基于闭塞时间的中速磁浮线路通过能力分析OA

The medium-speed maglev transportation system has broad application prospects in the field of intercity and urban rail transit.However,the exact calculation problem of the transport capacity of maglev lines cannot be effectively solved by using the calculation methods of traditional wheel-rail systems.According to the actual needs of operation organizations,based on the technical characteristics of the medium-speed maglev system and integrating the constraint requirements of operation control and safety protection,the calculation method of transport capacity of medium-speed maglev lines was studied.Firstly,through an in-depth analysis of the rigid protection constraint of"one block partition for one running train"followed by medium-speed maglev trains,as well as the stop-point stepping control mechanism and quasi-moving block tracking protection mode adopted by the operation control system,the adaptability between the blocking time theory and the technical characteristics of the medium-speed maglev operation control system was demonstrated.On this basis,taking"blocking time theory and identification of the most unfavorable partition handover application point"as the core research paradigm,quantitative models of partition blocking time under four types of typical full-process operation scenarios,including interval operation,station arrival stop,platform departure,and station rear turn-back,were constructed,and an algorithm for solving transport capacity of lines based on time window compression was proposed.Finally,a specific line case was selected,and the validity of the output results of the proposed calculation models and algorithms was verified through a dual verification system combining simulation experiments and limit pressure tests.Simulation results indicate that the theoretical limit value of the transport capacity of the target line is 11 trains/h.If an extra running line is added,the running process of the following train is inevitably interfered by the preceding train.The proposed models and algorithms possess good calculation accuracy and engineering applicability.