AN ESTIMATION OF IN-CYLINDER PRESSURE BASED ON LAMBDA AND ENGINE SPEED IN HCCI ENGINE USING ARTIFICIAL NEURAL NETWORKS

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dc.authoridOzdilli, Ozgur / 0000-0002-9861-4793
dc.authorwosidOzdilli, Ozgur / AAM-5130-2021
dc.contributor.authorPolat, Seyfi
dc.contributor.authorOzdilli, Ozgur
dc.contributor.authorCizmeci, Huseyin
dc.date.accessioned2021-11-01T15:01:54Z
dc.date.available2021-11-01T15:01:54Z
dc.date.issued2019
dc.department[Belirlenecek]
dc.description.abstractIn this study, the in-cylinder pressure predicted based on lambda and engine speed with the ANN method for HCCI engine. In-cylinder pressures obtained at different lambda and engine speeds, constant inlet air temperature (80 degrees C), RON40 (40% iso-octane/60% n-heptane) fuel in a single cylinder, four-stroke, naturally aspirated, port injection HCCI engine. MATLAB ANN program was used for training, validation and testing ofinputs. The crank angle, engine speed, and lambda were used as input values and the in-cylinder pressure was used as the target value. The Levenberg-Marquardt training algorithm was used for the training of inputs. Also, three layers and 10 neurons were used for the training process. The best validation performance was obtained at epoch 535 as 0.000043691 MSE value. The correlation factor of training, validation, and testing between the targets to outputs were obtained at 0.99912, 0.99905 and 0.99893 respectively. The total correlation factor was found at 0.99908. It is observed that there is a high degree of accuracy between the estimation of results and experimental data using the developed ANN model.
dc.description.sponsorshipHitit University Scientific Research Project [MYOT19003.16.001]en_US
dc.description.sponsorshipThis study was supported by Hitit University Scientific Research Project which is numbered as MYOT19003.16.001.en_US
dc.identifier.endpage3576en_US
dc.identifier.issn1018-4619
dc.identifier.issn1610-2304
dc.identifier.issue4Aen_US
dc.identifier.startpage3568en_US
dc.identifier.urihttps://hdl.handle.net/11491/6752
dc.identifier.volume28en_US
dc.identifier.wosWOS:000467668200072
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.institutionauthor[Belirlenecek]
dc.language.isoen
dc.publisherParlar Scientific Publications (P S P)
dc.relation.ispartofFresenius Environmental Bulletin
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectArtificial neural networken_US
dc.subjectANNen_US
dc.subjectHCCIen_US
dc.subjectengineen_US
dc.subjectin-cylinder pressureen_US
dc.subjectlambdaen_US
dc.titleAN ESTIMATION OF IN-CYLINDER PRESSURE BASED ON LAMBDA AND ENGINE SPEED IN HCCI ENGINE USING ARTIFICIAL NEURAL NETWORKS
dc.typeArticle

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