Full-speed domain position sensorless control strategy for PMSM based on improved super-twisting sliding-mode observer and smooth transition optimization

In the sensorless control of permanent magnet synchronous motors (PMSMs), achieving smooth transitions from low to medium-high speeds remains a significant challenge. Aiming at the problem that PMSMs cannot be smoothly transitioned to medium-high speed range, this paper proposes a full-speed range control algorithm based on the fusion of pulsating high-frequency injection (HFI) with square waves and an improved super-twisting sliding-mode observer (STSMO). The proposed method enables smooth and stable operation over the full speed range, with notable improvements observed during transitional phases. In the low-speed range, high-frequency current signal is obtained by injecting a high-frequency (HF) square-wave signal, and the signal is processed to obtain rotor position and speed information. For medium-high speeds, a variable-gain linear STSMO (VGLSTSMO) combined with an adaptive back electromotive force (back-EMF) model is employed to improve robustness. Furthermore, this paper designs a Sine-weighted switching function to facilitate a smooth transition of motors from low to medium-high speeds domains. The effectiveness and superiority of the proposed methods are validated through simulations. The rotor position estimation errors of the improved STSMO method are approximately 0.2 rad, and Sine-weighted switching method enables motors to switch smoothly from the low-speed range to the medium- high-speed ranges.

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Publication Details

Journal
Scientific Reports
Published
2026-01-19
DOI
https://doi.org/10.1038/s41598-026-35994-5
Primary Topic
Sensorless Control of Electric Motors
Type
article
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article

Full-speed domain position sensorless control strategy for PMSM based on improved super-twisting sliding-mode observer and smooth transition optimization

Xia Zhang, Pengwei Li, Minghao Lv, Liangtong Shi et al.
Scientific Reports
Sensorless Control of Electric Motors
article

Full-speed domain position sensorless control strategy for PMSM based on improved super-twisting sliding-mode observer and smooth transition optimization

Xia Zhang, Pengwei Li, Minghao Lv, Liangtong Shi, Bo Wang
article en

Abstract

In the sensorless control of permanent magnet synchronous motors (PMSMs), achieving smooth transitions from low to medium-high speeds remains a significant challenge. Aiming at the problem that PMSMs cannot be smoothly transitioned to medium-high speed range, this paper proposes a full-speed range control algorithm based on the fusion of pulsating high-frequency injection (HFI) with square waves and an improved super-twisting sliding-mode observer (STSMO). The proposed method enables smooth and stable operation over the full speed range, with notable improvements observed during transitional phases. In the low-speed range, high-frequency current signal is obtained by injecting a high-frequency (HF) square-wave signal, and the signal is processed to obtain rotor position and speed information. For medium-high speeds, a variable-gain linear STSMO (VGLSTSMO) combined with an adaptive back electromotive force (back-EMF) model is employed to improve robustness. Furthermore, this paper designs a Sine-weighted switching function to facilitate a smooth transition of motors from low to medium-high speeds domains. The effectiveness and superiority of the proposed methods are validated through simulations. The rotor position estimation errors of the improved STSMO method are approximately 0.2 rad, and Sine-weighted switching method enables motors to switch smoothly from the low-speed range to the medium- high-speed ranges.

Scientific ReportsVol. 16(1)
Beihua University (CN)
Affordable and clean energy
Openalex Percentile: Top 84%
Sensorless Control of Electric Motors
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Full-speed domain position sensorless control strategy for PMSM based on improved super-twisting sliding-mode observer and smooth transition optimization — Xia Zhang, Pengwei Li, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS