his.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
The effect of optimizing engine control on fuel consumption and roll amplitude in ocean-going vessels: An experimental study
University of Skövde, The Informatics Research Centre. University of Skövde, School of Informatics. (DRTS)ORCID iD: 0000-0002-5223-4381
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (DRTS)
2015 (English)Report (Other academic)
Abstract [en]

We use data-generated models based on data from experiments of an ocean-going vessel to study the effect of optimizing fuel consumption. The optimization is an add-on module to the existing diesel-engine fuel-injection control built by Q-TAGG R&D AB. The work is mainly a validation of knowledge-based models based on a priori knowledge from physics. The results from a simulation-based analysis of the predictive models built on data agree with the results based on knowledge-based models in a companion study. This indicates that the optimization algorithm saves fuel. We also address specific problems of adapting data to existing machine learning methods. It turns out that we can simplify the problem by ignoring the auto-correlative effects in the time series by employing low-pass filters and resampling techniques. Thereby we can use mature and robust classification techniques with less requirements on the data to demonstrate that fuel is saved compared to the full-fledged time series analysis techniques which are harder to use. The trade-off is the accuracy of the result, that is, it is hard to tell exactly how much fuel is saved. In essence, however, this process can be automated due to its simplicity. 

Place, publisher, year, edition, pages
Skövde, 2015. , 74 p.
National Category
Signal Processing Embedded Systems Computer Science Probability Theory and Statistics
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-10942OAI: oai:DiVA.org:his-10942DiVA: diva2:812353
Projects
“System för bränslebesparing på stora fartyg”, 2013-00301, Vinnova Forska & Väx 2013
Funder
VINNOVA, 2013-00301
Available from: 2015-05-18 Created: 2015-05-18 Last updated: 2015-05-19Bibliographically approved

Open Access in DiVA

fulltext(995 kB)767 downloads
File information
File name FULLTEXT01.pdfFile size 995 kBChecksum SHA-512
be868afb7c5b84308f6714494e862fa5ab334d5e9ccfa82c6ab4a8920f7400c8b1090e5610a097f4d040f39c859e7848c8e45a2d1e65499440b1fb30a878abf5
Type fulltextMimetype application/pdf
fulltext(11785 kB)90 downloads
File information
File name FULLTEXT02.zipFile size 11785 kBChecksum SHA-512
48e7c890c263b5cbe7e259fa824afeb79f66b3df748fd4b1ebaa78361e00a108692ca1592736ce70742d0ba77e129af5ecb865eb34ca32046ba84136ffbf2cff
Type fulltextMimetype application/zip

Search in DiVA

By author/editor
Mellin, JonasAndler, Sten F.
By organisation
The Informatics Research CentreSchool of Informatics
Signal ProcessingEmbedded SystemsComputer ScienceProbability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
Total: 857 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

Total: 1541 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