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Static and dynamic analysis of non-linear magnetic characteristics in switched reluctance motors based on circuit-coupled time stepping finite element method

Author

Listed:
  • C. Labiod

    (University of Biskra)

  • M. Bahri

    (University of Biskra)

  • K. Srairi

    (University of Biskra)

  • B. Mahdad

    (University of Biskra)

  • M. T. Benchouia

    (University of Biskra)

  • M. E. H. Benbouzid

    (University of Brest)

Abstract

This paper presents a static and dynamic analysis of non-linear magnetic characteristics in switched reluctance motor (SRM) based on finite element method (FEM). Static performances of the SRM are determined by using two-dimensional FEM under different rotor positions due to variations of the excitation current. Dynamic performances are obtained by the use of circuit-coupled time stepping finite element method. The proposed modeling strategy allows predicting the four-phase 8/6 SRM performances behaviors in both static and dynamic cases. Static torque values and current waveform give dynamic torque profile by using look up table in Simulink software. The advantage of the proposed approach is that it allows minimizing the torque ripples when changing the phase turn-on (θ on ) and the phase turn-off (θ off ) angles.

Suggested Citation

  • C. Labiod & M. Bahri & K. Srairi & B. Mahdad & M. T. Benchouia & M. E. H. Benbouzid, 2017. "Static and dynamic analysis of non-linear magnetic characteristics in switched reluctance motors based on circuit-coupled time stepping finite element method," 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. 8(1), pages 47-55, January.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:1:d:10.1007_s13198-014-0294-6
    DOI: 10.1007/s13198-014-0294-6
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    Cited by:

    1. 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.
    2. Abdellatif Seghiour & Tahar Seghier & Boubakeur Zegnini & George Georgoulas, 2017. "Diagnosis of the combined rotor faults using air gap magnetic flux density spectrum for an induction machine," 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. 8(2), pages 1503-1519, November.

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