Research On Energy Saving Operation Of High-speed Train Based On Dual Optimization

High-speed railway has the characteristics of fast speed,strong transportation capacity,and promotes the coordinated development of urban and rural areas.In recent years,with the rapid development of the world economy,the construction of high-speed railways has become more rapid,but the amount of energy consumed is huge,according to incomplete statistics,China’s high-speed railways consume about 20 billion kilowatt-hours of electricity a year.In order to solve the problem of large energy consumption during high-speed train operation,the main contents of the thesis are as follows:Firstly,for elemental point in some of the ramp in frequent line train model to calculate the error of energy consumption problems,based on fully considering the high-speed train running lines of complex conditions,has established more than meet the constraints of time and speed particle train model,can be more accurate simulation of high-speed trains in change slope and curve points of additional resistance,and then calculate the more accurate the energy consumption and it lays a foundation for studying the optimization of energy saving operation of trains.Secondly,the existing optimization strategies to solve the problem of high-speed train operation energy consumption mainly perform global optimization,and do not use the line data and information during the entire train operation process,resulting in unsatisfactory optimization results.Taking the energy-saving operation of the train as the optimization goal,and taking the train speed curve as the research object,and optimizing it twice based on the genetic algorithm.After analyzing the principle of energy consumption of trains,in order to achieve the purpose of energy saving,on the premise of the train arriving at the station on time,the idle running condition is adopted as far as possible to find the position of the transition point of traction and idle running condition in the middle period of train operation,so as to further reduce the energy consumption.Thirdly,taking high-speed train energy-saving optimization as the research object,using genetic algorithm to solve the problem,and based on the research of adaptive genetic algorithm,combined with the characteristics of train operation,the genetic algorithm is improved,and the strategy of elite retention is used in the selection process.In the process of crossover and mutation,crossover adaptive operator and mutation adaptive operator are added respectively,and corresponding chromosomes are designed for the optimization of train energy saving.Then,the improved genetic algorithm was successfully applied to the study of energy-saving optimization of train running curve.The optimization results show that compared with the traditional genetic algorithm an d the adaptive genetic algorithm,the improved genetic algorithm is more effective in solving the energy-saving problem of high-speed trains.Finally,based on CRH3 series models to study the high-speed trains,collect hefei-bengbu speed and route information,using MATLAB simulation software on double speed curves before and after optimization of the simulation analysis,calculation and contrast train before and after the optimization of energy consumption and energy consumption reduced by15.53% after optimization,demonstrate the validity of the energy-saving strategy,and has good popularization value in the practical engineering application.