Speed Adjustment Of Automatic Train Operation Systems Based On Unit-displacement Multi-particle Model

Transportation among cities is growing quickly with the rapid development of economy; high-speed railway has become the inevitable trend in the railway development of the world. As a mean of safe and reliable, fast and comfortable, and high loading with low energy consumption, high-speed railway has become an important part in transportation system, and plays an important role in national economy. Automatic Train Operation (ATO) system is one of the most important parts in automatic control system of high speed trains, as the nerve center in Automatic Train Control (ATC) system. The main function of ATO system is the speed adjustment according to the given distance-to-go curve, in that way the train can precisely track the given speed and distance, also the control effect such as efficiency and safety during the whole route could be improved. ATO system provides an effective guarantee for the operation quality of the train. Nowadays, ATO system has been widely used in urban railway transportation, and achieved excellent control effect. As a traditional operation way, manual driving has not met the requirement of train control demands on increasing the speed of the train. This paper focuses on the theory research on ATO system of high-speed railways. Main works are as follows:Firstly the basic structure, functions and performance index of ATO system has been introduced in detail, and the important role of ATO system in speed adjustment is also described. Speed calculations on different running conditions are provide through analysis the different forces of the train.Secondly, two typical models of the train are introduced as the single-particle model and multi-particles model. A unit-displacement multi-particle model is therefore established as the essential research of the train operation systems in this paper.Thirdly, the speed adjustment of ATO system with multiple working conditions based on fuzzy control algorithm is investigated. The performance of ATO systems on different ratio factors which decided by fuzzy rules is studied. Three simulation researches are analyzed as the distance-to-go tracking simulation, the two trains'speed tracking simulation and the accurate automatic stop simulation. The result is illustrated to be efficient through establishing the control model in MATLAB/SIMULINK.Finally, based on adaptive fuzzy algorithms ATO speed adjust systems with unit-displacement multi-particle model are designed. Better control effect and higher controlling accuracy are shown though the simulation.