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

被引:14
作者
Chen, Zeyu [1 ]
Liu, Weiguo [2 ]
Yang, Ying [1 ]
Chen, Weiqiang [1 ,3 ]
机构
[1] Northeastern Univ, Sch Mech Engn & Automat, Shenyang 110819, Peoples R China
[2] Zhejiang Key Lab Automobile Safety Technol, Hangzhou 310000, Zhejiang, Peoples R China
[3] BYD Auto Ind Co Ltd, Shenzhen 518000, Peoples R China
关键词
PARTICLE SWARM OPTIMIZATION; POWER MANAGEMENT; SYSTEM; BUS;
D O I
10.1155/2015/368769
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页数:11
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