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Model predictive control for hybrid vehicle ecological driving using traffic signal and road slope information
K.Yu,J.Yang,D.Yamaguchi
0
(School of Electrical Engineering and Automation, Henan Polytechnic University)
摘要:
This paper presents development of a control system for ecological driving of a hybrid vehicle. Prediction using traffic signal and road slope information is considered to improve the fuel economy. It is assumed that the automobile receives traffic signal information from intelligent transportation systems (ITS). Model predictive control is used to calculate optimal vehicle control inputs using traffic signal and road slope information. The performance of the proposed method was analyzed through computer simulation results. Both the fuel economy and the driving profile are optimized using the proposed approach. It was observed that fuel economy was improved compared with driving of a typical human driving model.
关键词:  Ecological driving, model predictive control, intelligent transportation systems, traffic signal, optimal control
DOI:
Received:May 04, 2014Revised:January 03, 2015
基金项目:
Model predictive control for hybrid vehicle ecological driving using traffic signal and road slope information
K. Yu,J. Yang,D. Yamaguchi
(School of Electrical Engineering and Automation, Henan Polytechnic University;School of Information Science and Electrical Engineering, Kyushu University)
Abstract:
This paper presents development of a control system for ecological driving of a hybrid vehicle. Prediction using traffic signal and road slope information is considered to improve the fuel economy. It is assumed that the automobile receives traffic signal information from intelligent transportation systems (ITS). Model predictive control is used to calculate optimal vehicle control inputs using traffic signal and road slope information. The performance of the proposed method was analyzed through computer simulation results. Both the fuel economy and the driving profile are optimized using the proposed approach. It was observed that fuel economy was improved compared with driving of a typical human driving model.
Key words:  Ecological driving, model predictive control, intelligent transportation systems, traffic signal, optimal control