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

Autori
Pavković, Danijel ; Cipek, Mihael ; Kljaić, Zdenko ; Mlinarić, Tomislav Josip

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of XXIV International Conference on Material Handling, Constructions and Logistics – MHCL ’22 / Zrnić, Nenad ; Kartnig, Georg ; Bošnjak, Srđan - Beograd : Univerzitet u Beogradu, 2022, 121-126

ISBN
978-86-6060-134-8

Skup
XXIV International Conference on Material Handling, Constructions and Logistics - MHCL

Mjesto i datum
Beograd, Srbija, 21.09.2022. - 23.09.2022

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

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

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Strojarstvo, Tehnologija prometa i transport

POVEZANOST RADA