Research On High Speed Trains Energy-saving Control Methods Based On Genetic Algorithm

The rapid development of High-Speed Train program in China is necessary and inevitable in the case of a large population and limited resources. However, the energy that consumed in railway transportation is very large, thus the research of energy-saving control methods is of great significance. Based on the train’s traction and braking characteristics as well as operating conditions, the energy consumption model of train travelling process is built. The control strategy of the train is optimized, combining with genetic algorithm. At last, the desired optimized velocity curve is obtained.The research content of this paper mainly includes the following three parts.First of all, the paper deeply studies the dynamics theory of train operation, establishes the train traction calculation model and analyzes calculation method of the train travelling process. On the basis of these, the train running energy consumption is analyzed, and the energy consumption calculation model is established. With the constraint conditions of the train dynamic model, the train operation optimization model is established.Secondly, this paper proposes a train energy-saving optimal control method based on genetic algorithm which combines the global optimization control with the coasting optimization control. In the process of the global optimization control, the train’s running line is divided into several discrete intervals according to the slope values. The energy consumption optimization model of the train is set up with the goal of minimum energy consumption under the constraint conditions which includes time, distance and comfort. The running speed sequence with the minimum energy consumption of the train is obtained through the improved genetic algorithm, with which the running speed curve of the train can be optimized. In the process of the coasting optimization control, based on the previous running speed curve, the energy consumption in the middle of the train operation stage will be reduced again, considering the characteristics of high speed train. The genetic algorithm is used again to search for the optimal locations of the key transition points, which further optimizes the train running speed curve under the condition of satisfying the upper and lower bounds of the velocity.Finally, the effectiveness of this control method is verified by MATLAB simulation software. Simulation Research on train operation optimization control is carried out with a section of data about Wuhan Guangzhou high-speed railway line and BeijingShanghai high-speed railway line. It is proved that the train has reached the goal of energy saving in satisfying various constraints. And the comparative analysis of the global optimization control and coasting optimization control is done.