Real-time implementation of a traction control algorithm on a scaled roller rig
Traction control is a very important aspect in railway vehicle dynamics. Its optimisation allows improvement of the performance of a locomotive by working close to the limit of adhesion. On the other hand, in case the adhesion limit is surpassed, the wheels are subjected to heavy wear and there is also a big risk that vibrations in the traction occur. Similar considerations can be made in the case of braking. The development and optimisation of a traction/braking control algorithm is a complex activity, because it is usually performed on a real vehicle on the track, where many uncertainties are present due to environmental conditions and vehicle characteristics. This work shows the use of a scaled roller rig to develop and optimise a traction control algorithm on a single wheelset. Measurements performed on the wheelset are used to estimate the optimal adhesion forces by means of a wheel/rail contact algorithm executed in real time. This allows application of the optimal adhesion force.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00423114
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Supplemental Notes:
- Abstract reprinted with permission from Taylor & Francis.
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Authors:
- Bosso, N
- Zampieri, N
- Publication Date: 2013-4
Language
- English
Media Info
- Media Type: Print
- Features: Figures; Photos; References; Tables;
- Pagination: pp 517-541
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Serial:
- Vehicle System Dynamics
- Volume: 51
- Issue Number: 4
- Publisher: Taylor & Francis
- ISSN: 0042-3114
- EISSN: 1744-5159
- Serial URL: https://www.tandfonline.com/toc/nvsd20/current
Subject/Index Terms
- TRT Terms: Braking; Locomotives; Performance tests; Real time data processing; Rolling contact; Scale models; Traction control; Vehicle dynamics; Wheelsets (Railroads)
- Uncontrolled Terms: Roller rigs
- Subject Areas: Railroads; Vehicles and Equipment; I91: Vehicle Design and Safety;
Filing Info
- Accession Number: 01488039
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 24 2013 4:49PM