resistance Rs,inductance Lq and Ld,and permanent magnet flux linkage ψf is only 1.58%at the highest and 0.005 2%at the lowest.The proposed strategy can accurately identify motor parameters and has the characteristics of fast convergence speed and high accuracy.关键词
永磁同步电机/参数辨识/差分扰动/自适应惯性权重/改进PSO/样本均值学习策略/混合策略Key words
permanent magnet synchronous motor/parameter identification/differential perturbation/adaptive inertia weight/improved PSO/sample mean learning strategy/hybrid strategy分类
电子信息工程引用本文复制引用
李安芳,吴钦木..基于带差分扰动的改进PSO的PMSM参数辨识[J].现代电子技术,2025,48(10):25-30,6.基金项目
国家自然科学基金项目(52267003) （52267003）
