IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i3p497-d133534.html
   My bibliography  Save this article

Regenerative Braking Compensatory Control Strategy Considering CVT Power Loss for Hybrid Electric Vehicles

Author

Listed:
  • Yang Yang

    (State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China
    School of Automotive Engineering, Chongqing University, Chongqing 400044, China)

  • Xiaolong He

    (School of Automotive Engineering, Chongqing University, Chongqing 400044, China)

  • Yi Zhang

    (Department of Mechanical Engineering, University of Michigan-Dearborn, Dearborn, MI 48128, USA)

  • Datong Qin

    (State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China
    School of Automotive Engineering, Chongqing University, Chongqing 400044, China)

Abstract

Hybrid electric vehicles (HEV) equipped with continuously variable transmission (CVT) adjust the motor operating point continuously to achieve the optimal motor operating efficiency during regenerative braking. Traditional control strategies consider the CVT efficiency as constant, while the CVT efficiency varies in different operating conditions. In order to reflect the transmission efficiency more accurately during regenerative braking, the CVT theoretical torque loss model is firstly established which then leads to the battery–front motor–CVT joint operating efficiency model. The joint operating efficiency model indicates that the system efficiency is influenced by input speed, input torque, CVT speed ratio, and battery SOC (state of charge). The compensatory strategy for the front motor barking force is proposed to make full use of its braking power and the CVT speed ratio control strategy is modified to maintain the optimal operating efficiency of the system. The simulations are performed under three typical braking conditions and UDDS, NYCC, US06 respectively, the results show that the modified control strategy increases the front motor braking power and improves the system operating efficiency.

Suggested Citation

  • Yang Yang & Xiaolong He & Yi Zhang & Datong Qin, 2018. "Regenerative Braking Compensatory Control Strategy Considering CVT Power Loss for Hybrid Electric Vehicles," Energies, MDPI, vol. 11(3), pages 1-15, February.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:497-:d:133534
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/3/497/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/3/497/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guoqing Xu & Weimin Li & Kun Xu & Zhibin Song, 2011. "An Intelligent Regenerative Braking Strategy for Electric Vehicles," Energies, MDPI, vol. 4(9), pages 1-17, September.
    2. Li, Liang & Wang, Xiangyu & Xiong, Rui & He, Kai & Li, Xujian, 2016. "AMT downshifting strategy design of HEV during regenerative braking process for energy conservation," Applied Energy, Elsevier, vol. 183(C), pages 914-925.
    3. Li, Liang & Li, Xujian & Wang, Xiangyu & Song, Jian & He, Kai & Li, Chenfeng, 2016. "Analysis of downshift’s improvement to energy efficiency of an electric vehicle during regenerative braking," Applied Energy, Elsevier, vol. 176(C), pages 125-137.
    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. 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).
    2. Nena Apostolidou & Nick Papanikolaou, 2018. "Energy Saving Estimation of Athens Trolleybuses Considering Regenerative Braking and Improved Control Scheme," Resources, MDPI, vol. 7(3), pages 1-18, July.
    3. Yang Yang & Qiang He & Yongzheng Chen & Chunyun Fu, 2020. "Efficiency Optimization and Control Strategy of Regenerative Braking System with Dual Motor," Energies, MDPI, vol. 13(3), pages 1-21, February.
    4. Hyung-jin Do & Se-hoon Oh, 2022. "CVT for a Small Electric Vehicle Using Centrifugal Belt Pulley," Energies, MDPI, vol. 15(23), pages 1-15, November.
    5. Hu, Jianjun & Mei, Bo & Peng, Hang & Guo, Zihan, 2019. "Discretely variable speed ratio control strategy for continuously variable transmission system considering hydraulic energy loss," Energy, Elsevier, vol. 180(C), pages 714-727.

