| Peer-Reviewed

An Intelligent Regenerative Braking Strategy for Power-split Hybrid Electric Vehicle

Received: 20 December 2019     Accepted: 17 January 2020     Published: 13 February 2020
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Abstract

Nowadays, hybrid electric vehicle (HEV) is a popularly vehicle due to its advances such as reducing fossil fuel consumption and emissions that affect on environment. Brake energy regeneration system is essential part in HEV and electric vehicle. It assists HEV in reducing fuel consumption and pollution emission. Regenerative braking system aims to discard heat energy from mechanical braking as vehicle decelerated. Therefore, design and develop a suitable regenerative braking system were always intended. The braking control strategies were variation and improvement. The mechanical – electric braking system was utilized. This braking system must achieve the criteria such as safety, stability, maximum energy recovery and the shortest the braking distance. This paper proposed a control strategy for this hybrid braking system. Firstly, braking performances were satisfied by braking torque distribution strategy between front and rear axles. Secondly, maximum energy recovery was computed by compromising between mechanical and electric braking torque. Two issues were implemented by applying fuzzy logic and rule-based to design the braking torque controllers. Two controllers were estimated through the results of simulation in power-split HEV. The controller, applied fuzzy-based, had significant improvements in fuel consumption compare with another one. In addition, this controller was more flexible in various driving conditions.

Published in International Journal of Mechanical Engineering and Applications (Volume 8, Issue 1)

This article belongs to the Special Issue Transportation Engineering Technology – Part IV

DOI 10.11648/j.ijmea.20200801.14
Page(s) 27-33
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Braking Force Distribution, Hybrid Electric Vehicle (HEV), Fuzzy Logic Control (FLC), Regenerative Braking System (RBS), Mechanical-Electric Braking System

References
[1] Y. Gao, L. P. Chen, and M. Ehsani, "Investigation of the effectiveness of regenerative braking for EV and HEV," SAE Trans., pp. 3184-3190, 1999.
[2] K. Rajashekara, "Power conversion and control strategies for fuel cell vehicles," In Proceeding of the 29th Annual Conference of the IEEE Industrial Electronics Sociaty, vol. 3, pp. 2865-2870, 2004.
[3] M. Zolot, T. Markel, and A. Pesaran, "Analysis offuel cell vehicle hybridization and implications for energy storage devices," Proceedings of the 4th avandced automotive battery conference, pp. 121-124, 2004.
[4] G. Xu, W. Li, K. Xu, and Z. Song, "An intelligent regenerative braking strategy for electric vehicles," Energy, vol. 4, pp. 1461-1477, 2011.
[5] S. R. Cikanek; K. E. Bailey, "Regenerative braking system for a hybrid electric vehicle", Proceedings of the 2002 American Control Conference (IEEE), 2002.
[6] J. K. Ahn, K. H. Jung, D. H. Kim, H. B. Jin, H. S. Kim & S. H. Hwang, "Analysis of a regenerative braking system for Hybrid Electric Vehicles using an Electro-Mechanical Brake", International Journal of Automotive Technology, vol. 10, pp. 229–234, 2009.
[7] J. G. Guo, J. P. Wang, and B. G. Cao, "Regenerative braking strategy for electric vehicles," Proceedings of the IEEE Intelligent vehicles symposium, pp. 864-868, 2005.
[8] H Yeo, H Kim,"Hardware-in-the-loop simulation of regenerative braking for a hybrid electric vehicle", Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 216, pp. 855-864, 2002.
[9] X. J. Li, L. F. Xu, J. F. Hua, J. Q. Li, and M. G. Ouyang, "Regenerative braking control strategy for fuel cell hybrid vehicles using fuzzy logic.," Proceedings of the International conference on electrical machines and systems pp. 2712-2716, 2008.
[10] J. M. Zhang, B. Y. Song, and S. M. Cui, "Fuzzy logic approach to regenerative braking system," Proceedings of the International conference on intelligent human-machine systems and cybernetics, pp. 451-454, 2009.
[11] J. B. Cao, B. G. Cao, W. Z. Chen, and P. Xu, "Neural network self-adaptive PID control for driving and regenerative braking of electric vehicle," Proceedings of the IEEE International conference on Automation and logistics, pp. 2019-2034, 2007.
[12] N. Mutoh and H. Yahagi, "Control methods suitable for electric vehicles with independently driven front and rear wheel structures," Vehicle Power and Propulsion, pp. 665-672, 2005.
[13] Mehrdad Ehsani, Y. Gao, and A. Emadi, “Modern electric, hybrid electric, and fuel cell vehicles: Fundamentals, theory, and design,” 2nd ed.: CRC Press, 2010.
[14] J.-S. Chen and Q.-V. Huynh, "Model and control power-split hybrid electric vehicle with fuzzy logic," Journal of Engineering Technology and Education, 2012.
[15] Liang Chu and W. Sun, "Integrative control strategy of regenerative and Hydraulic braking for hybrid electric car," IEEE Transactions on Vehicular Technology, 2009.
Cite This Article
  • APA Style

