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Different Control Techniques of Permanent Magnet Synchronous Motor with Fuzzy Logic for Electric Vehicles: Analysis, Modelling, and Comparison

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  • Khoudir Kakouche

    (Laboratoire de Technologie Industrielle et de l’Information, Faculté de Technologie, Université de Bejaia, Bejaia 06000, Algeria)

  • Adel Oubelaid

    (Laboratoire de Technologie Industrielle et de l’Information, Faculté de Technologie, Université de Bejaia, Bejaia 06000, Algeria)

  • Smail Mezani

    (Université de Lorraine, GREEN, F-54000 Nancy, France)

  • Djamila Rekioua

    (Laboratoire de Technologie Industrielle et de l’Information, Faculté de Technologie, Université de Bejaia, Bejaia 06000, Algeria)

  • Toufik Rekioua

    (Laboratoire de Technologie Industrielle et de l’Information, Faculté de Technologie, Université de Bejaia, Bejaia 06000, Algeria)

Abstract

This paper presents a detailed analysis and comparative study of three torque control methodologies with fuzzy logic, namely direct torque control (DTC), fuzzy direct torque control (FDTC), and model predictive direct torque control (MPDTC), for PMSM control applied to an electric vehicle. The three control strategies are designed and developed to control torque in order to achieve vehicle requirements, such as minimum torque and flux ripples, fast dynamic response, and maximum efficiency. To enhance the performance and efficiency of the overall drive, a bidirectional DC/DC buck-boost converter is connected to the Li-ion battery. In addition, a fuzzy logic controller (FLC) is used in the outer loop to control the speed of the PMSM. As a result, the tuning difficulty of the conventional proportional-integral (PI) controller is avoided and the dynamic speed response is improved. Simulation results obtained from the three control techniques establish that the proposed system via the MPDTC technique reduces the torque ripples, flux ripples, reduces the THD of the PMSM current, and achieves a faster transient response. Additionally, the MPTDC technique enabled the electric vehicle to cover the longest distance, with approximately 110.72 km in a charging cycle. The real-time simulation is developed using the RT LAB simulator, and the obtained results confirm the superiority of the MPDTC technique over conventional DTC and FDTC techniques.

Suggested Citation

  • Khoudir Kakouche & Adel Oubelaid & Smail Mezani & Djamila Rekioua & Toufik Rekioua, 2023. "Different Control Techniques of Permanent Magnet Synchronous Motor with Fuzzy Logic for Electric Vehicles: Analysis, Modelling, and Comparison," Energies, MDPI, vol. 16(7), pages 1-28, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:3116-:d:1110940
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    References listed on IDEAS

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    1. Younes Sahri & Salah Tamalouzt & Sofia Lalouni Belaid & Seddik Bacha & Nasim Ullah & Ahmad Aziz Al Ahamdi & Ali Nasser Alzaed, 2021. "Advanced Fuzzy 12 DTC Control of Doubly Fed Induction Generator for Optimal Power Extraction in Wind Turbine System under Random Wind Conditions," Sustainability, MDPI, vol. 13(21), pages 1-23, October.
    2. Adel Oubelaid & Hisham Alharbi & Abdullah S. Bin Humayd & Nabil Taib & Toufik Rekioua & Sherif S. M. Ghoneim, 2022. "Fuzzy-Energy-Management-Based Intelligent Direct Torque Control for a Battery—Supercapacitor Electric Vehicle," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    3. Jemma J. Makrygiorgou & Antonio T. Alexandridis, 2019. "Power Electronic Control Design for Stable EV Motor and Battery Operation during a Route," Energies, MDPI, vol. 12(10), pages 1-21, May.
    4. Ibrahim Farouk Bouguenna & Ahmed Tahour & Ralph Kennel & Mohamed Abdelrahem, 2021. "Multiple-Vector Model Predictive Control with Fuzzy Logic for PMSM Electric Drive Systems," Energies, MDPI, vol. 14(6), pages 1-23, March.
    5. Ali Djerioui & Azeddine Houari & Mohamed Machmoum & Malek Ghanes, 2020. "Grey Wolf Optimizer-Based Predictive Torque Control for Electric Buses Applications," Energies, MDPI, vol. 13(19), pages 1-18, September.
    6. Mahmoudzadeh Andwari, Amin & Pesiridis, Apostolos & Rajoo, Srithar & Martinez-Botas, Ricardo & Esfahanian, Vahid, 2017. "A review of Battery Electric Vehicle technology and readiness levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 414-430.
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    1. Zhiwen Zhang & Jie Tang & Jiyuan Zhang & Tianci Zhang, 2024. "Research on Energy Hierarchical Management and Optimal Control of Compound Power Electric Vehicle," Energies, MDPI, vol. 17(6), pages 1-22, March.

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