IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i1p126-d88259.html
   My bibliography  Save this article

Integrated Traction Control Strategy for Distributed Drive Electric Vehicles with Improvement of Economy and Longitudinal Driving Stability

Author

Listed:
  • Xudong Zhang

    (Methods for Product Development and Mechatronics, Technical University of Berlin, 10623 Berlin, Germany)

  • Dietmar Göhlich

    (Methods for Product Development and Mechatronics, Technical University of Berlin, 10623 Berlin, Germany)

Abstract

This paper presents an integrated traction control strategy (ITCS) for distributed drive electric vehicles. The purpose of the proposed strategy is to improve vehicle economy and longitudinal driving stability. On high adhesion roads, economy optimization algorithm is applied to maximize motors efficiency by means of the optimized torque distribution. On low adhesion roads, a sliding mode control (SMC) algorithm is implemented to guarantee the wheel slip ratio around the optimal slip ratio point to make full use of road adhesion capacity. In order to avoid the disturbance on slip ratio calculation due to the low vehicle speed, wheel rotational speed is taken as the control variable. Since the optimal slip ratio varies according to different road conditions, Bayesian hypothesis selection is utilized to estimate the road friction coefficient. Additionally, the ITCS is designed for combining the vehicle economy and stability control through three traction allocation cases: economy-based traction allocation, pedal self-correcting traction allocation and inter-axles traction allocation. Finally, simulations are conducted in CarSim and Matlab/Simulink environment. The results show that the proposed strategy effectively reduces vehicle energy consumption, suppresses wheels-skid and enhances the vehicle longitudinal stability and dynamic performance.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:1:p:126-:d:88259
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/1/126/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/1/126/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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. 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.
    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. 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.
    4. 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).
    5. 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.

    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. 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.
    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. 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.
    4. 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.
    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. 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.
    8. 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).
    9. Anith Khairunnisa Ghazali & Mohd Khair Hassan & Mohd Amran Mohd Radzi & Azizan As’arry, 2023. "Optimizing Energy Harvesting: A Gain-Scheduled Braking System for Electric Vehicles with Enhanced State of Charge and Efficiency," Energies, MDPI, vol. 16(12), pages 1-19, June.
    10. Idris Idris Sunusi & Jun Zhou & Chenyang Sun & Zhenzhen Wang & Jianlei Zhao & Yongshuan Wu, 2021. "Development of Online Adaptive Traction Control for Electric Robotic Tractors," Energies, MDPI, vol. 14(12), pages 1-24, June.
    11. 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.
    12. 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.
    13. Zhenpo Wang & Changhui Qu & Lei Zhang & Jin Zhang & Wen Yu, 2018. "Integrated Sizing and Energy Management for Four-Wheel-Independently-Actuated Electric Vehicles Considering Realistic Constructed Driving Cycles," Energies, MDPI, vol. 11(7), pages 1-22, July.
    14. Valery Vodovozov & Zoja Raud & Eduard Petlenkov, 2021. "Review on Braking Energy Management in Electric Vehicles," Energies, MDPI, vol. 14(15), pages 1-26, July.

    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:10:y:2017:i:1:p:126-:d:88259. 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.