期刊文献+

移动闭塞条件下基于双曲列控策略的发车间隔时间计算 被引量:2

Analysis and Calculation of Time Interval between Two Trains in Railway Station under Moving Automatic Block
下载PDF
导出
摘要 列车间隔时间关乎铁路行车安全和效率。对未来铁路移动闭塞系统发车间隔时间的科学计算进行探讨,引入了能够反映经验丰富司机驾车列车优化行为的基于双曲函数的列车行为控制模型;然后,讨论了列车分段运动方程和车站发车作业、进路解锁等环节,以及各种误差因素,并将它们与基于双曲函数的列车行为控制模型有机结合起来,建立了计算移动闭塞条件下车站发车间隔时间的数学模型,给出了两种不同情形的车站发车间隔时间计算方法,数值仿真试验验证了算法的有效性和可行性。对移动闭塞条件下车站发车环节的列车行为控制和行车组织有较大参考价值。 Train interval is closely related to the safety and efficiency of railway traffic. Discussions are made on the scientific calculation of the time interval of two successive trains departing the same station in the same direction under the future railway moving block system, and the train behavior control model based on the hyperbolic function is introduced to describe the optimal behavior of the train steering by the experienced driver. Then, we discuss the time-piecewise train motion equation, and the links such as station departure operation and the automatic unlocking of train route, as well as various error-caused factors, and combine them with the train control model based on the hyperbolic function, establish a mathematical model to calculate the time interval of two successive trains departing the same station in the same direction under moving block system, and present the algorithms of the departure interval of two successive trains under two different situations. Numerical simulations verify the effectiveness and feasibility of two algorithms. There are great reference values in train control and organization when the train(s) departing the station under moving block system.
作者 陈泽君 潘登 汪镭 梅萌 袁德强 CHEN Zejun;PAN Deng;WANG Lei;MEI Meng;YUAN Deqiang(School of Electronics and Information Engineering,Tongji University,Shanghai 201804;CRRC Changchun Railway Vehicles Co.Ltd.,Changchun 130062)
出处 《微型电脑应用》 2020年第1期1-6,共6页 Microcomputer Applications
基金 国家重点研发计划资助(2017YFB120110508) 科技部重点研发项目课题(2018YFF0300500-5)
关键词 移动闭塞系统 发车间隔时间 双曲函数 仿真优化 算法 Moving block system Train departing interval Hyperbolic function Simulation optimization Algorithms
  • 相关文献

参考文献8

二级参考文献57

共引文献41

同被引文献12

引证文献2

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部