Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
Development and Evaluation of Model-Based Misfire Detection Algorithm
Linköping University, Department of Electrical Engineering, Vehicular Systems.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This report present the work to develop a misfire detection algorithm for onboard

diagnostics on a spark ignited combustion engine. The work is based on

a previous developed model-based detection algorithm, created to meet more

stringent future legislation and reduce the cost of calibration. In the existing approach

a simplified engine model is used to estimate the torque from the flywheel

angular velocity, and the algorithm can detect misfires in various conditions.

The main contribution in this work, is further development of the misfire detection

algorithm with focus on improving the handling of disturbances and variations

between different vehicles. The resulting detection algorithm can be automatically

calibrated with training data and manage disturbances such as manufacturing

errors on the flywheel and torsional vibrations in the crankshaft occurring

after a misfire. Furthermore a robustness analysis with different engine

configurations is carried out, and the algorithm is evaluated with the Kullback-

Leibler divergence correlated to the diagnosis requirements.

In the validation, data from vehicles with four cylinder engines are used and the

algorithm show good performance with few false alarms and missed detections.

Place, publisher, year, edition, pages
2014. , 56 p.
Keyword [en]
Model-Based, Misfire, Detection, Diagnosis, Kullback-Leibler, SVM
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-112127ISRN: LiTH-ISY-EX--14/4807--SEOAI: oai:DiVA.org:liu-112127DiVA: diva2:763644
External cooperation
Volvo Cars
Subject / course
Vehicular Systems
Supervisors
Examiners
Available from: 2014-11-17 Created: 2014-11-16 Last updated: 2014-11-17Bibliographically approved

Open Access in DiVA

fulltext(4235 kB)150 downloads
File information
File name FULLTEXT01.pdfFile size 4235 kBChecksum SHA-512
c152a5d0df088ecbc2b289c4f77b7444bb497a5f7e85fca8c8966b93cb46164e8353d4caa4dfc54d99cd92c500925de9bb272800ce9ed190d6befe2cd85a75b8
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Therén, Linus
By organisation
Vehicular Systems
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 150 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: 249 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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