Adaptive Step-Size Predictive PLL Based Rotor Position Estimation Method for Sensorless IPMSM Drives

The fixed-gain position observer for sensorless interior permanent magnet synchronous motor (IPMSM) drives requires repeated trials for parameter tuning and has poor dynamic response capability. A novel adaptive step-size predictive phase-locked loop (ASS-PPLL) based rotor position estimation method...

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Bibliographic Details
Published inIEEE transactions on power electronics Vol. 39; no. 5; pp. 6136 - 6147
Main Authors Zhang, Guoqiang, Yan, Yunhao, Wang, Qiwei, Ding, Dawei, Wang, Gaolin, Ding, Li, Li, Yunwei, Xu, Dianguo
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive step-size iterative search
Cost function
Dynamic response
Estimation
high-frequency square-wave injection
interior permanent magnet synchronous motor (IPMSM)
Iterative methods
Observers
Parameters
Permanent magnets
Phase locked loops
Position sensing
predictive phase-locked loop (PPLL)
Rotors
Sensorless control
Synchronous motors
Tracking errors
Tuning
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Summary:The fixed-gain position observer for sensorless interior permanent magnet synchronous motor (IPMSM) drives requires repeated trials for parameter tuning and has poor dynamic response capability. A novel adaptive step-size predictive phase-locked loop (ASS-PPLL) based rotor position estimation method is proposed to improve dynamic performance in this article. A cost function using position-tracking error decoupled from a high-frequency current response through a high-frequency square-wave injection is established. In addition, the step-size and direction are automatically adjusted by the predefined cost function to speed up the iterative search for an optimal rotor position estimate in a finite position set. Compared with the fixed-gain observers, the proposed ASS-PPLL effectively improves dynamic performance without a complex and time-consuming parameter tuning process. Compared with the conventional predictive PLL, the proposed method reduces the computational burden with fewer iterations, while ensuring the position estimation accuracy. Finally, the effectiveness of the proposed ASS-PPLL is comprehensively verified on a 2.2-kW IPMSM drive platform.
ISSN:0885-8993
1941-0107
DOI:10.1109/TPEL.2024.3365735