Research on optimization of energy-saving operation speed of metro based on APSO

In the current research on energy-saving operation optimization of multi-station between urban rail trains, the traction energy consumption model does not consider the actual operating state, and is determined only by two indicators of train control force and running speed, and the fixed operation mode is widely adopted, which is difficult to dynamically adjust according to the actual environment. According to the actual running process of the train, this paper firstly studied the influence of running time and inter-station distance on the running energy consumption, analyzed the energy-saving operating conditions of the distance between the same station, studied the conversion sequence of working conditions, and then reconstructed the energy optimization model. Finally, the improved particle swarm optimization algorithm was used to solve the working condition transition point to realize the energy saving optimization of the train speed curve. The simulation results show that the contrast accuracy of the reconstructed energy optimization model and the traditional model is improved by 1.16%, and the optimized operating energy consumption is 6.92% lower than the original fixed driving strategy, which has better energy saving effect. © 2020, Central South University Press. All rights reserved.