Research On Optimization Model And Algorithm For Energy-saving Operation Of High-speed Train

High-speed train has gained more and more attention because of its safety,comfort and convenience.While driving economic growth,high-speed train has also generated huge energy consumption.Therefore,high-speed train energy-saving optimization is an important research topic to realize the sustainable development of high-speed railway.The energy consumption of train in the course of running mainly plays an important role in accelerating traction and overcoming various kinds of resistance,the running energy consumption is different due to different operation strategy,which reflect on the train speed distance curve at the same time.This paper based on the train traction / braking characteristics and line conditions,a practical train energy consumption model is established and the train operation strategy is optimized with genetic algorithm.The optimized speed distance curve is obtained by computer simulation.It is mainly studied from the following four aspects:(1)Based on the single point model of high-speed train traction calculation,the force situation during train operation is analyzed in detail to determine the operating conditions and dynamic equations.(2)On the basis of analyzing two macroscopic operation modes of high-speed train,the regenerative braking feedback energy is fully considered.The energy consumption models which meet the constraints of both the on-time arrival station and the line are established,and the result shows that the train operation mode with " traction-uniform-coasting-braking " has better energy saving effect.(3)Based on the operation mode of " traction-uniform-coasting-braking ",the line ramp factors and train condition changes are fully considered.A two-stage energy saving optimization strategy for high speed trains is proposed,which includes ramp operation optimization and whole coasting optimization.In the first stage,the line is discretized into different subsections according to the value of equal slope,and the optimal target speed is searched for each subinterval by genetic algorithm,along which the train can save energy.In the second stage,based on the ramp operation optimization,genetic algorithm is used again to search in the middle stage of train operation to determine the position and the corresponding speed of the transition point of "traction-coasting" working condition,to reduce energy consumption again,and to optimize the train speed distance curve.(4)Taking the CRH3 high-speed train as the research vehicle,based on the line data and speed limit condition of Jinan-Tai'an,the simulation results after two-stage optimization are compared with the simulation results before optimization by using MATLAB simulation software,achieving an energy-saving effect of 11.63%.This verifies the reliability of the strategy proposed in this paper in the optimization of train energy saving,and at the same time,ensures the safety of train operation.In this paper,a two-stage energy-saving optimization strategy is proposed from the point of view of optimizing the speed distance curve of high-speed train by using the method of energy consumption modeling,algorithm solving and example simulation.The feasibility and effectiveness of the optimization strategy are verified by example simulation.It has certain theoretical and practical significance for the optimal control of train energy saving.