Performance maps of a diesel engine

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dc.contributor.authorÇelik, Veli
dc.contributor.authorArcaklioğlu, Erol
dc.date.accessioned2020-06-25T17:40:31Z
dc.date.available2020-06-25T17:40:31Z
dc.date.issued2005
dc.departmentKırıkkale Üniversitesi
dc.descriptionARCAKLIOGLU, Erol/0000-0001-8073-5207
dc.description.abstractThis paper suggests a mechanism for determining the constant specific-fuel consumption curves of a diesel engine using artificial neural-networks (ANNs). In addition, fuel-air equivalence ratio and exhaust temperature values have been predicted with the ANN. To train the ANN, experimental results have been used, performed for three cooling-water temperatures 70, 80, 90, and 100 C for the engine powers ranging from 1000 to 2300 - for six different powers of 75-450 kW with incremental steps of 75 kW. In the network, the back-propagation learning algorithm with two different variants, single hidden-layer, and logistic sigmoid transfer function have been used. Cooling water-temperature, engine speed and engine power have been used as the input layer, while the exhaust temperature, break specific-fuel consumption (BSFC, g/kWh) and fuel-air equivalence ratio (FAR) have also been used separately as the output layer. It is shown that R-2 values are about 0.99 for the training and test data; RMS values are smaller than 0.03; and mean errors are smaller than 5.5% for the test data. (c) 2004 Elsevier Ltd. All rights reserved.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.doi10.1016/j.apenergy.2004.08.003
dc.identifier.endpage259en_US
dc.identifier.issn0306-2619
dc.identifier.issn1872-9118
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-14644428981
dc.identifier.scopusqualityQ1
dc.identifier.startpage247en_US
dc.identifier.urihttps://doi.org/10.1016/j.apenergy.2004.08.003
dc.identifier.urihttps://hdl.handle.net/20.500.12587/3471
dc.identifier.volume81en_US
dc.identifier.wosWOS:000229661300002
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofApplied Energy
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectartificial neural-networken_US
dc.subjectperformance mapsen_US
dc.subjectfuel-air equivalence ratioen_US
dc.subjectdiesel engineen_US
dc.titlePerformance maps of a diesel engineen_US
dc.typeArticle

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