    Quoc-Viet Huynh, Ly Vinh Dat, Khanh-Tan Le. (2020). An Intelligent Regenerative Braking Strategy for Power-split Hybrid Electric Vehicle. International Journal of Mechanical Engineering and Applications, 8(1), 27-33. https://doi.org/10.11648/j.ijmea.20200801.14

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    ACS Style

    Quoc-Viet Huynh; Ly Vinh Dat; Khanh-Tan Le. An Intelligent Regenerative Braking Strategy for Power-split Hybrid Electric Vehicle. Int. J. Mech. Eng. Appl. 2020, 8(1), 27-33. doi: 10.11648/j.ijmea.20200801.14

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    AMA Style

    Quoc-Viet Huynh, Ly Vinh Dat, Khanh-Tan Le. An Intelligent Regenerative Braking Strategy for Power-split Hybrid Electric Vehicle. Int J Mech Eng Appl. 2020;8(1):27-33. doi: 10.11648/j.ijmea.20200801.14

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  • @article{10.11648/j.ijmea.20200801.14,
      author = {Quoc-Viet Huynh and Ly Vinh Dat and Khanh-Tan Le},
      title = {An Intelligent Regenerative Braking Strategy for Power-split Hybrid Electric Vehicle},
      journal = {International Journal of Mechanical Engineering and Applications},
      volume = {8},
      number = {1},
      pages = {27-33},
      doi = {10.11648/j.ijmea.20200801.14},
      url = {https://doi.org/10.11648/j.ijmea.20200801.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmea.20200801.14},
      abstract = {Nowadays, hybrid electric vehicle (HEV) is a popularly vehicle due to its advances such as reducing fossil fuel consumption and emissions that affect on environment. Brake energy regeneration system is essential part in HEV and electric vehicle. It assists HEV in reducing fuel consumption and pollution emission. Regenerative braking system aims to discard heat energy from mechanical braking as vehicle decelerated. Therefore, design and develop a suitable regenerative braking system were always intended. The braking control strategies were variation and improvement. The mechanical – electric braking system was utilized. This braking system must achieve the criteria such as safety, stability, maximum energy recovery and the shortest the braking distance. This paper proposed a control strategy for this hybrid braking system. Firstly, braking performances were satisfied by braking torque distribution strategy between front and rear axles. Secondly, maximum energy recovery was computed by compromising between mechanical and electric braking torque. Two issues were implemented by applying fuzzy logic and rule-based to design the braking torque controllers. Two controllers were estimated through the results of simulation in power-split HEV. The controller, applied fuzzy-based, had significant improvements in fuel consumption compare with another one. In addition, this controller was more flexible in various driving conditions.},
     year = {2020}
    }
    

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  • TY  - JOUR
    T1  - An Intelligent Regenerative Braking Strategy for Power-split Hybrid Electric Vehicle
    AU  - Quoc-Viet Huynh
    AU  - Ly Vinh Dat
    AU  - Khanh-Tan Le
    Y1  - 2020/02/13
    PY  - 2020
    N1  - https://doi.org/10.11648/j.ijmea.20200801.14
    DO  - 10.11648/j.ijmea.20200801.14
    T2  - International Journal of Mechanical Engineering and Applications
    JF  - International Journal of Mechanical Engineering and Applications
    JO  - International Journal of Mechanical Engineering and Applications
    SP  - 27
    EP  - 33
    PB  - Science Publishing Group
    SN  - 2330-0248
    UR  - https://doi.org/10.11648/j.ijmea.20200801.14
    AB  - Nowadays, hybrid electric vehicle (HEV) is a popularly vehicle due to its advances such as reducing fossil fuel consumption and emissions that affect on environment. Brake energy regeneration system is essential part in HEV and electric vehicle. It assists HEV in reducing fuel consumption and pollution emission. Regenerative braking system aims to discard heat energy from mechanical braking as vehicle decelerated. Therefore, design and develop a suitable regenerative braking system were always intended. The braking control strategies were variation and improvement. The mechanical – electric braking system was utilized. This braking system must achieve the criteria such as safety, stability, maximum energy recovery and the shortest the braking distance. This paper proposed a control strategy for this hybrid braking system. Firstly, braking performances were satisfied by braking torque distribution strategy between front and rear axles. Secondly, maximum energy recovery was computed by compromising between mechanical and electric braking torque. Two issues were implemented by applying fuzzy logic and rule-based to design the braking torque controllers. Two controllers were estimated through the results of simulation in power-split HEV. The controller, applied fuzzy-based, had significant improvements in fuel consumption compare with another one. In addition, this controller was more flexible in various driving conditions.
    VL  - 8
    IS  - 1
    ER  - 

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Author Information
  • Faculty of Vehicle and Energy Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Viet Nam

  • Faculty of Vehicle and Energy Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Viet Nam

  • Faculty of Vehicle and Energy Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Viet Nam

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