A Novel Inductance Identification Method of Synchronous Reluctance Motor

In the process of operation, the parameters of Synchronous Reluctance Motor (SynRM) will be changed by such factors as temperature and magnetic saturation, so as to reduce the control performance. Therefore, obtaining accurate motor parameters in high-performance control is of great significance. To solve the problem of the inductance of alternating and straight axis varies greatly during the operation of SynRM, an improved model reference adaptive online inductance identification method of SynRM is proposed in this paper. Firstly, the basic principle of inductance parameters online identification in model reference adaptive system (MRAS) is studied, and the variable forgetting factor robust recursive least square (VFFRRLS) method is introduced into MRAS algorithm. Based on the inductance parameters identification values at the current time, the second identification is carried out and the adjustable model is updated in real time to improve the speed of MRAS inductance parameters online identification and the anti-disturbance performance of the identification process. Finally, the proposed method is applied for the experimental verification, and the performance is compared with that of the traditional method in inductance parameters online identification under the different operating conditions, which validates the correctness and effectiveness of the proposed method.