Research on Operating Strategy Based on Particle Swarm Optimization for Heavy Haul Train on Long Down-Slope

Abstract

In this paper, aiming at the difficult problem that it is necessary to choose the braking and releasing opportunity rightly when heavy haul train is controlled by cyclic braking method on long down-slope, the running process and control requirements of heavy haul train are analyzed, and the intelligent operating strategy based on particle swarm optimization is proposed. Firstly, the dynamic model and the control requirement constraints are set up considering the line data and the train marshalling data, and the initial particle swarm which represents the conversion points of working condition is generated randomly. Then, with the goal of safety and minimizing running time, algorithm is designed for the operation of heavy haul train. Finally, the actual line data on long down-slope of ShuoHuang railway are selected to verify the algorithm and the optimal working condition sequence is obtained, and then the operating curve is generated. Analyzing the expectation and variance of the speed difference between the simulation operating curve and the actual operating curve, it is proved that the method is feasible.