Thermal assessment of Li-ion battery cells and coolant in hybrid electric vehicles system: Application of conjugate condition and response surface methodology - Asif Afzal; M.K. Ramis; R.D. Jilte; Mamdooh Alwetaishi; Sung Goon Park; Abdulrajak Buradi; Qasem M. Al-Mdallal; Ümit Ağbulut (Case Studies in Thermal Engineering)
Numerical 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 ζcc (conduction–convection parameter – 0.06 to 0.1), Ar (Aspect ratio 10 to 30), volumetric heat generation (S‾q – 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 S‾q, ζcc, Re, and Ar are illustrated. The RS methodology is employed to analyze the MT of the battery. The MT difference obtained with increasing S‾q and Re is quite significant. The MT difference obtained with an increase in ζcc and Re is much less and the same is negligible with Ar. Re below 500 and ζcc below 0.06 will cause a greater increase in MT, which acts as lower limits. Similarly, Re above 1250 and ζcc above 0.08 do not help in the reduction of MT. For S‾q = 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 S‾q is the most influential parameter.