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Implementation of an Improved Motor Control for Electric Vehicles

Author

Listed:
  • Xiaojin Men

    (Department of Automation, University of Science and Technology of China, Hefei 230026, China)

  • Youguang Guo

    (School of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Gang Wu

    (Department of Automation, University of Science and Technology of China, Hefei 230026, China)

  • Shuangwu Chen

    (Department of Automation, University of Science and Technology of China, Hefei 230026, China)

  • Chun Shi

    (Department of Automation, University of Science and Technology of China, Hefei 230026, China)

Abstract

Electric vehicles are regarded as a significant way to mitigate the global energy crisis and the environmental pollution problem. Motor control is a very important part for electric vehicles. As for hardware, a motor controller usually has components such as a power module, microprocessor unit, IGBT driver, sensors, and resolver-to-digital convertor. As for software, a field-oriented control (FOC) with space vector pulse width modulation (SVPWM) is a popular method, while model predictive control (MPC) has recently shown great potential in motor drives. In this paper, both FOC and MPC are discussed and the performances are compared based on experiments. As the implementation is on a digital processor, the discretization and normalization are addressed, and the flux observer and speed estimation are discussed. Some practical issues for implementation are also talked about, such as field weakening control, overmodulation, etc. This paper focuses on how to implement the improved motor control for electric vehicles as industrial applications. The steady-state torque performances of this motor controller are verified by motor test-bench experiments. MPC shows as good performance as FOC in these experiments.

Suggested Citation

  • Xiaojin Men & Youguang Guo & Gang Wu & Shuangwu Chen & Chun Shi, 2022. "Implementation of an Improved Motor Control for Electric Vehicles," Energies, MDPI, vol. 15(13), pages 1-24, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4833-:d:853709
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    Citations

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    Cited by:

    1. Sofiane Bacha & Ramzi Saadi & Mohamed Yacine Ayad & Mohamed Sahraoui & Khaled Laadjal & Antonio J. Marques Cardoso, 2023. "Autonomous Electric-Vehicle Control Using Speed Planning Algorithm and Back-Stepping Approach," Energies, MDPI, vol. 16(5), pages 1-26, March.
    2. Vijina Abhijith & M. J. Hossain & Gang Lei & Premlal Ajikumar Sreelekha & Tibinmon Pulimoottil Monichan & Sree Venkateswara Rao, 2022. "Hybrid Switched Reluctance Motors for Electric Vehicle Applications with High Torque Capability without Permanent Magnet," Energies, MDPI, vol. 15(21), pages 1-16, October.
    3. Konstantina Bitsi & Sjoerd G. Bosga & Oskar Wallmark, 2022. "Design Aspects and Performance Evaluation of Pole-Phase Changing Induction Machines," Energies, MDPI, vol. 15(19), pages 1-18, September.
    4. Nikita V. Martyushev & Boris V. Malozyomov & Ilham H. Khalikov & Viktor Alekseevich Kukartsev & Vladislav Viktorovich Kukartsev & Vadim Sergeevich Tynchenko & Yadviga Aleksandrovna Tynchenko & Mengxu , 2023. "Review of Methods for Improving the Energy Efficiency of Electrified Ground Transport by Optimizing Battery Consumption," Energies, MDPI, vol. 16(2), pages 1-39, January.
    5. Youguang Guo & Xin Ba & Lin Liu & Haiyan Lu & Gang Lei & Wenliang Yin & Jianguo Zhu, 2023. "A Review of Electric Motors with Soft Magnetic Composite Cores for Electric Drives," Energies, MDPI, vol. 16(4), pages 1-17, February.

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