Engine-Map-Based Predictive Fuel-Efficient Control Strategies for a Group of Connected Vehicles

作     者：Lihong Qiu Lijun Qian Zoleikha Abdollahi Zhouwei Kong Pierluigi Pisu 

作者机构：Changan Intelligent Vehicle R&D InstituteChongqing 401120China Department of Vehicle EngineeringHefei University of TechnologyHefei 230009China International Center for Automotive ResearchClemson UniversityGreenville 29607USA 

出 版 物：《Automotive Innovation》 (汽车创新工程（英文）)

年 卷 期：2018年第1卷第4期

页      面：311-319页

核心收录：

学科分类：082304[工学-载运工具运用工程] 08[工学] 080204[工学-车辆工程] 0802[工学-机械工程] 0823[工学-交通运输工程] 

基　　金：the National Hi-Tech Research and Development Program of China(“863”Project)(Grant No.2015BAG17B04) National Natural Science Foundation of China(Grant No.51875149) China Scholarship Council(Grant No.201506690009)and U.S.Department of Energy GATE program 

主　　题：Model predictive control Connected vehicles Fuel-efficient control Engine map Intelligent transportation system 

摘      要：An engine-map-based predictive fuel-efficient control strategy for a group of connected vehicles is presented. A decentralizedmodel predictive control framework is formulated to predict the optimal velocity profile that compromises fuel economy andmobility while guaranteeing the safety of each vehicle. In the model predictive control framework, an engine-map-based fuelconsumption model is established by implementing a backward conventional vehicle model in the cost function. Moreover,the cost function is normalized by dividing each term by its reference value. An extra cost is added to the safety term when thedistance between adjacent vehicles drops to a critical value to guarantee vehicle safety, while another extra cost is consideredfor the velocity tracking term to prevent the violation of traffic rules. The results of simulation show the effectiveness of theproposed control method.