Research On Automatic Driving Traction Control Strategy Of High-speed EMU

Due to its advantages of safety,speed and comfort,high-speed railway has been booming in China in recent years.At present,most of the EMUs running on China’s high-speed railways adopt the manual driving mode,the operation effect of the EMUs is too dependent on the driver’s operation experience and technology,improper or incorrect operation of the driver may cause the train to be delayed or even threaten the safety of the train.Therefore,in order to ensure the safety of the train operation better and improve the efficiency of high-speed railway transportation,people are committed to researching high-speed EMU automatic driving control strategy.Using the train automatic driving system instead of manual driving,selecting a reasonable traction control strategy to control the normal operation of the high-speed EMU,at the same time improving the performance indicators of the high-speed EMU,such as safety,comfort,energy saving,punctuality and precise parking,it is foreseeable that automatic driving of high-speed EMUs is the development direction of high-speed railways in the future.Studying the automatic driving control strategy of high-speed EMUs is mainly to optimize the target curve of the train running speed and track the target curve accurately.Aiming at the above problems,this thesis analyzes the automatic train control system(ATC)and Chinese train control system(CTCS),and introduces the structure,working principle and function of the ATC system,as well as the classification and overall structure of the CTCS system.On this basis,selecting the EMU models to be studied,seting the operating line parameters,calculating the traction,braking force and resistance during the train operation,and adopting integrated optimization control strategy to control automatic driving of the train,completing the multi-objective model of high-speed EMU with the performance indexes of comfort,energy-saving,punctuality and precise parking.According to the influence degree of each performance index on the operation process of high-speed EMU,the entropy weight method is used to allocate the weight of each performance index,and the fitness function is constructed,the genetic algorithm is used to optimize the multi-objective model,and the train running target curve is generated in combination with the train traction calculation knowledge in MATLAB.Then structure and working principle of the PID control,fuzzy control and neural network control are introduced,in the MATLAB environment,the high-speed EMU speed controller models based on PID control and fuzzy neural network control are established respectively,the target curve is tracked and controlled by the established speed controller,and finally the simulation tracking curve is generated.By comparing the target curve,the tracking curve based on PID control and the tracking curve based on fuzzy neural network control,it can be seen that the control effect of the speed controller based on fuzzy neural network control is more ideal than the speed controller based on PID control,it can meet the requirements of various performance indexes in the operation process of high-speed EMUs,furthermore,the feasibility of the fuzzy neural network control algorithm in the automatic driving control process of high-speed EMUs is verified.