Optimization Method of Train Electric Braking Control Based on Particle Swarm Algorithm

Due to the sudden change of gradient resistance and the asynchrony of front and rear braking, the heavy haul train will have a large longitudinal impulse when braking at the grade change point. In this paper, an optimization method of train electric braking control based on particle swarm optimization is proposed to reduce the longitudinal impulse of the train braking. The results show that the algorithm can realize the efficient optimization of the optimal electric braking control scheme. Compared with the conventional average distribution of electric braking force, the coupler force under the optimized electric braking control is reduced by 23.2% while the braking distance is only increased by 9.95 m.