Estimation of the COVIMEP Variation in a HCCI Engine

dc.authoridYILMAZ, Emre / 0000-0002-5653-2079
dc.authoridSolmaz, Hamit / 0000-0003-0689-6824
dc.authorwosidYILMAZ, Emre / AAA-7073-2020
dc.authorwosidSolmaz, Hamit / D-3070-2018
dc.contributor.authorPolat, Seyfi
dc.contributor.authorSolmaz, Hamit
dc.contributor.authorCalam, Alper
dc.contributor.authorYilmaz, Emre
dc.date.accessioned2021-11-01T15:05:05Z
dc.date.available2021-11-01T15:05:05Z
dc.date.issued2020
dc.department[Belirlenecek]
dc.description.abstractIn this study, variation of the COVIMEP was tried to be predicted by using the artificial neural network method for 4-stroke, 4-cylinder, direct injection and supercharged HCCI engine experimental data obtained by using n-heptane fuel at 60 degrees C intake air temperature, 1000 rpm engine speed at different inlet air intake pressure. Intake air inlet pressure and lambda were used as input data in artificial neural network model. The COVIMEP value was used as the target. Three layers and five neurons were used to construct the network using the Levenberg-Marquardt algorithm. Correlation between targets and outputs for teaching, accuracy and testing were obtained as 0.97989, 0.9504 and 0.91644, respectively. Total correlation factor was found as 0.96983. As a result of the study, it was seen that the stored data and the estimated COVIMEP data were compatible.
dc.identifier.endpage727en_US
dc.identifier.issn1302-0900
dc.identifier.issn2147-9429
dc.identifier.issue3en_US
dc.identifier.startpage721en_US
dc.identifier.urihttps://hdl.handle.net/11491/7105
dc.identifier.volume23en_US
dc.identifier.wosWOS:000545278700015
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.institutionauthor[Belirlenecek]
dc.language.isoen
dc.publisherGazi Univ
dc.relation.ispartofJournal Of Polytechnic-Politeknik Dergisi
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectHCCI engineen_US
dc.subjectlow temperature combustionen_US
dc.subjectartificial neural networken_US
dc.titleEstimation of the COVIMEP Variation in a HCCI Engine
dc.typeArticle

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