Multi-Lookup Table Based Regenerative Braking Strategy of Plug-in Hybrid Electric Vehicle

Article Preview

Abstract:

. In order to improve the energy efficiency of plug-in hybrid electric vehicles, it is important to design a suitable regenerative braking strategy. There are many control strategies that have been developed and presented for plug-in hybrid electric vehicles. Most of them are aimed to energy flow management, and seldom involves regenerative braking control. In this paper, a regenerative braking strategy based on multi-lookup table method is proposed for plug-in hybrid electric vehicles. Decelerations are introduced as the index of Table Selector, so braking force distribution coefficients can be flexibly adjusted using the proposed strategy. Finally, the simulation results show the validity of the novel strategy.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1509-1513

Citation:

Online since:

December 2010

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] C. C. Chan and K. T. Chau. Modern electric vehicle technology[M]. Oxford University Press, (2001).

Google Scholar

[2] Zhang Xiang, Wang Jia and Yang Jianzhong, et al. Prospects of New Energy Vehicles for China Market, Hybrid and Eco-Friendly Vehicle Conference, 2008, Page(s): 1 – 11.

DOI: 10.1049/cp:20081055

Google Scholar

[3] Fritz R. Kalhammer, Haresh Kamath, and Mark Duvall, et al. Plug-In Hybrid Electric Vehicles: Promise, Issues and Prospects, EVS24 International Battery, Hybrid and Fuel Cell Electric Vehicle Symposium, 1-11, Stavanger, Norway, May 13-16, (2009).

Google Scholar

[4] Yimin Gao, Liping Chen,Mehrdad Ehsani,Investigation of the Effectiveness of Regenerative Braking for EV and HEV[J], SAE, 1999-01-2910.

DOI: 10.4271/1999-01-2910

Google Scholar

[5] Moura, S. J.; Fathy, H. K.; Callaway, D. S.; Stein, J. L.; A Stochastic Optimal Control Approach for Power Management in Plug-In Hybrid Electric Vehicles. IEEE Transactions on Control Systems Technology, 2010, Volume: 57, Issue: 99 Page(s): 1 – 11.

DOI: 10.1109/tcst.2010.2043736

Google Scholar

[6] Chenghong Yang; Jun Li; Wei Sun; Bo Zhang; Ying Gao; Xuefeng Yin; Study on Global Optimization of Plug-In Hybrid Electric Vehicle Energy Management Strategies, Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific, 2010 , Page(s): 1 – 5.

DOI: 10.1109/appeec.2010.5448895

Google Scholar

[7] Yimin Gao; Ehsani, M.; Design and Control Methodology of Plug-in Hybrid Electric Vehicles. IEEE Transactions on Industrial Electronics, 2010 , Volume: 57 , Issue: 2, Page(s): 633 – 640.

DOI: 10.1109/tie.2009.2027918

Google Scholar

[8] Li Yushan; Zeng Qingliang; Wang Chenglong; Li Yuanjie; Research on Fuzzy Logic Control Strategy for a Plug-in Hybrid Electric City Public Bus, 2010 International Conference on Measuring Technology and Mechatronics Automation, 2010, Volume: 3 Page(s): 88 – 91.

DOI: 10.1109/icmtma.2010.754

Google Scholar

[9] Wang Zijie, Huang Miaohua, Deng Yadong. Modeling and Simulation of the Regenerative Braking System for Electrical Vehicles[J]. Journal of Chinese Wuhan University of Technology (Information & Management Engineering), 2001, 23(4): 102-105.

Google Scholar

[10] Cuddy, M., Burch, S. and Markel, T. etc. ADVISOR2002-ADVANCED VEHICLE SIMULATOR. NREL Document. April, 2002.

Google Scholar