Sensorless estimation and simulation of PMSM based on high-frequency signal injection

Wu, Maogang; Xuan, Xiaogang; Chen, Xing

doi:10.1109/wcica.2012.6359042

Cited by 8 publications

(1 citation statement)

References 4 publications

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“…Currently, the main position-sensorless control algorithms of PMSMs are the highfrequency signal injection method [17,18], the extended Kalman filter method [19,20], the sliding-mode observer (SMO) method [21,22], the model reference adaptive method [23,24], etc. Among them, the high-frequency signal injection method is not sensitive to changes in motor parameters and can accurately estimate the position at zero or low velocity.…”

Section: Introductionmentioning

confidence: 99%

Study on a Second-Order Adaptive Sliding-Mode Observer Control Algorithm for the Sensorless Permanent Magnet Synchronous Motor

et al. 2023

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The control of a permanent magnet synchronous motor (PMSM) without a position sensor based on a sliding-mode observer (SMO) algorithm has a serious jitter problem in the process of motor phase tracking. A second-order adaptive sliding-mode observer algorithm was proposed, and the ideas and principles of the second-order sliding-mode observer algorithm based on the super-twisting algorithm were elaborated. In particular, adaptive estimation with the introduction of back-electromotive force (EMF) was investigated, and the Lyapunov stability criterion was used to determine the convergence properties of the algorithm. The results showed that the second-order adaptive sliding-mode observer algorithm had better jitter suppression and a better phase tracking performance than the traditional sliding-mode observer algorithm. The experimental results showed that when the motor velocity was 800 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.57 r/min and the position error was 0.018 rad, with accuracy improvements of 93.63% and 58.34%, respectively. When the motor velocity was 1000 r/min, the velocity error of the second-order adaptive sliding-mode observer algorithm was 0.94 r/min and the position error was 0.022 rad, with accuracy improvements of 90.55% and 55.10%, respectively. The jitter of the system was suppressed well, the curve of back-EMF was smoother, and the robustness of the system was high. Therefore, the second-order adaptive sliding-mode observer algorithm is more suitable for the position-sensorless control of a PMSM.

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