hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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
Self-organized Modeling for Vehicle Fleet Based Fault Detection
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent systems (IS-lab).ORCID iD: 0000-0001-5163-2997
Volvo Technology, 405 08 Göteborg, Sweden.
2008 (English)In: Proceedings of the SAE World Congress & Exhibition, Warrendale, PA: SAE Inc. , 2008Conference paper, Published paper (Refereed)
Abstract [en]

Operators of fleets of vehicles desire the best possible availability and usage of their vehicles. This means the preference is that maintenance of a vehicle is scheduled with as long intervals as possible. However, it is then important to be able to detect if a component in a specific vehicle is not functioning properly earlier than expected (due to e.g. manufacturing variations). This paper proposes a telematic based fault detection scheme for enabling fault detection for diagnostics by using a population of vehicles. The basic idea is that it is possible to create low-dimensional representations of a sub-system or component in a vehicle, where the representation (or model parameters) of a vehicle can be monitored for changes compared to the model parameters observed in a fleet of vehicles. If a model in a vehicle is found to deviate compared to a group of models from a fleet of vehicles, then the vehicle is judged to need diagnostics for that component (assuming the deviation in the model cannot be attributed to e.g. a different driver behavior). The representation should be low-dimensional so it is possible to have it transferred over a limited wireless communication channel to a communications center where the comparison is made. The algorithm is shown to be able to detect leakage on simulated data from a cooling system, work is currently in progress for detecting other types of faults.

Place, publisher, year, edition, pages
Warrendale, PA: SAE Inc. , 2008.
Series
SAE Technical Papers, ISSN 0148-7191 ; 2008-01-1297
Keywords [en]
Fleet operators, Vehicles
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-2057DOI: 10.4271/2008-01-1297Local ID: 2082/2452OAI: oai:DiVA.org:hh-2057DiVA, id: diva2:239275
Conference
SAE World Congress & Exhibition, April 2008, Detroit, Michigan, United States
Available from: 2008-10-17 Created: 2008-10-17 Last updated: 2018-03-23Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Byttner, StefanRögnvaldsson, ThorsteinnSvensson, Magnus

Search in DiVA

By author/editor
Byttner, StefanRögnvaldsson, ThorsteinnSvensson, Magnus
By organisation
Intelligent systems (IS-lab)
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 210 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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