Biogas engine performance estimation using ANN

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dc.authoridKARAGOZ, Mustafa/0000-0002-2595-9002
dc.contributor.authorKurtgoz, Yusuf
dc.contributor.authorKaragoz, Mustafa
dc.contributor.authorDeniz, Emrah
dc.date.accessioned2024-09-29T15:57:31Z
dc.date.available2024-09-29T15:57:31Z
dc.date.issued2017
dc.departmentKarabük Üniversitesien_US
dc.description.abstractArtificial neural network (ANN) method was used to estimate the thermal efficiency (TE), brake specific fuel consumption (BSFC) and volumetric efficiency (VE) values of a biogas engine with spark ignition at different methane (CH4) ratios and engine load values. For this purpose, the biogas used in the biogas engine was produced by the anaerobic fermentation method from bovine manure and different CH4 contents (51%, 57%, 87%) were obtained by purification of CO2 and H2S. The data used in the ANN models were obtained experimentally from a 4-stroke four-cylinder, spark ignition engine, at constant speed for different load and CH4 ratios. Using some of the obtained experimental data, ANN models were developed, and the rest was used to test the developed models. In the ANN models, the CH4 ratio of the fuel, engine load, inlet air temperature (T-in), air fuel ratio and the maximum cylinder pressure are chosen as the input parameters. TE, BSFC and VE are used as the output parameters. Root mean square error (RMSE), mean absolute percentage error (MAPE) and correlation coefficient (R) performance indicators are used to compare measured and predicted values. It has been shown that ANN models give good results in spark ignition biogas engines with high correlation and low error rates for TE, BSFC and VE values. (C) 2017 Karabuk University. Publishing services by Elsevier B.V.en_US
dc.description.sponsorshipKarabuk University Scientific Research Projects Unit [KBU-BAP-14/2-DR-004]en_US
dc.description.sponsorshipThis study is funded by Karabuk University Scientific Research Projects Unit (project number: KBU-BAP-14/2-DR-004).en_US
dc.identifier.doi10.1016/j.jestch.2017.12.010
dc.identifier.endpage1570en_US
dc.identifier.issn2215-0986
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-85044452795en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1563en_US
dc.identifier.urihttps://doi.org/10.1016/j.jestch.2017.12.010
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4864
dc.identifier.volume20en_US
dc.identifier.wosWOS:000428053200006en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier - Division Reed Elsevier India Pvt Ltden_US
dc.relation.ispartofEngineering Science and Technology-An International Journal-Jestechen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectEstimating engine performanceen_US
dc.subjectBiogasen_US
dc.subjectBSFCen_US
dc.subjectANNen_US
dc.titleBiogas engine performance estimation using ANNen_US
dc.typeArticleen_US

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