典型文献
Predictive cruise control for heavy trucks based on slope information under cloud control system
文献摘要：
With the advantage of fast calculation and map resour-ces on cloud control system (CCS), cloud-based predictive cruise control (CPCC) for heavy trucks has great potential to improve energy efficiency, which is significant to achieve the goal of national carbon neutrality. However, most investigations focus on the on-board predictive cruise control (PCC) system, lack of research on CPCC architecture under CCS. Besides, the current PCC algorithms have the problems of a single control target and high computational complexity, which hinders the improvement of the control effect. In this paper, a layered archi-tecture based on CCS is proposed to effectively address the real-time computing of CPCC system and the deployment of its algo-rithm on vehicle-cloud. In addition, based on the dynamic pro-gramming principle and the proposed road point segmentation method (RPSM), a PCC algorithm is designed to optimize the speed and gear of heavy trucks with slope information. Simula-tion results show that the CPCC system can adaptively control vehicle driving through the slope prediction, with fuel-saving rate of 6.17％ in comparison with the constant cruise control. Also, compared with other similar algorithms, the PCC algorithm can make the engine operate more in the efficient zone by coopera-tively optimizing the gear and speed. Moreover, the RPSM algo-rithm can reconfigure the road in advance, with a 91％ roadpoint reduction rate, significantly reducing algorithm complexity. Therefore, this study has essential research significance for the economic driving of heavy trucks and the promotion of the CPCC system.
文献关键词：
中图分类号：
作者姓名：
LI Shuyan;WAN Keke;GAO Bolin;LI Rui;WANG Yue;LI Keqiang
作者机构：
College of Engineering,China Agricultural University,Beijing 100083,China;School of Vehicle and Mobility,Tsinghua University,Beijing 100084,China
文献出处：
引用格式：
[1]LI Shuyan;WAN Keke;GAO Bolin;LI Rui;WANG Yue;LI Keqiang-.Predictive cruise control for heavy trucks based on slope information under cloud control system)[J].系统工程与电子技术（英文版）,2022(04):812-826
A类：
resour,RPSM,roadpoint
B类：
Predictive,cruise,control,heavy,trucks,slope,information,under,cloud,system,With,advantage,fast,calculation,map,ces,CCS,predictive,CPCC,has,great,potential,energy,efficiency,which,achieve,goal,national,carbon,neutrality,However,most,investigations,focus,board,lack,research,architecture,Besides,current,algorithms,have,problems,single,target,high,computational,complexity,hinders,improvement,In,this,paper,layered,proposed,effectively,address,real,computing,deployment,its,vehicle,addition,dynamic,gramming,principle,segmentation,method,designed,optimize,speed,gear,Simula,results,show,that,adaptively,driving,through,prediction,fuel,saving,comparison,constant,Also,compared,other,similar,make,engine,operate,more,efficient,zone,by,coopera,optimizing,Moreover,reconfigure,advance,reduction,significantly,reducing,Therefore,study,essential,significance,economic,promotion
AB值：
0.472801
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机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
