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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/27371

Title: Contact force estimation in the wheel/rail interface for curving scenarios through regions of reduced adhesion
Authors: Hubbard, Peter D.
Farhat, Nabilah
Ward, Christopher P.
Amarantidis, G.A.
Keywords: Rail
Low adhesion
Wheel/rail contact
Kalman filtering
Issue Date: 2017
Publisher: © Elsevier
Citation: HUBBARD, P.D. ...et al., 2017. Contact force estimation in the wheel/rail interface for curving scenarios through regions of reduced adhesion. Mechatronics, In Press.
Abstract: © 2017. Regions of extreme low-adhesion between the wheel and rail can cause critical problems in traction and braking. This can manifest in operational issues such as signals being passed at danger, or pessimistic network wide responses to mitigate for localised issues. Poor traction conditions can be caused by oil contaminants, rain, ice, condensation of water droplets (micro-wetting) or leaves on the line, where compressed leaf contamination can cause a rapid decrease in adhesion. The complexity of the problem arises as a result of the inability to directly measure and monitor all the factors involved. There remains a lack of real-time information regarding the state and location of low-adhesion areas across rail networks. On-board low adhesion detection technology installed to in-service vehicles is a suggested method to capture up-to-date adhesion information network wide and minimise significant disruptions and cancellations in railway schedules. This paper extends a principle of a model-based estimation technique previously developed in straight track running for operating in a curving scenario. The vehicle model of focus here will be a high-fidelity, multi-body physics representation of a full-vehicle.
Description: This paper is in closed access until 4th Aug 2018.
Version: Accepted for publication
DOI: 10.1016/j.mechatronics.2017.06.013
URI: https://dspace.lboro.ac.uk/2134/27371
Publisher Link: https://doi.org/10.1016/j.mechatronics.2017.06.013
ISSN: 0957-4158
Appears in Collections:Closed Access (Mechanical, Electrical and Manufacturing Engineering)

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