Nanofluid-based cooling of prismatic lithium-ion battery packs: an integrated numerical and statistical approach

Basit Öğe Kaydı
dc.authorid0000-0001-7794-6943en_US
dc.contributor.authorMorali, Ugur
dc.contributor.authorYetik, Ozge
dc.contributor.authorKarakoc, Tahir Hikmet
dc.date.accessioned2023-11-28T07:48:46Z
dc.date.available2023-11-28T07:48:46Z
dc.date.issued2023en_US
dc.departmentRektörlük, Bilişim Teknolojileri Uygulama ve Araştırma Merkezien_US
dc.description.abstractRecently, the need for thermal management of lithium-ion batteries in electrical transportation engineering has received increased attention. To get maximum performance from lithium-ion batteries, battery thermal management systems are required. This paper quantitatively presents the efects of several factors on both maximum battery temperature and tem perature gradient. These factors include ambient temperature (288 K, 293 K, 298 K, 303 K, 308 K), C-rate (1C, 2C, 3C, 4C, 5C), mixing ratio (1%, 2%, 3%, 4%, 5%), and inlet velocity (0.01 m s ?1, 0.02 m s ?1, 0.03 m s ?1, 0.04 m s ?1, 0.05 m s ?1). Five levels for each parameter were considered to develop the orthogonal array. The signifcance of the variables was orderly shown through the L25 experiment. Results indicated that for maximal battery temperature, C-rate and ambient temperature are the most signifcant factors while for temperature gradient, C-rate and inlet velocity play an important role. For maxi mum battery temperature ambient temperature, C-rate, mixing ratio, and inlet velocity of 288 K, 1C, 4%, and 0.05 m s ?1, respectively, were obtained at the optimal setting. An ambient temperature of 308 K, a C-rate of 1, a mixing ratio of 5%, and an inlet velocity of 0.05 m s ?1 was the optimal setting for the temperature gradient. The results showed that the confrmatory test validates the optimization process for maximum battery temperature and temperature gradient. This study may provide a pathway for manufacturers and researchers interested in minimizing battery temperature and improving temperature gradient in electric vehicle applications.en_US
dc.identifier.doi10.1007/s10973-023-12726-9en_US
dc.identifier.scopus2-s2.0-85176761695en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11467/7044
dc.identifier.urihttps://doi.org/10.1007/s10973-023-12726-9
dc.identifier.wosWOS:001123274800004en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofJournal of Thermal Analysis and Calorimetryen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Başka Kurum Yazarıen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectThermal management system, Prismatic lithium-ion battery, Maximum battery temperature, Temperature gradient, Nanofuiden_US
dc.titleNanofluid-based cooling of prismatic lithium-ion battery packs: an integrated numerical and statistical approachen_US
dc.typeArticleen_US

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