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Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview

Author

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  • Pedro Gonçalves

    (Department of Electrical and Computer Engineering, University of Coimbra, and Instituto de Telecomunicações, Pólo 2-Pinhal de Marrocos, P-3030-290 Coimbra, Portugal)

  • Sérgio Cruz

    (Department of Electrical and Computer Engineering, University of Coimbra, and Instituto de Telecomunicações, Pólo 2-Pinhal de Marrocos, P-3030-290 Coimbra, Portugal)

  • André Mendes

    (Department of Electrical and Computer Engineering, University of Coimbra, and Instituto de Telecomunicações, Pólo 2-Pinhal de Marrocos, P-3030-290 Coimbra, Portugal)

Abstract

Recently, the control of multiphase electric drives has been a hot research topic due to the advantages of multiphase machines, namely the reduced phase ratings, improved fault tolerance and lesser torque harmonics. Finite control set model predictive control (FCS-MPC) is one of the most promising high performance control strategies due to its good dynamic behaviour and flexibility in the definition of control objectives. Although several FCS-MPC strategies have already been proposed for multiphase drives, a comparative study that assembles all these strategies in a single reference is still missing. Hence, this paper aims to provide an overview and a critical comparison of all available FCS-MPC techniques for electric drives based on six-phase machines, focusing mainly on predictive current control (PCC) and predictive torque control (PTC) strategies. The performance of an asymmetrical six-phase permanent magnet synchronous machine is compared side-by-side for a total of thirteen PCC and five PTC strategies, with the aid of simulation and experimental results. Finally, in order to determine the best and the worst performing control strategies, each strategy is evaluated according to distinct features, such as ease of implementation, minimization of current harmonics, tuning requirements, computational burden, among others.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4693-:d:296065
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    References listed on IDEAS

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    1. Fengxiang Wang & Zhenbin Zhang & Xuezhu Mei & José Rodríguez & Ralph Kennel, 2018. "Advanced Control Strategies of Induction Machine: Field Oriented Control, Direct Torque Control and Model Predictive Control," Energies, MDPI, vol. 11(1), pages 1-13, January.
    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.
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    1. Karol Wróbel & Piotr Serkies & Krzysztof Szabat, 2020. "Model Predictive Base Direct Speed Control of Induction Motor Drive—Continuous and Finite Set Approaches," Energies, MDPI, vol. 13(5), pages 1-15, March.
    2. Jing Tang & Yongheng Yang & Jie Chen & Ruichang Qiu & Zhigang Liu, 2019. "Characteristics Analysis and Measurement of Inverter-Fed Induction Motors for Stator and Rotor Fault Detection," Energies, MDPI, vol. 13(1), pages 1-17, December.
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    4. Marwa Ben Slimene & Mohamed Arbi Khlifi, 2022. "Investigation on the Effects of Magnetic Saturation in Six-Phase Induction Machines with and without Cross Saturation of the Main Flux Path," Energies, MDPI, vol. 15(24), pages 1-18, December.
    5. Jaime A. Rohten & David N. Dewar & Pericle Zanchetta & Andrea Formentini & Javier A. Muñoz & Carlos R. Baier & José J. Silva, 2021. "Multivariable Deadbeat Control of Power Electronics Converters with Fast Dynamic Response and Fixed Switching Frequency," Energies, MDPI, vol. 14(2), pages 1-16, January.
    6. Sergio Toledo & Edgar Maqueda & Marco Rivera & Raúl Gregor & Pat Wheeler & Carlos Romero, 2020. "Improved Predictive Control in Multi-Modular Matrix Converter for Six-Phase Generation Systems," Energies, MDPI, vol. 13(10), pages 1-13, May.
    7. 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.
    8. Angel Gonzalez-Prieto & Ignacio Gonzalez-Prieto & Mario J. Duran & Juan Carrillo-Rios & Juan J. Aciego & Pedro Salas-Biedma, 2021. "Proportional Usage of Low-Level Actions in Model Predictive Control for Six-Phase Electric Drives," Energies, MDPI, vol. 14(14), pages 1-15, July.
    9. Hongtai Ma & Li Li & Yingpeng Fan & Youguang Guo & Zhihui Jin & Jian Luo, 2022. "A Discrete Current Controller for High Power-Density Synchronous Machines," Energies, MDPI, vol. 15(17), pages 1-23, September.
    10. Claudio Rossi & Yasser Gritli & Alessio Pilati & Gabriele Rizzoli & Angelo Tani & Domenico Casadei, 2020. "High Resistance Fault-Detection and Fault-Tolerance for Asymmetrical Six-Phase Surface-Mounted AC Permanent Magnet Synchronous Motor Drives," Energies, MDPI, vol. 13(12), pages 1-18, June.

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