Online Optimal Energy Distribution of Composite Power Vehicles Based on BP Neural Network Velocity Prediction

被引：6
|
作者：
Jiang, Qingjian [1 ,2 ]
Fu, Zhijun [3 ]
Hu, Qiang [4 ]
机构：
[1] Henan Inst Econ & Trade, Zhengzhou 450018, Peoples R China
[2] Int Joint Res Lab Agr Prod Traceabil Henan, Zhengzhou 450018, Peoples R China
[3] Zhengzhou Univ Light Ind, Coll Mech & Elect Engn, Zhengzhou 450002, Peoples R China
[4] Zhejiang Univ Technol, Coll Mech Engn, Hangzhou 310014, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2021年 / 2021卷
基金：
中国国家自然科学基金;
关键词：
MANAGEMENT STRATEGY; ELECTRIC VEHICLES; SPEED; RANGE; ECMS;
D O I：
10.1155/2021/2519569
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In this paper, an online optimal energy distribution method is proposed for composite power vehicles using BP neural network velocity prediction. Firstly, the predicted vehicle speed in the future period is obtained via the output of a BP neural network, where the current vehicle driving state and elapsed vehicle speed information is used as the input. Then, according to the predicted vehicle speed, an energy management method based on model predictive control is proposed, and online real-time power distribution is carried out through rolling optimization and feedback correction. Cosimulation results under urban drive cycle show that the proposed method can effectively improve the energy efficiency of composite power sources compared with the commonly used method with the assumption of prior known driving conditions.
引用
收藏
页数：10
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