Model Predictive Control Based Energy Management Strategy for a Plug-In Hybrid Electric Vehicle

被引：0

作者：

Zhang, Jieli ^{[1
]}

He, Hongwen ^{[1
]}

Wang, Ximing ^{[2
]}

机构：

[1] Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China

[2] Beihang Univ, Sch Transportat Sci & Engn, Beijing 100191, Peoples R China

来源：

PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING AND INTELLIGENT SYSTEMS (ICMEIS 2015) | 2015年 / 26卷

关键词：

model predictive control (MPC); plug-in hybrid electric vehicles (PHEVs); energy management strategy;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In this paper, the model predictive control (MPC) method is researched for energy management problem of plug-In hybrid electric vehicle (PHEV). Multi-step Markov prediction method is selected for the prediction. Dynamic programming (DP) is chosen to solve the optimization problem within the prediction horizon. Through the comparison of MPC result with the results of dynamic programming strategy and a rule-based strategy, it is certified that the control effect of MPC strategy is much better than the ruled-based strategy and close to the global optimal control under DP strategy.

引用

页码：875 / 879

页数：5

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