Tang Licheng, T. Tao, Xun Jing, Suo Shuai, Liu Tong
{"title":"Optimization of train speed curve based on ATO tracking control strategy","authors":"Tang Licheng, T. Tao, Xun Jing, Suo Shuai, Liu Tong","doi":"10.1109/CAC.2017.8244082","DOIUrl":null,"url":null,"abstract":"How to reduce the energy consumption of urban rail transit system is always the focus of attention. The automatic train operation(ATO) system operates trains between successive stations by controlling the speed automatically, which is very important for the train energy saving operation. The traditional ATO recommended speed curve optimization research is based on line information, train information and control objectives to generate the optimal recommended speed curve, which does not take the influence ATO tracking control strategy taken on the practical driving strategy into account. In this paper, the recommended speed curve optimization and ATO tracking control strategy are considered together. On the basis of using the dynamic programming to optimize the recommended speed curve of the train, a method based on the existing ATO tracking control strategy for the recommended speed curve optimization is given. The method can effectively reduce the energy consumption under the condition that the running time is acceptable.","PeriodicalId":116872,"journal":{"name":"2017 Chinese Automation Congress (CAC)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Chinese Automation Congress (CAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAC.2017.8244082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
How to reduce the energy consumption of urban rail transit system is always the focus of attention. The automatic train operation(ATO) system operates trains between successive stations by controlling the speed automatically, which is very important for the train energy saving operation. The traditional ATO recommended speed curve optimization research is based on line information, train information and control objectives to generate the optimal recommended speed curve, which does not take the influence ATO tracking control strategy taken on the practical driving strategy into account. In this paper, the recommended speed curve optimization and ATO tracking control strategy are considered together. On the basis of using the dynamic programming to optimize the recommended speed curve of the train, a method based on the existing ATO tracking control strategy for the recommended speed curve optimization is given. The method can effectively reduce the energy consumption under the condition that the running time is acceptable.