Rotor Position Estimation Algorithm for Surface-Mounted Permanent Magnet Synchronous Motor Based on Improved Super-Twisting Sliding Mode Observer

In response to the chattering issue inherent in sliding mode observers during rotor position estimation and to enhance the stability and robustness of sensorless control systems for surface-mounted permanent magnet synchronous motors (SPMSM), this study proposes a rotor position estimation algorithm for SPMSM based on an improved super-twisting sliding mode observer (ISTSMO) and a second-order generalized integrator (SOGI) structure. Firstly, the super-twisting algorithm is introduced to design the observer, which effectively attenuates the sliding mode chattering by using continuous control signals. Secondly, SOGI is introduced in the filtering stage, which not only effectively addresses the time delay issues caused by traditional low-pass filters but also enables the observer to extract rotor position information by monitoring only the back electromotive force (back-EMF) signal of the alpha-phase, thereby simplifying the observer structure. Finally, the proposed scheme is experimentally compared with the traditional sliding mode observer on the YXMBD-TE1000 platform. The experimental results showed that during motor acceleration and deceleration tests, the average speed estimation error was reduced from 141 r/min to 40 r/min, and the maximum position estimation error was reduced from 0.74 rad to 0.29 rad. In load disturbance experiments, the speed variation decreased from 781 r/min to 451 r/min, and the steady-state speed fluctuation was significantly reduced. These results confirm that the proposed observer exhibits superior stability and robustness.