IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i9p2438-d169774.html
   My bibliography  Save this article

Steering Stability Control for a Four Hub-Motor Independent-Drive Electric Vehicle with Varying Adhesion Coefficient

Author

Listed:
  • Rufei Hou

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Co-Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081, China)

  • Li Zhai

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Co-Innovation Center of Electric Vehicles in Beijing, Beijing Institute of Technology, Beijing 100081, China)

  • Tianmin Sun

    (BAIC BJEV Inc., Beijing 100021, China)

Abstract

In order to enhance the steering stability of a four hub-motor independent-drive electric vehicle (4MIDEV) on a road with varying adhesion coefficient, for example on a joint road, this paper proposes a hierarchical steering stability control strategy adapted to the road adhesion. The upper control level of the proposed strategy realizes the integrated control of the sideslip angle and yaw rate in the direct yaw moment control (DYC), where the influences of the road adhesion and sideslip angle are both studied by the fuzzy control. The lower control level employs a weight-based optimal torque distribution algorithm in which weight factors for each motor torque are designed to accommodate different adhesion of each wheel. The proposed stability control strategy was validated in a co-simulation of the Carsim and Matlab/Simulink platforms. The results of double-lane-change maneuver simulations under different conditions indicate that the proposed strategy can effectively achieve robustness to changes in the adhesion coefficient and improve the steering stability of the 4MIDEV.

