Research And Simulation Validation Of Train Energy Saving Operation Optimization In Urban Rail Transit

With the rapid development of urban rail transit construction,the total length of urban rail transit in our country has been ranked first in the world.But the annual operation maintenance costs of urban rail transit are very high,especially the highest cost of power consumption,and the energy consumption of train traction accounted about 50%of the total consumption of power supply.So,the research on the train energy-saving optimization operation curve is of great significance.Aiming at the problem that the calculation speed of target speed curve of train energy-saving operation is slow and the new algorithm is difficult to be tested on real train directly,in order to calculate the train energy-saving optimization operation curve fast and establish a train energy-saving optimization simulation platform,the paper establishes a fast calculation model of "Simulink simulation and combinatorial algorithm",which can update the energy-saving optimization operation curve quickly.And the model is verified in the simulation platform.The research contents include the following aspects:1.The paper introduces the present research situation of train energy-saving optimization algorithm and analyzes the relevant principles of solving the optimization curve.2.The paper builds a vehicle driving model to simulate driver's operation using Simulink software package according to the principles of energy-saving driving.When the key operation type and transfer position is given,the model can calculate train running time and energy consumption value.3.Establishing a model to calculate train energy-saving operation curve,and the key operation type and transfer position is solution variable.The paper achieves calculating train minimum-time energy consumption and running time on the ideal conditions using VC++and realizes the fibonacci algorithm,pattern search algorithm and adaptive genetic algorithm to solve the optimization of energy curve.Aiming at the solving performance of the above algorithms,this paper presents a fast and efficient method for the train energy-saving operation curve by using a combination of off-line adaptive genetic algorithm and online pattern search algorithm and the results show that algorithm has a good effect.When the train is late in the case of abnormal,it can update the driving curve at the stop time rapidly and provide guidance for driver.4.Establishing a simulation verification platform of train operation optimization algorithm,it can solve the optimal operation curve according to the user's specific settings.The user can set simulation parameters,select control strategy and algorithm.At the same time,the paper analyzes using the same driving strategies and different algorithm compared with the same algorithm and different driving strategies,further validating the improvement effect of combinatorial algorithm.