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Estimation of Rotor Temperature of Permanent Magnet Synchronous Motor Based on Model Reference Fuzzy Adaptive Control

Author

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  • Hongchang Ding
  • Xiaobin Gong
  • Yuchun Gong

Abstract

For high-speed permanent magnet synchronous motor (PMSM), its efficiency is significantly affected by the performance of permanent magnets (PMs), and the phenomenon of demagnetization will occur with the increase of PM temperature. So, the temperature detection of PMs in rotor is very necessary for the safe operation of PMSM, and direct detection is difficult due to the rotation of rotor. Based on the relationship between permanent magnet flux linkage and its temperature, in this paper, a new temperature estimation method using model reference fuzzy adaptive control (MRFAC) is proposed to estimate PM temperature. In this method, the model reference adaptive system (MRAS) is built to estimate the permanent magnet flux linkage, and the fuzzy control method is introduced into MRAS, which is used to improve the accuracy and applicable speed range of parameters estimated by MRAS. Different permanent magnet flux linkages are estimated in MRFAC based on the variation of stator resistance, which corresponds to different working temperatures measured by thermal resistance, and the PM temperature will be obtained according to the estimated permanent magnet flux linkage. At last, the back electromotive force (BEMF) is measured on the experimental motor, and the flux linkage and PM temperature of the experimental motor are deduced according to the BEMF. Compared with the experimental results, the estimated PM temperature is very close to the actual test value, and the error is less than 5%, which verifies that the proposed method is suitable for the estimation of PM temperature.

Suggested Citation

  • Hongchang Ding & Xiaobin Gong & Yuchun Gong, 2020. "Estimation of Rotor Temperature of Permanent Magnet Synchronous Motor Based on Model Reference Fuzzy Adaptive Control," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-11, April.
  • Handle: RePEc:hin:jnlmpe:4183706
    DOI: 10.1155/2020/4183706
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    Cited by:

    1. Mohamed El-Borhamy & Essam Eddin M. Rashad & Ismail Sobhy & M. Kamel El-Sayed, 2021. "Modeling and Semi-Analytic Stability Analysis for Dynamics of AC Machines," Mathematics, MDPI, vol. 9(6), pages 1-13, March.

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