liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Online Identification of Running Resistance and Available Adhesion of Trains
Linköping University, Department of Electrical Engineering, Vehicular Systems.
Linköping University, Department of Electrical Engineering, Vehicular Systems.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Online identifiering av tågs gångmotstånd och tillgänglig adhesion (Swedish)
Abstract [en]

Two important physical aspects that determine the performance of a running train are the total running resistance that acts on the whole train moving forward, and the available adhesion (utilizable wheel-rail-friction) for propulsion and breaking. Using the measured and available signals, online identification of the current running resistance and available adhesion and also prediction of future values for a distance ahead of the train, is desired. With the aim to enhance the precision of those calculations, this thesis investigates the potential of online identification and prediction utilizing the Extended Kalman Filter.

The conclusions are that problems with observability and sensitivity arise, which result in a need for sophisticated methods to numerically derive the acceleration from the velocity signal. The smoothing spline approximation is shown to provide the best results for this numerical differentiation. Sensitivity and its need for high accuracy, especially in the acceleration signal, results in a demand of higher sample frequency. A desire for other profound ways of collecting further information, or to enhance the models, arises with possibilities of future work in the field.

Abstract [sv]

Två viktiga fysikaliska aspekter som bestämmer prestandan för ett tåg i drift är det totala gångmotståndet som verkar på hela tåget, samt den tillgängliga adhesionen (användbara hjul-räl-friktionen) för framdrivning och bromsning. Från de tillgängliga signalerna önskas identifiering, samt prediktering, av dessa två storheter, under drift. Med målet att förbättra precisionen av dessa skattningar undersöker detta examensarbete potentialen av skattning och prediktering av gångmotstånd och adhesion med hjälp av Extended KalmanFiltering.

Slutsatsen är att problem med observerbarhet och känslighet uppstår, vilket resulterar i ett behov av sofistikerade metoder att numeriskt beräkna acceleration från en hastighetssignal. Metoden smoothing spline approximation visar sig ge de bästa resultaten för denna numeriska derivering. Känsligheten och dess medförda krav på hög precision, speciellt på accelerationssignalen, resulterar i ett behov av högre samplingsfrekvens. Ett behov av andra adekvata metoder att tillföra ytterligare information, eller att förbättra modellerna, ger upphov till möjliga framtida utredningar inom området.

Place, publisher, year, edition, pages
2011. , 123 p.
Keyword [en]
running resistance, extended kalman filter, ekf, parameter estimation, acceleration estimation, adaptive models, adhesion, freight trains, numerical differentiation
Keyword [sv]
gångmotstånd, extended kalman filter, ekf, parameterskattning, accelerationsskattning, adaptiva modeller, adhesion, godståg, numerisk derivering
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-71301ISRN: LiTH-ISY-EX--11/4317--SEOAI: oai:DiVA.org:liu-71301DiVA: diva2:447122
Subject / course
Vehicular Systems
Uppsok
Technology
Supervisors
Examiners
Available from: 2011-10-12 Created: 2011-10-10 Last updated: 2011-10-12Bibliographically approved

Open Access in DiVA

Ahlberg, Blomquist - Online Identification of Running Resistance and Available Adhesion of Trains(3934 kB)3467 downloads
File information
File name FULLTEXT01.pdfFile size 3934 kBChecksum SHA-512
f1396406c5a87b48f8bb64439e4541f6a19e3a399322014f595f0b5df1645e5cb0172b5063e079eb041da8fb71af2a5641c6df535314c4a5fa4f9caa1fc6f48a
Type fulltextMimetype application/pdf

By organisation
Vehicular Systems
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 3467 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 590 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf