典型文献
Prediction of Commuter Vehicle Demand Torque Based on Historical Speed Information
文献摘要：
The development of vehicle-to-everything and cloud computing has brought new oppor-tunities and challenges to the automobile industry. In this paper, a commuter vehicle demand torque prediction method based on historical vehicle speed information is proposed, which uses machine learning to predict and analyze vehicle demand torque. Firstly, the big data of vehicle driving is collected, and the driving data is cleaned and features extracted based on road informa-tion. Then, the vehicle longitudinal driving dynamics model is established. Next, the vehicle simula-tion simulator is established based on the longitudinal driving dynamics model of the vehicle, and the driving torque of the vehicle is obtained. Finally, the travel is divided into several acceleration-cruise-deceleration road pairs for analysis, and the vehicle demand torque is predicted by BP neu-ral network and Gaussian process regression.
文献关键词：
中图分类号：
作者姓名：
Shiji Sun;Mingxin Kang;Yuzhe Li
作者机构：
State Key Laboratory of Synthetical Automation for Process Industries,Northeastern University,Shenyang 110819,China
文献出处：
引用格式：
[1]Shiji Sun;Mingxin Kang;Yuzhe Li-.Prediction of Commuter Vehicle Demand Torque Based on Historical Speed Information)[J].北京理工大学学报（英文版）,2022(04):362-370
A类：
Commuter,commuter
B类：
Prediction,Vehicle,Demand,Torque,Based,Historical,Speed,Information,development,vehicle,everything,cloud,computing,has,brought,new,oppor,tunities,challenges,automobile,industry,this,paper,demand,torque,prediction,method,historical,speed,information,proposed,which,uses,machine,learning,analyze,Firstly,big,data,driving,collected,cleaned,features,extracted,road,Then,longitudinal,dynamics,model,established,Next,simulator,obtained,Finally,travel,divided,into,several,acceleration,cruise,deceleration,pairs,analysis,predicted,by,neu,network,Gaussian,process,regression
AB值：
0.553607
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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。
