Modeling the Performance and Emission Characteristics of Diesel Engine and Petrol-Driven Engine by ANN

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dc.contributor.authorTütüncü, Kemal
dc.contributor.authorAllahverdi, Novruz
dc.date.accessioned2020-03-26T17:45:51Z
dc.date.available2020-03-26T17:45:51Z
dc.date.issued2009
dc.departmentSelçuk Üniversitesien_US
dc.descriptionInternational Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing, CompSysTech'09 -- 18 June 2009 through 19 June 2009 -- Ruse -- 79958en_US
dc.description.abstractIn this study, performance and emission characteristics of an internal combustion (IC) diesel engine and petrol-driven engine were modeled by Artificial Neural Network (ANN). Diesel engine input parameters are air flow rate (Aflr), boost pressure (Pb), fuel rate (Frt), cycle (Cy) and load (L) whereas input parameters of the petrol-driven engine are advance (A) and cycle (Cy). Engine torque (Tq), power (P), specific fuel consumption (Sfc), emission values such as HC, CO2 and NOx of diesel engine and engine torque (Tq), power (P), specific fuel consumption (Sfc) and HC of petrol-driven have been investigated. R square values of Tq, P, Sfc, HC, CO2 and NOx of diesel engine were %99.9, %99.45, %99.32, %99.84, %99.71 and %99.26 respectively when ANN was used for modeling. R square values of Tq, P, Sfc and Hc of petrol-driven engine %97.24, %99.56, %98.19 and %97.19 respectively. The back-propagation learning algorithm with Hyperbolic tangent activation functions (for hidden layer neurons and output neuron) and 5:12:1 combination have been used in the topology of the network of diesel engine. The back-propagation learning algorithm with Logistic-Hyperbolic tangent activation functions (hidden layer neurons and output neuron) and 2:6:1 combination have been used in the topology of the network of petrol-driven engine. After having statistical t-test for outputs of both ANN, it has been seen that the obtained results are approximately %99.5 and %98.5 consisted (matched) with experimental data of diesel and petrol-driven engine. Main contribution of this work includes; 1) Dynamic load value was used as input parameters for diesel engine and so engine performance modeling and emission characteristic determination were done by regarding changing load, 2) The highest prediction values of output parameters are reached for both engine type regarding to the previous studies and 3) None of the previous studies include modeling of diesel and petrol-driven engine.en_US
dc.identifier.citationTütüncü, K., Allahverdi, N., (2006). Modeling the Performance and Emission Characteristics of Diesel Engine and Petrol-Driven Engine by ANN. Acm International Conference Proceeding Series, (433), 101-106. Doi: 10.1145/1731740.1731803
dc.identifier.doi10.1145/1731740.1731803en_US
dc.identifier.endpageIIIB.106en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpageIIIB.101en_US
dc.identifier.urihttps://dx.doi.org/10.1145/1731740.1731803
dc.identifier.urihttps://hdl.handle.net/20.500.12395/24163
dc.identifier.volume433en_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorTütüncü, Kemal
dc.institutionauthorAllahverdi, Novruz
dc.language.isoenen_US
dc.relation.ispartofAcm International Conference Proceeding Seriesen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectANNen_US
dc.subjectEngine performance and emissionen_US
dc.subjectIC diesel engineen_US
dc.subjectModelingen_US
dc.subjectPetrol-driven engineen_US
dc.titleModeling the Performance and Emission Characteristics of Diesel Engine and Petrol-Driven Engine by ANNen_US
dc.typeConference Objecten_US

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