Rule-based Online Energy Management Strategy for Power-Split Plug-in Hybrid Electric Vehicles

被引：0
|
作者：
Chen, Zheng [1 ]
Wu, Yitao [1 ]
Guo, Ningyuan [1 ]
Shen, Jiangwei [1 ]
Xiao, Renxin [1 ]
机构：
[1] Kunming Univ Sci & Technol, Fac Transportat Engn, Kunming 650500, Yunnan, Peoples R China
来源：
2018 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC) | 2018年
基金：
美国国家科学基金会; 国家重点研发计划;
关键词：
dynamic programming (DP); energy management; multi-mode; neural network; rule based algorithm; DESIGN;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, a rule-based online energy management strategy is proposed for a power-split plug-in hybrid electric vehicle (PHEV), i.e., Chevrolet Voltec. Dynamic programming (DP) is employed to find optimal solutions with respect to different road types and driving ranges, which are analyzed in detail in order that some significant characters can be extracted. Neural network (NN) is applied to train the solutions to achieve the online mode selection. In addition, some fitting-based rules for the battery power are directly extracted based on the DP solution. Compared with the typical charge depletion-charge sustaining (CD-CS) strategy, the proposed strategy can effectively reduce the total cost, of which the maximum saving reaches 10.29%.
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页数：6
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