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An Acceleration Slip Regulation Strategy for Four-Wheel Drive Electric Vehicles Based on Sliding Mode Control

Author

Listed:
  • Hongwen He

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Jiankun Peng

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Rui Xiong

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Hao Fan

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

Abstract

This paper presents an acceleration slip regulation (ASR) system for four-wheel drive (4WD) electric vehicles, which are driven by the front and rear axles simultaneously. The ASR control strategy includes three control modes: average distribution of inter-axle torque, optimal distribution of inter-axle torque and independent control of optimal slip rate, respectively, which are designed based on the torque adaptive principle of inter-axle differential and sliding mode control theory. Furthermore, in order to accurately describe the longitudinal tyre force characteristic, a slip rate calculation formula in the form of a state equation was used for solving the numerical problem posed by the traditional way. A simulation was carried out with the MATLAB/Simulink software. The simulation results show that the proposed ASR system can fully use the road friction condition, inhibit the drive-wheels from slipping, and improve the vehicle longitudinal driving stability.

Suggested Citation

  • Hongwen He & Jiankun Peng & Rui Xiong & Hao Fan, 2014. "An Acceleration Slip Regulation Strategy for Four-Wheel Drive Electric Vehicles Based on Sliding Mode Control," Energies, MDPI, vol. 7(6), pages 1-16, June.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:6:p:3748-3763:d:37149
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    References listed on IDEAS

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    1. Jiankun Peng & Hongwen He & Nenglian Feng, 2013. "Simulation Research on an Electric Vehicle Chassis System Based on a Collaborative Control System," Energies, MDPI, vol. 6(1), pages 1-17, January.
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    Cited by:

    1. Ran Chen & Zongxia Jiao & Liang Yan & Yaoxing Shang & Shuai Wu, 2019. "Nonlinear Synchronous Control for H-Type Gantry Stage Used in Electric Vehicles Manufacturing," Energies, MDPI, vol. 12(12), pages 1-16, June.
    2. Jiangyi Lv & Hongwen He & Wei Liu & Yong Chen & Fengchun Sun, 2019. "Vehicle Velocity Estimation Fusion with Kinematic Integral and Empirical Correction on Multi-Timescales," Energies, MDPI, vol. 12(7), pages 1-24, April.
    3. Xudong Zhang & Dietmar Göhlich, 2017. "Integrated Traction Control Strategy for Distributed Drive Electric Vehicles with Improvement of Economy and Longitudinal Driving Stability," Energies, MDPI, vol. 10(1), pages 1-18, January.
    4. Binh-Minh Nguyen & Hung Van Nguyen & Minh Ta-Cao & Michihiro Kawanishi, 2020. "Longitudinal Modelling and Control of In-Wheel-Motor Electric Vehicles as Multi-Agent Systems," Energies, MDPI, vol. 13(20), pages 1-28, October.
    5. Lingfei Wu & Jinfang Gou & Lifang Wang & Junzhi Zhang, 2015. "Acceleration Slip Regulation Strategy for Distributed Drive Electric Vehicles with Independent Front Axle Drive Motors," Energies, MDPI, vol. 8(5), pages 1-30, May.
    6. Cheng Lin & Zhifeng Xu, 2015. "Wheel Torque Distribution of Four-Wheel-Drive Electric Vehicles Based on Multi-Objective Optimization," Energies, MDPI, vol. 8(5), pages 1-17, April.
    7. Wanke Cao & Helin Liu & Cheng Lin & Yuhua Chang & Zhiyin Liu & Antoni Szumanowski, 2017. "Co-Design Based Lateral Motion Control of All-Wheel-Independent-Drive Electric Vehicles with Network Congestion," Energies, MDPI, vol. 10(10), pages 1-16, October.
    8. Thanh Vo-Duy & Minh C. Ta & Bảo-Huy Nguyễn & João Pedro F. Trovão, 2020. "Experimental Platform for Evaluation of On-Board Real-Time Motion Controllers for Electric Vehicles," Energies, MDPI, vol. 13(23), pages 1-28, December.
    9. Kanghyun Nam & Yoichi Hori & Choonyoung Lee, 2015. "Wheel Slip Control for Improving Traction-Ability and Energy Efficiency of a Personal Electric Vehicle," Energies, MDPI, vol. 8(7), pages 1-21, July.
    10. Xudong Zhang & Dietmar Göhlich, 2017. "A hierarchical estimator development for estimation of tire-road friction coefficient," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-21, February.
    11. Miranda, Matheus H.R. & Silva, Fabrício L. & Lourenço, Maria A.M. & Eckert, Jony J. & Silva, Ludmila C.A., 2022. "Electric vehicle powertrain and fuzzy controller optimization using a planar dynamics simulation based on a real-world driving cycle," Energy, Elsevier, vol. 238(PC).

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