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Road Roughness Etimation Using Available Vehicle Sensors
Linköping University, Department of Electrical Engineering.
2009 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Road conditions affect fuel efficiency and vehicle fatigue when driving heavy trucks. Information about traveled road conditions enable optimization of chassis configuration when driving, and logging of vehicle stress. Previous work on this topic focus mainly on tuning of active suspension parameters in the car industry. One conceivable application for heavy trucks is implementation of active chassis level control based on road conditions, with possible improvements in driving economy as result. Another is logging of usage conditions which helps explain vehicle faults caused by abnormal wear. This work examines the possibilities to use already on vehicle sensors for road roughness estimation. It also investigates what requirements existing signals must fulfill to ensure reliable estimates. Two methods for road roughness estimation are proposed using rear axle level sensor and a simple linear suspension system model.

Place, publisher, year, edition, pages
2009. , 55 p.
Keyword [en]
Heavy truck, Road Roughness
National Category
Vehicle Engineering Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-17876ISRN: LiTH-ISY-EX - - 09/4227 - - SEOAI: oai:DiVA.org:liu-17876DiVA: diva2:212816
Presentation
(English)
Uppsok
teknik
Supervisors
Examiners
Available from: 2009-04-28 Created: 2009-04-23 Last updated: 2009-04-28Bibliographically approved

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fulltext(2009 kB)1426 downloads
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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