Study On Energy Saving Control Of High Speed Train Based On Particle Swarm Optimization

In recent years,the rapid development of rail transit has played an increasingly important role in transportation.In terms of transportation,the development of railway transportation has always been in the core position.The prosperity of railway transportation industry has greatly promoted the economic development of our country and played an irreplaceable role in social progress.In this paper,based on the train parameters and the actual operation route,the train dynamics model is established,and the optimal operation strategy of the train is analyzed combining with energy consumption and time.The main research contents of this paper include the following parts:This paper studies and analyzes the train operation process,and uses the single mass point model to carry out a detailed analysis of the stress situation in the train operation process,so as to determine the motion equation of the train under different operation conditions.Based on the maximum principle,the Hamiltonian function corresponding to the minimum energy consumption is established and four train operation modes are obtained.The operation strategy of "maximum traction cruise coasting braking" is proposed as the optimal driving strategy of high-speed train.These four operation modes provide a theoretical basis for energy-saving optimization and coasting optimization of ramps in the subsequent operation of the whole train.Considering the regenerative braking feedback energy of the train,the energy consumption model of the train is established.A method based on particle swarm optimization(PSO)is used to optimize the ramp control and coasting control.In the first part,on the ramp optimization control of the whole line,the route is divided into different sub sections according to the method of equal ramp value.Through the improved particle swarm optimization algorithm,an optimal target speed is found for each section.When running according to the speed sequence,an energy-saving effect can be achieved,in the second part,on the basis of the whole line ramp optimization,the improved particle swarm optimization algorithm is used again to search the position of the switching point of train working condition,and further optimize the train running speed curve.Taking the CRH3 high-speed train as the research vehicle,this paper analyzes the data and speed limit of Jinan-Taian section.Matlab software is used to simulate the lines that are not optimized,the lines that are optimized for ramp operation and the lines that are optimized for coasting,compared with four stage operation strategy,the energy consumption of ramp optimization operation optimization method is relatively reduced by 4.3%,and the energy consumption of idle optimization line is relatively reduced by 10.06%,which has certain reference value for line optimization.