Study on ATO Braking Model Identification Based on Model Selection and Optimization Techniques

This paper studied system identification of the electric train braking model with the field data from the ATO(Automatic Train Operation) system in urban rail transit.Firstly,after analyzing the field data under the maximal braking current,some possible types of models are proposed.Then,nonlinear optimization techniques are used to identify the model parameters of different models with or without constrained conditions,and the best braking model and its parameters are obtained by the model selection technique and expert know-ledge.In the end,the consistence of train braking models under different braking rates are studied and the best model describing the relationship between the braking rate and deceleration is chosen by the model selection technique.