An Impedance Model-Based Multiparameter Identification Method of PMSM for Both Offline and Online Conditions
Qiwei Wang, Gaolin Wang, Nannan Zhao, Guoqiang Zhang, Qingwen Cui, Dianguo Xu
Abstract
Existing online motor parameter identification methods mostly depend on the fundamental frequency voltage equations, which lead to the unsatisfactory identification effect at low current and low speed operation. This article proposes a parameter identification method based on the high frequency (HF) equivalent impedance model of permanent magnet synchronous motor with HF signal injection at both the dq-axes. This method identifies the resistance and the dq-axis inductances offline and online, along with the flux linkage online. In order to improve the identification accuracy, the parameter sensitivity analysis-based algorithm is proposed to detect the resistance and the flux linkage. Meanwhile, the inverter nonlinearities and the HF influence on parameter identification are compensated effectively. In order not to affect the normal operation of the motor drive, the selection of the amplitude, and the frequency of the injected signal is investigated. The proposed method is validated on a 2.2-kW motor and confirmed by finite element analysis. The experimental results show the good identification effect in different operation conditions.