An improved method of interior permanent magnet synchronous motor parameter identification based on particle swarm optimization

On account of the reverse salient pole characteristic and defects of the traditional parameter identification method, this article put forward a parameter identification method based on particle swarm optimization (PSO) combine with the mathematical model of the motor. And even made an improvement of PSO. The improvement of PSO can identify the four parameters in same time such as the stator resistance, the d-axis inductance, the q-axis inductance and the permanent magnet flux. The signal used in the method are all can be directly detected the state variables so it can reduce the influence of the other disturbance on the motor parameters identification and improve the accuracy of the parameter identification. Simulation and experimental results shows that the PSO to identify the parameters has a strong robustness and convergence. Four pending identification parameters can converge to the true value in a relatively short time and has a high accuracy no matter in the different speed, load and control strategy. It also overcomes the drawback of high requirements in the initial parameter values which in the basic PSO to identify and the improvement of PSO is better.