Publication:
Smart cooling design using dual loop cooling to increase engine efficiency and decrease fuel emissions with artificial intelligence

dc.contributor.authorKula, Sinan
dc.contributor.authorBulut, Emre
dc.contributor.authorAltay, Esad
dc.contributor.authorSümer, Osman
dc.contributor.authorÖztürk, Ferruh
dc.contributor.buuauthorKula, Sinan
dc.contributor.buuauthorBULUT, EMRE
dc.contributor.buuauthorÖZTÜRK, FERRUH
dc.contributor.departmentBursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.
dc.contributor.orcid0000-0001-9159-5000
dc.contributor.researcheridJCO-2416-2023
dc.contributor.researcheridHGN-4395-2022
dc.contributor.researcheridJGV-6240-2023
dc.date.accessioned2024-09-30T12:54:13Z
dc.date.available2024-09-30T12:54:13Z
dc.date.issued2022-10-26
dc.description.abstractIn this study, smart cooling design and optimization, which is based on dual loop cooling system, is used to increase the efficiency of the engine and decrease the fuel emission levels with the artificial intelligence approach. Dual circuit cooling system is used to cool down the charged air and condenser for the 1.6 lt turbocharged diesel engine. The main objective is to increase the efficiency of the engine and decrease the fuel emission levels with smart cooling system design using 1D analysis, experimental tests and neural networks. Water-cooled air charger and condenser are placed separately on engine bay. Whereas, similar applications have been used for these modules integrated on the engine itself. Artificial Neural Network approach is applied in order to optimize the water cooled air charger sizing. Input data is generated by using 1D model within the correlation of experimental test results both on dyno and road conditions. Experimental and 1D analysis data comparison shows that they are very coherent. Results showed that efficiency of the engine is increased and CO2 (g/km) emission levels are decreased about 4,1% in WLTP cycle. It's obtained with efficient dual loop cooling system and optimization based on 1D model and ANN approach.
dc.description.sponsorshipTOFAŞ, Otomotiv Fabrikası, Bursa, Türkiye
dc.identifier.doi10.1016/j.csite.2022.102351
dc.identifier.issn2214-157X
dc.identifier.urihttps://doi.org/10.1016/j.csite.2022.102351
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S2214157X22005913?via%3Dihub
dc.identifier.urihttps://hdl.handle.net/11452/45534
dc.identifier.volume40
dc.identifier.wos000883742600003
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherElsevier
dc.relation.journalCase Studies in Thermal Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.relation.tubitak3170846
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectMetamodeling techniques
dc.subjectHeat-exchangers
dc.subjectSystem
dc.subjectDual loop cooling system
dc.subjectNeural network
dc.subject1d analysis
dc.subjectFuel emission levels
dc.subjectThermodynamics
dc.titleSmart cooling design using dual loop cooling to increase engine efficiency and decrease fuel emissions with artificial intelligence
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublicationf40336d8-7dee-4bc0-b37a-c7f07578c139
relation.isAuthorOfPublication407521cf-c5bd-4b05-afca-6412ef47700b
relation.isAuthorOfPublication.latestForDiscoveryf40336d8-7dee-4bc0-b37a-c7f07578c139

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