Model Predictive Control Based Energy Management Strategy of Series Hybrid Electric Vehicles Considering Driving Pattern Recognition

被引:6
作者
Hao, Jinna [1 ]
Ruan, Shumin [2 ]
Wang, Wei [3 ]
机构
[1] Cent South Univ Forestry & Technol, Coll Comp & Informat Engn, Changsha 410004, Peoples R China
[2] Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China
[3] Dalian Univ Technol, Sch Informat & Commun Engn, Dalian 100081, Peoples R China
关键词
pattern recognition; condition prediction; model predictive control; energy management strategy; hybrid electric vehicles; POWER MANAGEMENT; ECMS;
D O I
10.3390/electronics12061418
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes an energy management strategy for a series hybrid electric vehicle based on driving pattern recognition, driving condition prediction, and model predictive control to improve the fuel consumption while maintain the state of charge of the battery. To further improve the computational efficiency, the discretization and linearization of the model is conducted, and the MPC problem is transferred into a quadratic programming problem, which can be solved by the interior point method effectively. The simulation is carried out by using Matlab/Simulink platform, and the simulation results verify the feasibility of the condition prediction method and the performance of the proposed method. In addition, the predictive control strategy successfully improves the fuel economy of the hybrid vehicle compared with the rule-based method.
引用
收藏
页数:17
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