Research On Multi-objective Optimization Of High-speed Train Tracking Operation Based On Particle Swarm Optimization

At present,China's high-speed rail is in a period of rapid development.In order to meet the growing demand of passenger and freight development,the speed and density of trains are increasing.Therefore,how to ensure the safe,energy-saving,punctual and efficient operation of the train becomes one of the most urgent research directions in the development of high-speed railway.The main contents of this paper are as follows:(1)In this thesis,the multi-objective optimization problem is deeply analyzed.In its solution method,according to the characteristics of particle swarm optimization algorithm,such as fast convergence speed,simple and easy implementation,and being suitable for solving the multi-objective optimization problem in a short period of time,the improved PSO algorithm is proposed to study the multi-objective optimization problem of multi train tracking operation,and its specific flow is designed.In order to avoid the algorithm falling into the local optimum,the dynamic inertia weight and disturbance operator are used to improve the global convergence performance of the algorithm,and the improved effect is verified by simulation experiments.(2)In this thesis,the train dynamics model of single mass point is established by analyzing the operation process of high-speed train,and the calculation method of train traction,braking force and running resistance used in this thesis is given.Then,it is proved that there is an optimal solution in the optimization of train operation,and the calculation model of high-speed train running in each section is established.Finally,the calculation method of energy consumption,running time and comfort performance index is designed.(3)Finally,the multi-objective optimization problem of high-speed train tracking operation under moving block is studied.According to the calculation model of the minimum tracking interval of the train,the dynamic security constraints of the tracking operation are considered,and the utilization of the track operation is also considered by the dynamic security constraints.On this basis,the multi-objective optimization model of high-speed train tracking operation is established,and the dynamic security constraints and operation efficiency are considered by introducing the concept of dynamic operator into the improved multi-objective particle swarm optimization algorithm,and the specific steps of the improved multi-objective particle swarm optimization algorithm with dynamic operator are designed.Based on the CRH3 EMU and the real line information of Beijing Shanghai high speed railway,the simulation optimization is carried out.Through the comparison and analysis of the performance indicators before and after the optimization,it is proved that the algorithm can effectively improve the performance indicators of energy saving,punctuality,comfort and efficiency of high-speed trains on the basis of ensuring the safety of multi train tracking operation,which verifies the effectiveness of the algorithm.