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Thermal assessment of Li-ion battery cells and coolant in hybrid electric vehicles system: Application of conjugate condition and response surface methodology

dc.contributor.authorAfzal, Asif
dc.contributor.authorRamis, M. K.
dc.contributor.authorJilte, R. D.
dc.contributor.authorAlwetaishi, Mamdooh
dc.contributor.authorPark, Sung Goon
dc.contributor.authorBuradi, Abdulrajak
dc.contributor.authorAl-Mdallal, Qasem M.
dc.contributor.authorAgbulut, Umit
dc.date.accessioned2026-06-27T15:15:18Z
dc.date.issued2025
dc.description.abstractNumerical and response surface (RS) analysis of the thermal performance of prismatic battery- operated cell is performed cooled by the forced flow of air considering conjugate condition at the cell-fluid interface. At the battery-air interface, where the heat flow continuity and temperature condition exist, the combined heat transfer condition is examined. Control volume-based code is developed where the Navier-stokes equation is solved by SIMPLE algorithm. The numerical work is endorsed by the experimental work specified in the literature. The effects of bcc (conduction-convection parameter - 0.06 to 0.1), Ar (Aspect ratio 10 to 30), volumetric heat generation (Sq - 0.1 to 1.0), and Re (Reynolds number - 250 to 2000) are investigated. The effect of the parameters mentioned above on temperature distribution (TeDi) along the axial direction (AD) in the battery cell (BC) and transverse TeDi in the fluid channel is investigated. The variations in temperature gradient and maximum temperature (MT) difference for different Sq, bcc, Re, and Ar are illustrated. The RS methodology is employed to analyze the MT of the battery. The MT difference obtained with increasing Sq and Re is quite significant. The MT difference obtained with an increase in bcc and Re is much less and the same is negligible with Ar. Re below 500 and bcc below 0.06 will cause a greater increase in MT, which acts as lower limits. Similarly, Re above 1250 and zeta cc above 0.08 do not help in the reduction of MT. For Sq = 0.7 and above, the temperature crosses its maximum permissible limit of the battery cell. The RS model developed gives an accuracy of 97 %, close to the numerical values. The RS analysis of MT indicates that Sq is the most influential parameter.en
dc.description.sponsorshipTaif University, Saudi Arabia [TU-DSPP-2024-32]
dc.description.sponsorshipNational Research Foundation of Korea [RS-2022-00144236]
dc.description.urihttps://doi.org/10.1016/j.csite.2025.105766
dc.identifier.doi10.1016/j.csite.2025.105766
dc.identifier.issn2214-157X
dc.identifier.urihttps://hdl.handle.net/20.500.14981/69539
dc.identifier.volume66
dc.identifier.wos001441535200001
dc.language.isoeng
dc.publisherELSEVIER
dc.relation.ispartofCASE STUDIES IN THERMAL ENGINEERING
dc.rightsopenAccess
dc.subjectLi-ion battery
dc.subjectHeat generation
dc.subjectThermal behavior
dc.subjectReynolds number
dc.subjectAxial temperature
dc.subjectMaximum temperature
dc.subjectMANAGEMENT
dc.subjectMODULE
dc.subjectPACK
dc.subjectFLOW
dc.subjectTEMPERATURE
dc.subjectPERFORMANCE
dc.subjectOVERCHARGE
dc.subjectBEHAVIOR
dc.subjectThermodynamics
dc.titleThermal assessment of Li-ion battery cells and coolant in hybrid electric vehicles system: Application of conjugate condition and response surface methodology
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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