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Identification of switched reluctance machine using fuzzy model

Author

Listed:
  • Abdelmalek Ouannou

    (Moulay Ismail University of Meknès)

  • Adil Brouri

    (Moulay Ismail University of Meknès)

  • Laila Kadi

    (Moulay Ismail University of Meknès)

  • Hafid Oubouaddi

    (Moulay Ismail University of Meknès)

Abstract

The main component in renewable energy and electrical vehicles is the electric motor. The choice of a low-cost motor, easy to maintain and with high efficiency is an important issue. Because of its many advantages, the switched reluctance machine (SRM) can be a suitable solution. However, the SRM is characterized by a so extremely nonlinear behavior, making the control of these devices very crucial issue. Then, The SRM is often run in the magnetically saturated mode. Furthermore, the most of available works have been based on several approximations. Presently, an analytical model and identification method for SRM are established. Then, the magnetization characteristics of SRM can be easily obtained using the proposed model. Unlike previous research, the inherent magnetic nonlinearity and the hysteretic effect of SRM are taken into consideration. Furthermore, a standstill test identification method based on fuzzy techniques is proposed. Then, it is verified that the SRM can be modeled by a fuzzy Wiener model. Specifically, it can be described by the series connection of a linear block and a static Takagi–Sugeno fuzzy model. Finally, the magnetization characteristics of SRM and the SRM model parameters can be achieved. The obtained results show the effectiveness of the proposed solution based on fuzzy logic techniques.

Suggested Citation

  • Abdelmalek Ouannou & Adil Brouri & Laila Kadi & Hafid Oubouaddi, 2022. "Identification of switched reluctance machine using fuzzy model," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 2833-2846, December.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:6:d:10.1007_s13198-022-01749-4
    DOI: 10.1007/s13198-022-01749-4
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