IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i3p1049-d1326549.html
   My bibliography  Save this article

A Review of One-Box Electro-Hydraulic Braking System: Architecture, Control, and Application

Author

Listed:
  • Xinyu Zhao

    (School of Automotive Studies, Tongji University, Shanghai 201804, China
    Shanghai Tongyu Automotive Technology Co., Ltd., Shanghai 201804, China)

  • Lu Xiong

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Guirong Zhuo

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Wei Tian

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Jing Li

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Qiang Shu

    (Shanghai Tongyu Automotive Technology Co., Ltd., Shanghai 201804, China)

  • Xuanbai Zhao

    (Shanghai Tongyu Automotive Technology Co., Ltd., Shanghai 201804, China)

  • Guodong Xu

    (Shanghai Tongyu Automotive Technology Co., Ltd., Shanghai 201804, China)

Abstract

With the development of automobile electrification and intelligence, new requirements have been put forward for automotive braking technologies. Under this background, the One-box EHB (Electro-Hydraulic Braking system) brake-by-wire technology has emerged, which combines the electric booster and wheel-cylinder control module into one box and can realize vehicle stability and comfort functions such as service brake, pedal feel simulation, brake decoupling, failure backup, active braking, and wheel-cylinder pressure control. This article reviews the current research of key technologies of One-box EHB, including system architecture design and applications under high-level autonomous driving, master cylinder pressure control algorithm design, wheel-cylinder pressure control algorithm design, and electro-hydraulic composite braking control algorithm design. Finally, this article summarizes the current research status of One-box EHB key technologies and puts forward suggestions for future research directions.

Suggested Citation

  • Xinyu Zhao & Lu Xiong & Guirong Zhuo & Wei Tian & Jing Li & Qiang Shu & Xuanbai Zhao & Guodong Xu, 2024. "A Review of One-Box Electro-Hydraulic Braking System: Architecture, Control, and Application," Sustainability, MDPI, vol. 16(3), pages 1-31, January.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:3:p:1049-:d:1326549
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/3/1049/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/3/1049/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Filippo Carrese & Simone Sportiello & Tolegen Zhaksylykov & Chiara Colombaroni & Stefano Carrese & Muzio Papaveri & Sergio Maria Patella, 2023. "The Integration of Shared Autonomous Vehicles in Public Transportation Services: A Systematic Review," Sustainability, MDPI, vol. 15(17), pages 1-12, August.
    2. He, Hongwen & Wang, Chen & Jia, Hui & Cui, Xing, 2020. "An intelligent braking system composed single-pedal and multi-objective optimization neural network braking control strategies for electric vehicle," Applied Energy, Elsevier, vol. 259(C).
    Full references (including those not matched with items on IDEAS)

    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. Zhou, Xiaochuan & Wu, Gang & Wang, Chunyan & Zhang, Ruijun & Shi, Shuaipeng & Zhao, Wanzhong, 2024. "Cooperative optimization of energy recovery and braking feel based on vehicle speed prediction under downshifting conditions," Energy, Elsevier, vol. 301(C).
    2. He, Qiang & Yang, Yang & Luo, Chang & Zhai, Jun & Luo, Ronghua & Fu, Chunyun, 2022. "Energy recovery strategy optimization of dual-motor drive electric vehicle based on braking safety and efficient recovery," Energy, Elsevier, vol. 248(C).
    3. Sapan Tiwari & Neema Nassir & Patricia Sauri Lavieri, 2024. "Smart Insertion Strategies for Sustainable Operation of Shared Autonomous Vehicles," Sustainability, MDPI, vol. 16(12), pages 1-28, June.
    4. 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).
    5. Tong Wu & Jing Li & Xuan Qin, 2021. "Braking performance oriented multi–objective optimal design of electro–mechanical brake parameters," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-31, May.
    6. Fengrui Xu & Xuelin Liang & Mengqiao Chen & Wensheng Liu, 2022. "Robust Self-Learning PID Control of an Aircraft Anti-Skid Braking System," Mathematics, MDPI, vol. 10(8), pages 1-18, April.
    7. Yang, Chao & Sun, Tonglin & Wang, Weida & Li, Ying & Zhang, Yuhang & Zha, Mingjun, 2024. "Regenerative braking system development and perspectives for electric vehicles: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
    8. Dong, Haoxuan & Zhuang, Weichao & Chen, Boli & Wang, Yan & Lu, Yanbo & Liu, Ying & Xu, Liwei & Yin, Guodong, 2022. "A comparative study of energy-efficient driving strategy for connected internal combustion engine and electric vehicles at signalized intersections," Applied Energy, Elsevier, vol. 310(C).
    9. Zhang, Junjiang & Yang, Yang & Hu, Minghui & Yang, Zhong & Fu, Chunyun, 2021. "Longitudinal–vertical comprehensive control for four-wheel drive pure electric vehicle considering energy recovery and ride comfort," Energy, Elsevier, vol. 236(C).
    10. Zhang, Yuanjian & Huang, Yanjun & Chen, Haibo & Na, Xiaoxiang & Chen, Zheng & Liu, Yonggang, 2021. "Driving behavior oriented torque demand regulation for electric vehicles with single pedal driving," Energy, Elsevier, vol. 228(C).
    11. Yang, Jian & Liu, Bo & Zhang, Tiezhu & Hong, Jichao & Zhang, Hongxin, 2023. "Multi-parameter controlled mechatronics-electro-hydraulic power coupling electric vehicle based on active energy regulation," Energy, Elsevier, vol. 263(PC).
    12. Valery Vodovozov & Andrei Aksjonov & Eduard Petlenkov & Zoja Raud, 2021. "Neural Network-Based Model Reference Control of Braking Electric Vehicles," Energies, MDPI, vol. 14(9), pages 1-22, April.
    13. Li, Shicheng & Xu, Lin & Du, Xiaofang & Wang, Nian & Lin, Feng & Abdelkareem, Mohamed A.A., 2023. "Combined single-pedal and low adhesion control systems for enhanced energy regeneration in electric vehicles: Modeling, simulation, and on-field test," Energy, Elsevier, vol. 269(C).
    14. Wei, Hongqian & Ai, Qiang & Zhao, Wenqiang & Zhang, Youtong, 2022. "Modelling and experimental validation of an EV torque distribution strategy towards active safety and energy efficiency," Energy, Elsevier, vol. 239(PA).
    15. 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:jsusta:v:16:y:2024:i:3:p:1049-:d:1326549. 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.