Suggested Citation

  • Rufei Hou & Li Zhai & Tianmin Sun, 2018. "Steering Stability Control for a Four Hub-Motor Independent-Drive Electric Vehicle with Varying Adhesion Coefficient," Energies, MDPI, vol. 11(9), pages 1-17, September.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2438-:d:169774
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/9/2438/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/11/9/2438/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhenpo Wang & Yachao Wang & Lei Zhang & Mingchun Liu, 2017. "Vehicle Stability Enhancement through Hierarchical Control for a Four-Wheel-Independently-Actuated Electric Vehicle," Energies, MDPI, vol. 10(7), pages 1-18, July.
    2. Mingchun Liu & Feihong Gu & Yuanzhi Zhang, 2017. "Ride Comfort Optimization of In-Wheel-Motor Electric Vehicles with In-Wheel Vibration Absorbers," Energies, MDPI, vol. 10(10), pages 1-21, October.
    3. 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.
    4. 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.
    5. Li Zhai & Rufei Hou & Tianmin Sun & Steven Kavuma, 2018. "Continuous Steering Stability Control Based on an Energy-Saving Torque Distribution Algorithm for a Four in-Wheel-Motor Independent-Drive Electric Vehicle," Energies, MDPI, vol. 11(2), pages 1-19, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Miranda, Matheus H.R. & Silva, Fabrício L. & Lourenço, Maria A.M. & Eckert, Jony J. & Silva, Ludmila C.A., 2022. "Vehicle drivetrain and fuzzy controller optimization using a planar dynamics simulation based on a real-world driving cycle," Energy, Elsevier, vol. 257(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li Zhai & Rufei Hou & Tianmin Sun & Steven Kavuma, 2018. "Continuous Steering Stability Control Based on an Energy-Saving Torque Distribution Algorithm for a Four in-Wheel-Motor Independent-Drive Electric Vehicle," Energies, MDPI, vol. 11(2), pages 1-19, February.
    2. Szilárd Czibere & Ádám Domina & Ádám Bárdos & Zsolt Szalay, 2021. "Model Predictive Controller Design for Vehicle Motion Control at Handling Limits in Multiple Equilibria on Varying Road Surfaces," Energies, MDPI, vol. 14(20), pages 1-17, October.
    3. Louback, Eduardo & Biswas, Atriya & Machado, Fabricio & Emadi, Ali, 2024. "A review of the design process of energy management systems for dual-motor battery electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    4. 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.
    5. Rui Xiong & Suleiman M. Sharkh & Xi Zhang, 2018. "Research Progress on Electric and Intelligent Vehicles," Energies, MDPI, vol. 11(7), pages 1-5, July.
    6. Zhaolong Zhang & Yuan Zou & Xudong Zhang & Zhifeng Xu & Han Wang, 2020. "Driver Model Based on Optimized Calculation and Functional Safety Simulation," Energies, MDPI, vol. 13(24), pages 1-12, December.
    7. Piotr Szewczyk & Andrzej Łebkowski, 2021. "Studies on Energy Consumption of Electric Light Commercial Vehicle Powered by In-Wheel Drive Modules," Energies, MDPI, vol. 14(22), pages 1-28, November.
    8. Zhenyuan Bai & Yufeng Lu & Yunxia Li, 2020. "Method of Improving Lateral Stability by Using Additional Yaw Moment of Semi-Trailer," Energies, MDPI, vol. 13(23), pages 1-23, November.
    9. Mingchun Liu & Feihong Gu & Yuanzhi Zhang, 2017. "Ride Comfort Optimization of In-Wheel-Motor Electric Vehicles with In-Wheel Vibration Absorbers," Energies, MDPI, vol. 10(10), pages 1-21, October.
    10. 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).
    11. Junnian Wang & Siwen Lv & Nana Sun & Shoulin Gao & Wen Sun & Zidong Zhou, 2021. "Torque Vectoring Control of RWID Electric Vehicle for Reducing Driving-Wheel Slippage Energy Dissipation in Cornering," Energies, MDPI, vol. 14(23), pages 1-16, December.
    12. Peikun Sun & Annika Stensson Trigell & Lars Drugge & Jenny Jerrelind, 2020. "Energy-Efficient Direct Yaw Moment Control for In-Wheel Motor Electric Vehicles Utilising Motor Efficiency Maps," Energies, MDPI, vol. 13(3), pages 1-25, January.
    13. Wei Chen & Jiaojiao Liang & Tingna Shi, 2018. "Speed Synchronous Control of Multiple Permanent Magnet Synchronous Motors Based on an Improved Cross-Coupling Structure," Energies, MDPI, vol. 11(2), pages 1-16, January.
    14. Jiongjiong Cai & Peng Ke & Xiao Qu & Zihui Wang, 2022. "Research on the Design of Auxiliary Generator for Enthalpy Reduction and Steady Speed Scroll Expander," Energies, MDPI, vol. 15(9), pages 1-17, April.
    15. Mohamed Derbeli & Cristian Napole & Oscar Barambones & Jesus Sanchez & Isidro Calvo & Pablo Fernández-Bustamante, 2021. "Maximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applications," Energies, MDPI, vol. 14(22), pages 1-31, November.
    16. Wen Sun & Yang Chen & Junnian Wang & Xiangyu Wang & Lili Liu, 2022. "Research on TVD Control of Cornering Energy Consumption for Distributed Drive Electric Vehicles Based on PMP," Energies, MDPI, vol. 15(7), pages 1-19, April.
    17. Mingchun Liu & Feihong Gu & Juhua Huang & Changjiang Wang & Ming Cao, 2017. "Integration Design and Optimization Control of a Dynamic Vibration Absorber for Electric Wheels with In-Wheel Motor," Energies, MDPI, vol. 10(12), pages 1-23, December.
    18. 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.
    19. Wei, Hongqian & Zhang, Nan & Liang, Jun & Ai, Qiang & Zhao, Wenqiang & Huang, Tianyi & Zhang, Youtong, 2022. "Deep reinforcement learning based direct torque control strategy for distributed drive electric vehicles considering active safety and energy saving performance," Energy, Elsevier, vol. 238(PB).
    20. Balázs Németh, 2021. "Coordination of Lateral Vehicle Control Systems Using Learning-Based Strategies," Energies, MDPI, vol. 14(5), pages 1-17, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2438-:d:169774. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.