Brake Modeling And Control Method Of High-speed Train Based On Levels Switching

Chinese high-speed railway is a beautiful business card representing our country in the world,and has made great achievements in world transportation.The braking system of the high-speed train is an important part to guarantee the stability,safety and punctuality of the train.Along with the high-speed train operation speed continuously improve,to ensure the security of train running,the more stringent requirements on the braking system is put forward.Meanwhile,the high-speed train braking operation is still based on artificial control,and difficult to improve the technical specifications of the train operation,so set up the appropriate high-speed train braking model and design efficient operation control strategy is of great significance to train the intelligent driving.In this paper,the level model of train braking process is established from the aspects of the train's performance,level characteristics and actual braking conditions,and the adaptive control strategy based on Stochastic Configure Networks(SCN)is adopted to realize the switching between the level of a model and the tracking control of target speed.Specific studies are as follows:1.For the establishment of the train model under the braking condition,the level model in the braking process is divided into two parts: the level characteristic model of the train and the time-delay characteristics and dynamic characteristic model.In view of the characteristics of brake level characteristics,a mathematical model about level is built.According to the actual braking situation of the train,the dynamic process model of the train is set up.The least squares algorithm and the improved particle swarm algorithm are used to identify the parameters of the two parts.Finally,the relationship between the two models is combined to obtain the level model of the braking condition of the high-speed train.2.Based on the characteristics of the established high-speed train level model in braking process,it is necessary to realize the switching between the level models,but also meet the accuracy requirement of speed tracking control.Therefore,this article adoptes a kind of strategy-model reference adaptive control based on SCNs.Through the level switching strategy,the complicated calculation and analysis in the conventional model switching method can be avoided,at the same time,a stable reference model is used to describe the velocity target curve to be tracked,and combined with the advantage of neural network,the speed tracking accuracy of the train can be greatly improved.3.Based on the data of the actual operation of CRH380 A train and the data of brake level curve,the established model and control strategy in this paper are simulated and verified.The results show that the braking level model established in this paper,satisfies the requirement of modeling accuracy,and the adaptive control strategy based on SCN can realize high-precision tracking control of braking speed and level model is convenient to switch.Meanwhile,in order to highlight the advantages of the control method of this paper in speed tracking,so compared with the Fuzzy-PID control algorithm.finally,the experimental results prove the superiority of the control method in this paper.