Predictive Ecological Control: Using Road Terrain and Traffic Signal Information for Improving Vehicle Energy Efficiency

被引：1

作者：

Li, Bingbing ^{[1
]}

Zhuang, Weichao ^{[1
]}

Chen, Nan ^{[1
]}

机构：

[1] Southeast Univ, Sch Mech Engn, Nanjing, Peoples R China

来源：

2019 3RD CONFERENCE ON VEHICLE CONTROL AND INTELLIGENCE (CVCI) | 2019年

关键词：

Electric vehicle; dynamic programming; eco-driving; road terrain; traffic signal; energy consumption; HYBRID; OPTIMIZATION;

D O I：

10.1109/cvci47823.2019.8951544

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a predictive ecological control (PEC) strategy to improve the energy efficiency of electric vehicle (EV) which approaches to an intersection with traffic light. By using the traffic signal information, the range of average cruising speed which avoids stopping is determined. Within the vehicle speed range, the cruising velocity is optimized by dynamic programming to reduce the energy loss while driving on highway with varying slops. Three case studies, cruising without information, with signal information and PEC are simulated. The results indicate the significant energy efficiency improvement of PEC and its potential impact on trip time.

引用

页码：207 / 212

页数：6

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