Nusselt number analysis from a battery pack cooled by different fluids and multiple back-propagation modelling using feed-forward networks

Abstract In this article, analysis of average Nusselt number (Nuavg), which indicates the heat removal from battery pack cooled by flowing fluid is carried out considering coupled transfer condition at and coolant interface. Five categories coolant, mainly gases, common oils, thermal nanofluids, liquid metals, are selected. each category, five fluids (having different Prandtl Pr) selected passed over Li-ion pack. The made for conductivity ratio (Cr), generation term (Qgen), Reynolds (Re), Pr. Pr varying in range 0.0208–511.5 (25 coolants) Cr category having its own upper lower limit used to analyze removed Using single feed-forward network integrating two networks multi-layers with back-propagation employed artificial neural (ANN) modelling. modelling, concept main space devised multiple back propagation (MBP). numerical revealed that temperature distribution greatly affected increasing Cr. maximum located close edge found get reduced significantly increase Cr, but upto a certain above reduction marginal. reveals Qgen have no role improving Nuavg while Re vary it step. Moreover, continuously irrespective any Qgen. While, oils an Re, was reduce significantly. Nanofluids be more effective when nano-coolants it. MBP proposed successfully trained, hence they can prediction Nuavg.