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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 368769, 11 pages
Research Article

Online Energy Management of Plug-In Hybrid Electric Vehicles for Prolongation of All-Electric Range Based on Dynamic Programming

1School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China
2Zhejiang Key Laboratory of Automobile Safety Technology, Hangzhou 310000, China
3BYD Auto Industry Co., Ltd., Shenzhen 518000, China

Received 4 September 2015; Revised 21 November 2015; Accepted 29 November 2015

Academic Editor: Xiaosong Hu

Copyright © 2015 Zeyu Chen et al. This 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.


The employed energy management strategy plays an important role in energy saving performance and exhausted emission reduction of plug-in hybrid electric vehicles (HEVs). An application of dynamic programming for optimization of power allocation is implemented in this paper with certain driving cycle and a limited driving range. Considering the DP algorithm can barely be used in real-time control because of its huge computational task and the dependence on a priori driving cycle, several online useful control rules are established based on the offline optimization results of DP. With the above efforts, an online energy management strategy is proposed finally. The presented energy management strategy concerns the prolongation of all-electric driving range as well as the energy saving performance. A simulation study is deployed to evaluate the control performance of the proposed energy management approach. All-electric range of the plug-in HEV can be prolonged by up to 2.86% for a certain driving condition. The energy saving performance is relative to the driving distance. The presented energy management strategy brings a little higher energy cost when driving distance is short, but for a long driving distance, it can reduce the energy consumption by up to 5.77% compared to the traditional CD-CS strategy.