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Interest and Applicability of Meta-Heuristic Algorithms in the Electrical Parameter Identification of Multiphase Machines

Author

Listed:
  • Daniel Gutierrez-Reina

    (Department of Engineering, Loyola University Andalusia, 41014 Seville, Spain)

  • Federico Barrero

    (Electronic Engineering Department, University of Seville, 41092 Sevilla, Spain)

  • Jose Riveros

    (Faculty of Engineering, University of Talca, Curicó 3340000, Chile)

  • Ignacio Gonzalez-Prieto

    (Thermal and Electrical Engineering Department, University of Huelva, 21007 Huelva, Spain)

  • Sergio L. Toral

    (Electronic Engineering Department, University of Seville, 41092 Sevilla, Spain)

  • Mario J. Duran

    (Department of Electrical Engineering, University of Malaga, 29071 Malaga, Spain)

Abstract

Multiphase machines are complex multi-variable electro-mechanical systems that are receiving special attention from industry due to their better fault tolerance and power-per-phase splitting characteristics compared with conventional three-phase machines. Their utility and interest are restricted to the definition of high-performance controllers, which strongly depends on the knowledge of the electrical parameters used in the multiphase machine model. This work presents the proof-of-concept of a new method based on particle swarm optimization and standstill time-domain tests. This proposed method is tested to estimate the electrical parameters of a five-phase induction machine. A reduction of the estimation error higher than 2.5% is obtained compared with gradient-based approaches.

Suggested Citation

  • Daniel Gutierrez-Reina & Federico Barrero & Jose Riveros & Ignacio Gonzalez-Prieto & Sergio L. Toral & Mario J. Duran, 2019. "Interest and Applicability of Meta-Heuristic Algorithms in the Electrical Parameter Identification of Multiphase Machines," Energies, MDPI, vol. 12(2), pages 1-15, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:2:p:314-:d:199258
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    References listed on IDEAS

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    1. Pingping Yun & Yongfeng Ren & Yu Xue, 2018. "Energy-Storage Optimization Strategy for Reducing Wind Power Fluctuation via Markov Prediction and PSO Method," Energies, MDPI, vol. 11(12), pages 1-23, December.
    2. Abdelbasset Krama & Laid Zellouma & Boualaga Rabhi & Shady S. Refaat & Mansour Bouzidi, 2018. "Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm," Energies, MDPI, vol. 11(12), pages 1-26, December.
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    Cited by:

    1. Jose A. Riveros & Joel Prieto & Marco Rivera & Sergio Toledo & Raúl Gregor, 2019. "A Generalised Multifrequency PWM Strategy for Dual Three-Phase Voltage Source Converters," Energies, MDPI, vol. 12(7), pages 1-13, April.

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