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Strategies for handling the fuel additive problem in neural network based ion current interpretation
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0001-5163-2997
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-4143-2948
2001 (English)Conference paper, Published paper (Refereed)
Abstract [en]

With the introduction of unleaded gasoline, special fuel agents have appeared on the market for lubricating and cleaning the valve seats. These fuel agents often contain alkali metals that have a significant impact on the ion current signal, thus affecting strategies that use the ion current for engine control and diagnosis, e.g., for estimating the location of the pressure peak. This paper introduces a method for making neural network algorithms robust to expected disturbances in the input signal and demonstrates how well this method applies to the case of disturbances to the ion current signal due to fuel additives containing sodium. The performance of the neural estimators is compared to a Gaussian fit algorithm, which they outperform. It is also shown that using a fuel additive significantly improves the estimation of the location of the pressure peak. © 2001 Society of Automotive Engineers, Inc.

Place, publisher, year, edition, pages
Warrendale, PA: Society of Automotive Engineers, 2001. Vol. 110
Series
SAE2001 Transaction - Journal of Fuels and Lubricants ; 4
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:hh:diva-5019DOI: 10.4271/2001-01-0560Scopus ID: 2-s2.0-84877564795ISBN: 0-7680-1100-0 OAI: oai:DiVA.org:hh-5019DiVA, id: diva2:327095
Conference
SAE 2001 World Congress, Session: Electronic Engine Controls (Part C&D), Detroit, MI, USA, 5-8 March, 2001
Funder
Knowledge Foundation
Note

Paper no: 2001-01-0560. Funding: KK-foundation & Mecel AB

Available from: 2010-06-28 Created: 2010-06-28 Last updated: 2021-05-11Bibliographically approved
In thesis
1. Algorithms for ion current based sensing of combustion variability and pressure peak position
Open this publication in new window or tab >>Algorithms for ion current based sensing of combustion variability and pressure peak position
2003 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Göteborg: Chalmers tekniska högsk., 2003. p. 43
Series
Technical report. L, ISSN 1651-4998 ; 482
Keywords
SI engines, Combustion variability, Ion currents, Location of pressure peak, Exhaust Gas Recirculation, Electronic engine control
National Category
Control Engineering
Identifiers
urn:nbn:se:hh:diva-666 (URN)2082/1008 (Local ID)2082/1008 (Archive number)2082/1008 (OAI)
Presentation
2003-12-09, Wigforssalen, Visionen, Kristian IV:s väg 3, Halmstad, 10:00 (English)
Supervisors
Projects
SCALE (Self CALibrating Engine control)
Funder
Knowledge Foundation
Note

Funding: STEM (Swedish National Energy Administration), the KK-foundation & Mecel AB

Available from: 2007-05-07 Created: 2007-05-07 Last updated: 2018-03-23Bibliographically approved

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Byttner, StefanRögnvaldsson, ThorsteinnWickström, Nicholas

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CiteExportLink to record
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Citation style
  • apa
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Language
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More languages
Output format
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