关键词: 永磁同步电机, 参数辨识, 粒子群算法, 小生境技术, 小生境粒子群算法

Abstract: The electromagnetic parameters of permanent magnet synchronous motor change with the change of temperature and magnetic circuit, and the accuracy of its identification has an important influence on the performance of its control system. The traditional identification algorithm has the defects of slow convergence speed and low identification accuracy. To solve this problem, a parameter identification method based on particle swarm optimization algorithm was adopted. This method was simple to measure the input parameters, and could identify the three parameters of resistance, inductance and flux accurately at the same time. Meanwhile, the niche technology and particle swarm optimization improvement strategy were introduced to overcome the defect that the basic particle swarm optimization algorithm is easy to fall into local optimum, and obtain better identification accuracy and convergence speed. The simulation results show that the method is feasible and correct.

Key words: permanent magnet synchronous motor (PMSM), parameter identification, particle swarm optimization (PSO), niche technology,niche particle swarm optimization (NPSO)