A new on-line detection method of magnet flux linkage for permanent magnet synchronous motor

Author(s):  
Chuanbo Wen
Author(s):  
Fan Xiao ◽  
Jing He ◽  
Miaoying Zhang ◽  
◽  

To address the problem of demagnetization fault diagnosis of permanent magnet synchronous motor (PMSM) under inductance change, a demagnetization fault detection method based on an adaptive observer is proposed. First, the mathematical model of the demagnetization fault of PMSM in a synchronous rotating coordinate system is established, and the inductance disturbance is analyzed separately. Then, considering the different characteristics of the flux linkage fault and inductance disturbance, a new adaptive observer is proposed. Two adaptive laws are designed to ensure the accuracy of fault diagnosis and to eliminate the influence of inductance disturbance, thus achieving the robust diagnosis of demagnetization fault.


2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Hongchang Ding ◽  
Xiaobin Gong ◽  
Yuchun Gong

For high-speed permanent magnet synchronous motor (PMSM), its efficiency is significantly affected by the performance of permanent magnets (PMs), and the phenomenon of demagnetization will occur with the increase of PM temperature. So, the temperature detection of PMs in rotor is very necessary for the safe operation of PMSM, and direct detection is difficult due to the rotation of rotor. Based on the relationship between permanent magnet flux linkage and its temperature, in this paper, a new temperature estimation method using model reference fuzzy adaptive control (MRFAC) is proposed to estimate PM temperature. In this method, the model reference adaptive system (MRAS) is built to estimate the permanent magnet flux linkage, and the fuzzy control method is introduced into MRAS, which is used to improve the accuracy and applicable speed range of parameters estimated by MRAS. Different permanent magnet flux linkages are estimated in MRFAC based on the variation of stator resistance, which corresponds to different working temperatures measured by thermal resistance, and the PM temperature will be obtained according to the estimated permanent magnet flux linkage. At last, the back electromotive force (BEMF) is measured on the experimental motor, and the flux linkage and PM temperature of the experimental motor are deduced according to the BEMF. Compared with the experimental results, the estimated PM temperature is very close to the actual test value, and the error is less than 5%, which verifies that the proposed method is suitable for the estimation of PM temperature.


2012 ◽  
Vol 588-589 ◽  
pp. 479-483
Author(s):  
Song Wang ◽  
Guang Da Li

A new method named Windowed Least Square (WLS) to test main parameters of Permanent Magnet Synchronous Motor (PMSM) is proposed in this paper. Compared with Extended Kalman Filter (EKF) & Elman neural network and Recursive Least Square (RLS), WLS guarantees identification accuracy and excellent timeliness, and the issue of data saturation of RLS can be avoided. The PMSM model is built combining on-line parameter identification with Active Disturbance Rejection Control (ADRC) to improve the control performance of PMSM. The simulation results demonstrate that the performance of ADRC system using online estimation strategy is better than that of the system using PID method.


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