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Coordinated Slip Control of Multi-Axle Distributed Drive Vehicle Based on HLQR

Author

Listed:
  • Yutong Bao

    (Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China
    Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory, Foshan 528200, China
    Hubei Research Center for New Energy & Intelligent Connected Vehicle, Wuhan University of Technology, Wuhan 430070, China)

  • Changqing Du

    (Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China
    Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory, Foshan 528200, China
    Hubei Research Center for New Energy & Intelligent Connected Vehicle, Wuhan University of Technology, Wuhan 430070, China)

  • Dongmei Wu

    (Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China
    Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory, Foshan 528200, China
    Hubei Research Center for New Energy & Intelligent Connected Vehicle, Wuhan University of Technology, Wuhan 430070, China)

  • Huan Liu

    (Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China
    Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory, Foshan 528200, China
    Hubei Research Center for New Energy & Intelligent Connected Vehicle, Wuhan University of Technology, Wuhan 430070, China)

  • Wei Liu

    (School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA)

  • Jun Li

    (Tsinghua Intelligent Vehicle Design and Safety Research Institute, Tsinghua University, Beijing 100084, China)

Abstract

For multi-axle distributed drive (MADD) vehicles, the complexity of the longitudinal dynamics control system increases with the number of driven wheels, which presents a huge challenge to control the multi-motor drive vehicle with more than four wheels. To reduce the control system complexity, this paper proposes a coordinated slip control algorithm using the hierarchical linear quadratic regulator (HLQR) scheme for a 12 × 12 MADD vehicle. The 12-wheel driving system is decoupled based on the wheel load and simplified to a double local subsystem. First, the 12 × 12 MADD vehicle dynamics model is established. Then, the optimal slip ratio is obtained on the basis of the road friction coefficient estimation through a fuzzy control algorithm when the wheel slips. Afterwards, the wheel slip ratio is controlled based on the HLQR program for anti-slip regulation. Furthermore, the driving torque control allocation based on quadratic programming (QR) is coordinated with the anti-slip control. Simulink results show that the proposed coordinated slip control based on HLQR can improve slip control accuracy by more than 30% and greatly reduce the calculation load. The torque control allocation is also limited by the slip control results to ensure wheel dynamic stability and smoothly satisfy the driver’s demand.

Suggested Citation

  • Yutong Bao & Changqing Du & Dongmei Wu & Huan Liu & Wei Liu & Jun Li, 2023. "Coordinated Slip Control of Multi-Axle Distributed Drive Vehicle Based on HLQR," Mathematics, MDPI, vol. 11(8), pages 1-18, April.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:8:p:1964-:d:1129286
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    References listed on IDEAS

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    1. Lunhaojie Liu & Juntao Fei & Xianghua Yang, 2023. "Adaptive Interval Type-2 Fuzzy Neural Network Sliding Mode Control of Nonlinear Systems Using Improved Extended State Observer," Mathematics, MDPI, vol. 11(3), pages 1-20, January.
    2. Han, Zhongliang & Xu, Nan & Chen, Hong & Huang, Yanjun & Zhao, Bin, 2018. "Energy-efficient control of electric vehicles based on linear quadratic regulator and phase plane analysis," Applied Energy, Elsevier, vol. 213(C), pages 639-657.
    3. Mahmoud Hamouda & Fahad Al-Amyal & Ismoil Odinaev & Mohamed N. Ibrahim & László Számel, 2022. "A Novel Universal Torque Control of Switched Reluctance Motors for Electric Vehicles," Mathematics, MDPI, vol. 10(20), pages 1-21, October.
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