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Study on a Wheel Electric Drive System with SRD for Loader

Author

Listed:
  • Xinming Xu

    (College of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha 410128, China
    Hunan Provincial Key Laboratory of Intelligent Agricultural Machinery Equipment, Changsha 410128, China)

  • Yang Gu

    (School of Mechanical Engineering, Tongji University, Shanghai 200092, China)

  • Guangjun Liu

    (School of Mechanical Engineering, Tongji University, Shanghai 200092, China)

Abstract

Loaders are widely used in the construction of earthworks for construction projects. Due to the large volume and mass of these machines, they have shortcomings such as low driving efficiency and high energy consumption. To address these shortcomings, this work applied eclectic drive technology to a loader’s traction system. A wheel electric drive system with a switched reluctance driver (SRD) was developed. The operating principle and basic structure of the SRD system were analyzed. A new voltage PWM-controlled strategy with dynamic adjustable turn-on and turn-off angles and a single conducting phase in a fixed period was developed. Then, an SRD simulation model was established in MATLAB/Simulink. A simulation of the working condition for the loader was performed. A test bench for the SRD was built and accordingly the transportation and operation conditions were tested. The corresponding speed–time curve of transportation and operation was obtained. Simulation and experiment results showed that the electric drive system with SRD had excellent responses to changes in torque and speed and adapted well to the various working conditions of the loader. The system could effectively traction the loader and verified the feasibility and applicability of the wheel electric drive system.

Suggested Citation

  • Xinming Xu & Yang Gu & Guangjun Liu, 2022. "Study on a Wheel Electric Drive System with SRD for Loader," Energies, MDPI, vol. 15(10), pages 1-16, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3781-:d:820511
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    References listed on IDEAS

    as
    1. Yang, Jian & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin & Zhao, Qinghai & Meng, Zewen, 2021. "Research on driving control strategy and Fuzzy logic optimization of a novel mechatronics-electro-hydraulic power coupling electric vehicle," Energy, Elsevier, vol. 233(C).
    2. Mahmoud A. Gaafar & Arwa Abdelmaksoud & Mohamed Orabi & Hao Chen & Mostafa Dardeer, 2021. "Performance Investigation of Switched Reluctance Motor Driven by Quasi-Z-Source Integrated Multiport Converter with Different Switching Algorithms," Sustainability, MDPI, vol. 13(17), pages 1-14, August.
    3. Songlin Yang & Jingan Feng & Bao Song, 2021. "Research on Decoupled Optimal Control of Straight-Line Driving Stability of Electric Vehicles Driven by Four-Wheel Hub Motors," Energies, MDPI, vol. 14(18), pages 1-25, September.
    4. Jichao Han & Baojun Ge & Kai Zhang & Yang Wang & Chao Wang, 2020. "Influence of Control and Structure Parameters on the Starting Performance of a 12/8 Pole Switched Reluctance Motor," Energies, MDPI, vol. 13(14), pages 1-15, July.
    5. Yuanfeng Lan & Yassine Benomar & Kritika Deepak & Ahmet Aksoz & Mohamed El Baghdadi & Emine Bostanci & Omar Hegazy, 2021. "Switched Reluctance Motors and Drive Systems for Electric Vehicle Powertrains: State of the Art Analysis and Future Trends," Energies, MDPI, vol. 14(8), pages 1-29, April.
    Full references (including those not matched with items on IDEAS)

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