Journal
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
Volume 166, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijheatmasstransfer.2020.120798
Keywords
Battery thermal analysis; Optimization; Conjugate condition; Coolants; Cuckoo search; Artificial bee colony algorithm
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Thermal management of heat-generating battery packs involves analysis and optimization of various parameters, with spacing, coolant characteristics, and optimization algorithms playing key roles in determining thermal characteristics.
Thermal management of heat-generating battery packs involve many operating parameters affecting its performance, efficiency, and maintenance. Heat generation (Q(gen)), conductivity ratio (Cr), Reynolds number (Re), spacing between the packs (W-s), and coolant Prandtl number (Pr) are the parameters selected as working parameters for conjugate thermal analysis and optimization. The thermal analysis of battery packs is carried out numerically using the finite volume method. Single and multi-objective optimization of thermal management characteristics, namely maximum temperature (T-b, (max)), average Nusselt number (Nu(a)(vg)), and coefficient of friction (Fc(avg)) using Cuckoo search (CS) and artificial bee colony (ABC) algorithm is attempted. For faster numerical analysis, the developed code is parallelized using OpenMP paradigm. 25 coolants having Pr in the range 0.02 to 511.5 belonging to five categories i.e. gases, oils, thermal oils, nanofluids, and liquid metals, are adopted for optimization. Nu(a)(vg) and Fc(avg) are not affected by Cr and Q(gen), while T-b, (max) changes significantly. W-s, Pr, and Re impact these characters differently, demanding the need for optimization. Nanofluids and thermal oils have emerged as the best coolants for optimized thermal characteristics at higher heat generations. CS algorithm provided high fitness of objective functions in single-objective optimization, whereas the ABC algorithm converged with high fitness during multi-objective optimization. (C) 2020 Elsevier Ltd. All rights reserved.
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