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Algorithm for Implementation of Optimal Vector Combinations in Model Predictive Current Control of Six-Phase Induction Machines

Author

Listed:
  • Carlos Romero

    (Laboratory of Power and Control Systems (LSPyC), Facultad de Ingeniería, Universidad Nacional de Asunción, Luque 2060, Paraguay)

  • Larizza Delorme

    (Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 2111, Paraguay)

  • Osvaldo Gonzalez

    (Laboratory of Power and Control Systems (LSPyC), Facultad de Ingeniería, Universidad Nacional de Asunción, Luque 2060, Paraguay)

  • Magno Ayala

    (Laboratory of Power and Control Systems (LSPyC), Facultad de Ingeniería, Universidad Nacional de Asunción, Luque 2060, Paraguay)

  • Jorge Rodas

    (Laboratory of Power and Control Systems (LSPyC), Facultad de Ingeniería, Universidad Nacional de Asunción, Luque 2060, Paraguay)

  • Raul Gregor

    (Laboratory of Power and Control Systems (LSPyC), Facultad de Ingeniería, Universidad Nacional de Asunción, Luque 2060, Paraguay)

Abstract

The development of new control techniques for multiphase induction machines (IMs) has become a point of great interest to exploit the advantages of these machines compared to three-phase topology, for example, the reduced phase currents and lower harmonic contents. One of the most analyzed techniques is the model-based predictive current control (MPC) with a finite control set. This technique presents high x – y currents because of the application of one switching state throughout the whole sampling period. Nevertheless, it is one of the most used due to its excellent dynamic response. To overcome the aforementioned drawbacks, new techniques called virtual vectors have been developed, but although there are several articles with experimental results, the algorithm for implementing the technique has not been appropriately described. This document provides a clear and detailed explanation for algorithm implementation of virtual vectors through two proposed variants VV4 and VV11, in a six-phase machine drive. The first entails lower computational cost and the second lower loss in the x – y plane. According to performance indicators such as the total harmonic distortion and the mean square error for both case studies, experimental tests were evaluated to determine the implementation’s behaviour.

Suggested Citation

  • Carlos Romero & Larizza Delorme & Osvaldo Gonzalez & Magno Ayala & Jorge Rodas & Raul Gregor, 2021. "Algorithm for Implementation of Optimal Vector Combinations in Model Predictive Current Control of Six-Phase Induction Machines," Energies, MDPI, vol. 14(13), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:13:p:3857-:d:583094
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    References listed on IDEAS

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    1. Pedro Gonçalves & Sérgio Cruz & André Mendes, 2019. "Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview," Energies, MDPI, vol. 12(24), pages 1-42, December.
    2. Osvaldo Gonzalez & Magno Ayala & Jesus Doval-Gandoy & Jorge Rodas & Raul Gregor & Marco Rivera, 2019. "Predictive-Fixed Switching Current Control Strategy Applied to Six-Phase Induction Machine," Energies, MDPI, vol. 12(12), pages 1-14, June.
    3. Yassine Kali & Magno Ayala & Jorge Rodas & Maarouf Saad & Jesus Doval-Gandoy & Raul Gregor & Khalid Benjelloun, 2019. "Current Control of a Six-Phase Induction Machine Drive Based on Discrete-Time Sliding Mode with Time Delay Estimation," Energies, MDPI, vol. 12(1), pages 1-17, January.
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