Publication: Smart cooling design using dual loop cooling to increase engine efficiency and decrease fuel emissions with artificial intelligence
dc.contributor.author | Kula, Sinan | |
dc.contributor.author | Bulut, Emre | |
dc.contributor.author | Altay, Esad | |
dc.contributor.author | Sümer, Osman | |
dc.contributor.author | Öztürk, Ferruh | |
dc.contributor.buuauthor | Kula, Sinan | |
dc.contributor.buuauthor | BULUT, EMRE | |
dc.contributor.buuauthor | ÖZTÜRK, FERRUH | |
dc.contributor.department | Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü. | |
dc.contributor.orcid | 0000-0001-9159-5000 | |
dc.contributor.researcherid | JCO-2416-2023 | |
dc.contributor.researcherid | HGN-4395-2022 | |
dc.contributor.researcherid | JGV-6240-2023 | |
dc.date.accessioned | 2024-09-30T12:54:13Z | |
dc.date.available | 2024-09-30T12:54:13Z | |
dc.date.issued | 2022-10-26 | |
dc.description.abstract | In 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.sponsorship | TOFAŞ, Otomotiv Fabrikası, Bursa, Türkiye | |
dc.identifier.doi | 10.1016/j.csite.2022.102351 | |
dc.identifier.issn | 2214-157X | |
dc.identifier.uri | https://doi.org/10.1016/j.csite.2022.102351 | |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S2214157X22005913?via%3Dihub | |
dc.identifier.uri | https://hdl.handle.net/11452/45534 | |
dc.identifier.volume | 40 | |
dc.identifier.wos | 000883742600003 | |
dc.indexed.wos | WOS.SCI | |
dc.language.iso | en | |
dc.publisher | Elsevier | |
dc.relation.journal | Case Studies in Thermal Engineering | |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | |
dc.relation.tubitak | 3170846 | |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | Metamodeling techniques | |
dc.subject | Heat-exchangers | |
dc.subject | System | |
dc.subject | Dual loop cooling system | |
dc.subject | Neural network | |
dc.subject | 1d analysis | |
dc.subject | Fuel emission levels | |
dc.subject | Thermodynamics | |
dc.title | Smart cooling design using dual loop cooling to increase engine efficiency and decrease fuel emissions with artificial intelligence | |
dc.type | Article | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | f40336d8-7dee-4bc0-b37a-c7f07578c139 | |
relation.isAuthorOfPublication | 407521cf-c5bd-4b05-afca-6412ef47700b | |
relation.isAuthorOfPublication.latestForDiscovery | f40336d8-7dee-4bc0-b37a-c7f07578c139 |
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