关键词: 永磁同步电机, 参数辨识, 天牛须搜索算法, 粒子群算法

Abstract: Aiming at the problem of slow convergence and inaccurate recognition effect caused by the local extreme value of the beetle antennae search algorithm for recognising permanent magnet synchronous motors, a kind of improved beetle antennae search algorithm is proposed to recognise the parameters of permanent magnet synchronous motors. The method takes the beetle as the research object and uses traditional particle swarm optimization to optimize it, ensuring consistency in initial positioning and motion trajectory. In the iterative process,the position update rule of the beetle herd is no longer simply based on a single update strategy that relies on historical and global optima. Instead, the idea of " left
whisker-right whisker" is introduced on this basis, which increases the judgment of the surrounding environment in each iteration step and can adapt more flexibly to the constantly changing environment. The simulation experiments are conducted in Matlab / Simulink. The results show that the improved particle swarm algorithm for beetle antennae converges faster and have higher recognition accuracy. Among them, the identification error of stator resistance is 0. 647%; the identification errors of d、 q axis inductance are 0. 609% and 0. 011 999%, respectively; the identification error of permanent magnet magnetic flux identification is 0. 052%.

Key words: permanent magnet synchronous motor, identifying parameters, beetle antennae search algorithm, particle swarm algorithm