    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. 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).
    2. Jiangbo Wang & Kai Liu & Toshiyuki Yamamoto, 2017. "Improving Electricity Consumption Estimation for Electric Vehicles Based on Sparse GPS Observations," Energies, MDPI, vol. 10(1), pages 1-12, January.
    3. Antonia Tamborrino & Claudio Perone & Filippo Catalano & Giacomo Squeo & Francesco Caponio & Biagio Bianchi, 2019. "Modelling Energy Consumption and Energy-Saving in High-Quality Olive Oil Decanter Centrifuge: Numerical Study and Experimental Validation," Energies, MDPI, vol. 12(13), pages 1-20, July.
    4. Liu, Kai & Wang, Jiangbo & Yamamoto, Toshiyuki & Morikawa, Takayuki, 2018. "Exploring the interactive effects of ambient temperature and vehicle auxiliary loads on electric vehicle energy consumption," Applied Energy, Elsevier, vol. 227(C), pages 324-331.
    5. Qi, Lingfei & Wu, Xiaoping & Zeng, Xiaohui & Feng, Yan & Pan, Hongye & Zhang, Zutao & Yuan, Yanping, 2020. "An electro-mechanical braking energy recovery system based on coil springs for energy saving applications in electric vehicles," Energy, Elsevier, vol. 200(C).
    6. Zhao, Mingjie & Shi, Junhui & Lin, Cheng, 2019. "Optimization of integrated energy management for a dual-motor coaxial coupling propulsion electric city bus," Applied Energy, Elsevier, vol. 243(C), pages 21-34.
    7. Muhammad Khalid, 2019. "A Review on the Selected Applications of Battery-Supercapacitor Hybrid Energy Storage Systems for Microgrids," Energies, MDPI, vol. 12(23), pages 1-34, November.
    8. López, I. & Ibarra, E. & Matallana, A. & Andreu, J. & Kortabarria, I., 2019. "Next generation electric drives for HEV/EV propulsion systems: Technology, trends and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    9. Wasbari, F. & Bakar, R.A. & Gan, L.M. & Tahir, M.M. & Yusof, A.A., 2017. "A review of compressed-air hybrid technology in vehicle system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 935-953.
    10. Ramesh Kumar Chidambaram & Dipankar Chatterjee & Barnali Barman & Partha Pratim Das & Dawid Taler & Jan Taler & Tomasz Sobota, 2023. "Effect of Regenerative Braking on Battery Life," Energies, MDPI, vol. 16(14), pages 1-24, July.
    11. Emilia M. Szumska & Rafał S. Jurecki, 2021. "Parameters Influencing on Electric Vehicle Range," Energies, MDPI, vol. 14(16), pages 1-23, August.
    12. Liu, Kai & Wang, Jiangbo & Yamamoto, Toshiyuki & Morikawa, Takayuki, 2016. "Modelling the multilevel structure and mixed effects of the factors influencing the energy consumption of electric vehicles," Applied Energy, Elsevier, vol. 183(C), pages 1351-1360.
    13. 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.
    14. Duo Zhang & Guohai Liu & Wenxiang Zhao & Penghu Miao & Yan Jiang & Huawei Zhou, 2014. "A Neural Network Combined Inverse Controller for a Two-Rear-Wheel Independently Driven Electric Vehicle," Energies, MDPI, vol. 7(7), pages 1-15, July.
    15. Jingang Guo & Xiaoping Jian & Guangyu Lin, 2014. "Performance Evaluation of an Anti-Lock Braking System for Electric Vehicles with a Fuzzy Sliding Mode Controller," Energies, MDPI, vol. 7(10), pages 1-18, October.
    16. Zhao, Weiwei & Zhang, Tongtong & Kildahl, Harriet & Ding, Yulong, 2022. "Mobile energy recovery and storage: Multiple energy-powered EVs and refuelling stations," Energy, Elsevier, vol. 257(C).
    17. Cui, Taowen & Zhao, Wanzhong & Wang, Chunyan, 2019. "Design optimization of vehicle EHPS system based on multi-objective genetic algorithm," Energy, Elsevier, vol. 179(C), pages 100-110.
    18. Pugi, L. & Pagliai, M. & Nocentini, A. & Lutzemberger, G. & Pretto, A., 2017. "Design of a hydraulic servo-actuation fed by a regenerative braking system," Applied Energy, Elsevier, vol. 187(C), pages 96-115.
    19. Jinhyun Park & In Gyu Jang & Sung-Ho Hwang, 2018. "Torque Distribution Algorithm for an Independently Driven Electric Vehicle Using a Fuzzy Control Method: Driving Stability and Efficiency," Energies, MDPI, vol. 11(12), pages 1-22, December.
    20. Petronilla Fragiacomo & Francesco Piraino & Matteo Genovese & Lorenzo Flaccomio Nardi Dei & Daria Donati & Michele Vincenzo Migliarese Caputi & Domenico Borello, 2022. "Sizing and Performance Analysis of Hydrogen- and Battery-Based Powertrains, Integrated into a Passenger Train for a Regional Track, Located in Calabria (Italy)," Energies, MDPI, vol. 15(16), pages 1-20, August.

    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:3:p:497-:d:133534. 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.