Evaluation of energy efficiency of train motion schedules based on modeling by nonlinear regression and neural network methods

The article deals with the modeling of the electric rolling stock and traction power supply system with the aim of solving the problem of reducing the electric power consumption for the traction of trains in the conditions of changing the schedule of freight trains. Simulation modeling is performed for the conditions of changing the mass of the train and the load on the axis. The description of the results obtained is based on regression models, the order of application of models in practice is given.