Research On ATO Operation Strategy Of CBTC Urban Rail Train

With the gradual advancement of Chinese urbanization construction,the size of the urban population has expanded significantly,and urban rail transportation is facing tremendous pressure and tests.In order to meet the actual needs of people traveling,how to improve the operation efficiency of urban rail transit systems on the premise of ensuring driving safety has become a key research issue.The train automatic operation system(ATO system for short)is the core part of the train automatic control system,and its operation strategy has become the key to the research.In this thesis,the optimization design and simulation research on the operation strategy of the urban rail train ATO system are carried out.The main research contents are as follows:First,based on the analysis and review of the ATO system composition principles and related technologies,in view of the current situation of incomplete consideration of the performance indicators in the current urban rail train ATO operation strategy,the in-depth study of the force during the train operation process is carried out to construct the train operation process.The required mathematical model.By analyzing the characteristics of the ATO system and the running characteristics of the train during the whole process,the urban rail train operation strategy with two-tier structure system is proposed.Secondly,the PSO-ABC algorithm is proposed by combining the particle swarm optimization algorithm and the artificial bee colony algorithm with the idea of ? ? hybrid improvement.Then,the coding method,initial population and fitness function in the improved algorithm are designed.Through simulation experiments,the single-target and multi-target optimization performance indexes are compared and analyzed.The simulated multi-objective optimized train operating curve can make the indexes between the indexes Achieve a relatively optimal state.Then the research on the tracking control of the train operation target speed curve is carried out.Most of the existing tracking strategies use PID controllers.This method relies on complex parameter adjustments,and it is difficult to achieve the ideal train operation tracking control effect.In this paper,a train running tracking control algorithm based on terminal sliding mode control is designed.By introducing the parameter self-adaptive method,the self-adaptability of the train tracking target curve control strategy is enhanced,so that the adaptive terminal sliding mode train running control algorithm is designed.By comparing and analyzing the speed tracking control effect and displacement tracking control effect of the train,it is verified that the adaptive terminal sliding mode control strategy has better tracking effect.Finally,using MATLAB’s advantages in matrix calculation and C # language in visualization,through the Access database to store and manage vehicle information and line information,design system login registration,information loading settings,running curve generation block,and auxiliary decision management,etc.Features.The ATO operation strategy simulation system finally designed has certain reference significance and practical value,which is convenient for technicians to analyze the operation strategy more intuitively and efficiently.