Study On The Energy-efficient Train Movement Using Intelligent Algorithms

Rail transport is an important part of the public transport system. Compared with other transport modes, the total energy consumption of rail transport is enormous. Adopting energy-saving operation measures can reduce operating costs under the premise of transport efficiency.Therefore, the study aboutthe rail transport energy-efficient manipulation has a practical significance.This paperutilizes the knowledge of train traction calculation on the basis of locomotive traction and braking characteristics, combining with the research of domestic and foreign scholars about theenergy-efficient train movement, especially the energy-saving operation principle and judgment, as well as the rail transit operation status in China, to design the train energy-saving operation control strategy betweentwo stations. The energy-saving control strategy is based on the train maximum acceleration traction control, and timely changinginto coasting in order to makefull use of the kinetic energy of a train and reduce the unnecessary brakingbetween stations. After the determination of control strategy, this paper gives full consideration oftrain punctuality and passengercomfort, using genetic algorithm and simulated annealing algorithm to simulate the process of train movement. This paper improves the encoding process of genetic algorithm, for which each population offspring is produced through selection, crossover and mutation, and makes the effective information in the parent inherited to the offspring to a greater degree so as to improve the evolution efficiency. In the simulated annealing algorithm, the new solution generated in each disturbance is selected, the historical optimal solutions produced in the calculation is recordedwhich are compared with the final solution in the end. The algorithmsare utilized to calculate the train costing points on the complex railway lines, and the simulated results are compared and analyzed.