Research On Multi-Objective Optimization Method Of Train ATO Based On CBTC

The train control system based on communication has become the development direction of the train operation control. The train automatic operation subsystem of CBTC system is the key equipment of train automatic operation.The train automatic operation control needs to achieve multiple performance indexes such as safety,punctuality,energy saving,comfortable,accurate stopping,but the ATO technology of CBTC products that a number suppliers offered are not reach this target. In present most of the studies about train automatic operation control are based on automatic blocking system,few studies about train ATO control are based on CBTC,and the studies did not take into consideration of overall indexes.For these reasons,this thesis study the efficient control method of ATO multi-objective optimization based on CBTC.This study is significant for improving the urban rail transit tains operating efficiency and reducing operating costs.First, this thesis analysis the operating environment and train speed control mode of CBTC,The function and control principle of ATO subsystems based on CBTC system is researched deeply,and built train ATO optimization control target model.The ATO multi-objective optimization model is built by the multi-objective optimization theory combined with the target model of ATO optimization control. The ATO multi-objective optimization model is solved by using genetic algorithm based on weighted objective and Pareto optimization algorithm, and the train running optimization conditions sequence and train optimized speed curve are created.Comparing and analysising two algorithms, Pareto optimization algorithm result is more optimized.Next,the ATO integrated intelligent controller is designed by the fuzzy control algorithms combined with predictive control algorithm,the controller can achieve efficiently tracking the ATO speed curve. Finally, this thesis verify the method by experiments. The simulation platform is established in Simulink and OpenTrack simulation environment,simulated on the simulation platform and vehicle testing on the actual subway lines,The train ATO multi-objective optimization method is verified correct and effective by experiments.