Assessment of Railway Train Energy Efficiency and Safety Using Real-time Track Condition Information
| Autor: | Mihael Cipek, Tomislav Josip Mlinarić, Zdenko Kljaić, Danijel Pavković |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
wireless networks
lcsh:T Renewable Energy Sustainability and the Environment Computer science Wireless network Weather conditions Wireless networks Hybrid electric locomotive Mountain rail route Modelling Energy efficiency Transportation safety Advanced transportation technologies Energy Engineering and Power Technology mountain rail route Environmental Science (miscellaneous) Track (rail transport) lcsh:Technology transportation safety lcsh:HD72-88 Automotive engineering weather conditions lcsh:Economic growth development planning modelling hybrid electric locomotive Weather conditions wireless networks hybrid electric locomotive mountain rail route modelling energy efficiency transportation safety advanced transportation technologies advanced transportation technologies energy efficiency Water Science and Technology Efficient energy use |
| Zdroj: | Journal of Sustainable Development of Energy, Water and Environment Systems Volume 9 Issue 2 Journal of Sustainable Development of Energy, Water and Environment Systems, Vol 9, Iss 2, Pp 1-20 (2021) |
| ISSN: | 1848-9257 |
| DOI: | 10.13044/j.sdewes.d8.0352 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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