engleski

A fuzzy logic-based classifier for railway track condition estimation and tractive effort conditioning using data from remote sensors

This paper presents the use of track condition data for predictive traction control of a diesel-electric locomotive-driven freight train using the data collected from the virtual remote wireless sensor network within a simulation model comprising wheel vs. track friction coefficient dependent on ambient temperature and relative humidity. The simulation model also includes the point-mass model of freight train longitudinal motion dynamics and the model of real-time information collection about railway track conditions based on a narrow-band wireless remote sensor network and its exchange with the virtual train driver. Simulations are carried out to assess the usage of remote wireless sensor data to avoid freight train slippage events through velocity target adjustment using track condition estimation, thus improving the quality of traction control and improving transportation safety.

Remote sensor networks ; weather conditions ; mountainous rail route ; transportation safety ; slippage mitigation ; advanced transportation technologies ; simulation

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