Position Sensorless Drive and Online Parameter Estimation for Surface-Mounted PMSMs Based on Adaptive Full-State Feedback Control

Journal Article (2020)
Author(s)

Yu Yao (Southeast University)

Yunkai Huang (Southeast University)

Fei Peng (Southeast University)

J. Dong (TU Delft - DC systems, Energy conversion & Storage)

Research Group
DC systems, Energy conversion & Storage
Copyright
© 2020 Yu Yao, Yunkai Huang, Fei Peng, J. Dong
DOI related publication
https://doi.org/10.1109/TPEL.2019.2957058
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 Yu Yao, Yunkai Huang, Fei Peng, J. Dong
Research Group
DC systems, Energy conversion & Storage
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
7
Volume number
35
Pages (from-to)
7341-7355
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Abstract

In this article, a position sensorless drive and online parameter estimation method for surface-mounted permanent magnet synchronous machines-based on adaptive full-state feedback current control is proposed. The position sensorless drive is established by the detection of the back-electromotive force in the gamma delta synchronous reference frame, which is effective at the medium-speed and high-speed range. Besides, accurate estimation of the winding resistance, the stator inductance, and the flux linkage of the PM is achieved independently. Compared with the traditional recursive-least-square methods, the proposed parameter identification method can be easily implemented because of the significantly reduced execution time. With the help of the parameter identification, the precise position estimation can be achieved by the proposed sensorless control method regardless of the parameter variation during the operation. The stability of the proposed method is proved by the Lyapunov-function method. Finally, the effectiveness of the proposed method is validated by the simulation and experimental results.

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