Estimating the benefits of energy-efficient train driving strategies: a model calibration with real data

This paper describes the first results of a research project where the main focus is to implement a Decision Support System (DSS) to optimise energy consumption of rail systems. In order to achieve this objective, we implement an optimisation module for the design of energy-efficient driving strategies, in terms of speed profiles, that requires a railway simulation model as a subroutine. Here we focus on the general framework of the optimisation module and on the calibration of the railway simulation model .All elaborations are implemented in a MatLab environment, aiming at defining possible energy-efficient speed profiles, in accordance with energy-saving strategies, through optimised speed profile parameters, in terms of acceleration, target speed, deceleration, coasting phase, and driving behaviour, represented by the jerk. The model is calibrated on real data recorded on a double track section of a railway line in the city of Naples (Italy). Initial results show that consumption is very variable with the speed profile and with driver behaviour, but the model is able to reproduce the average consumption of each driving strategy and should be able, within the DSS, to suggest the best driving strategies for each rail section.