Optimization of collision energy management for long series EMU based on machine learning
In order to effectively relieve the pressure of railway transportation,the passenger capacity can be increased doubly by adopting the reconnection operation of EMUs.However,once a collision accident occurs,the huge collision energy will cause serious occupant injury and property loss.Therefore,the research on collision energy management of long series EMU has become a focus object.In this paper,two modes of collision energy dissipation,namely concentrated dissipation and uniform dissipation,were proposed.With the platform force and compression stroke of the energy absorption device at the head and middle car ends as design parameters,the optimal design of collision energy management of long series EMU was carried out based on KNN,MLS,RBF and RF machine learning algorithms.The results show that MLS and RBF are the best machine learning models for predicting the energy absorption of the head car and the variance of energy absorption of the middle car,respectively,with relative errors within 4%.The platform force of the energy absorption element of the head car and the middle car is the main parameter affecting the energy absorption of the head car,and the parameters of the energy absorption device of the middle car are the main parameters that affect whether the energy distribution of middle vehicle is uniform.In the concentrated dissipation mode,48.24%of the collision energy is absorbed by the front car and the reconnection interfaces,and 51.76%of the collision energy is absorbed by the middle car,and this energy distribution mode requires higher energy absorption at the front end of the front car.In the uniform dissipation mode,only 22.75%of the collision energy is absorbed by the head and reconnection interfaces,while 77.25%is absorbed by the middle interfaces.This energy distribution mode will increase the distance between cars and lead to the increase of train length.This two optimized collision energy management modes can ensure the integrity of the car body structure of long series EMU under the collision condition of 36 km/h,and the maximum of 120 ms average acceleration of the car body is 2.64g and 2.36g respectively.
long series EMUcrash energy managementmulti-objective optimizationNSGA-Ⅱmachine learning
万方数据
维普
