Volume 8, Issue 1, February 2020, Page: 27-33
An Intelligent Regenerative Braking Strategy for Power-split Hybrid Electric Vehicle
Quoc-Viet Huynh, Faculty of Vehicle and Energy Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Viet Nam
Ly Vinh Dat, Faculty of Vehicle and Energy Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Viet Nam
Khanh-Tan Le, Faculty of Vehicle and Energy Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Viet Nam
Received: Dec. 20, 2019;       Accepted: Jan. 17, 2020;       Published: Feb. 13, 2020
DOI: 10.11648/j.ijmea.20200801.14      View  613      Downloads  245
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.
Braking Force Distribution, Hybrid Electric Vehicle (HEV), Fuzzy Logic Control (FLC), Regenerative Braking System (RBS), Mechanical-Electric Braking System
To cite this article
Quoc-Viet Huynh, Ly Vinh Dat, Khanh-Tan Le, An Intelligent Regenerative Braking Strategy for Power-split Hybrid Electric Vehicle, International Journal of Mechanical Engineering and Applications. Special Issue: Transportation Engineering Technology – Part IV. Vol. 8, No. 1, 2020, pp. 27-33. doi: 10.11648/j.ijmea.20200801.14
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.
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.
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.
G. Xu, W. Li, K. Xu, and Z. Song, "An intelligent regenerative braking strategy for electric vehicles," Energy, vol. 4, pp. 1461-1477, 2011.
S. R. Cikanek; K. E. Bailey, "Regenerative braking system for a hybrid electric vehicle", Proceedings of the 2002 American Control Conference (IEEE), 2002.
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.
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.
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.
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.
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.
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.
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.
Mehrdad Ehsani, Y. Gao, and A. Emadi, “Modern electric, hybrid electric, and fuel cell vehicles: Fundamentals, theory, and design,” 2nd ed.: CRC Press, 2010.
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.
Liang Chu and W. Sun, "Integrative control strategy of regenerative and Hydraulic braking for hybrid electric car," IEEE Transactions on Vehicular Technology, 2009.
Browse journals by subject