Assessment of railway train energy efficiency and safety using real-time track condition information

Abstract

This paper presents the use of track condition data from the virtual remote wireless sensor network within a simulation model of a battery-hybrid diesel-electric locomotive-driven freight train for a realistic mountain railway route simulation scenario. Simulation model includes the point-mass model of freight train longitudinal motion dynamics subject to wheel-to-track adhesion and head wind variations, the model of hybrid diesel-electric locomotive energy efficiency, and the model of real-time information provide to the virtual train driver about railway track conditions based on a narrow-band wireless remote sensor network. Simulation results are used to assess the possible benefits remote wireless sensor data for freight train energy-optimal control and to increase the transportation safety, including prediction of possible delays due to changed weather conditions en route.