A consolidated decision-making framework for nano-additives selection in battery thermal management applications

Abstract

The selection of appropriate nano-additives for optimum battery thermal management system (BTMS) performance is an exigent task for decision-makers and is a multi-attribute decision-making (MADM) problem. This work presents a framework that utilizes the application of various MADM schemes. These techniques are integrated with a subjective weighting criteria approach to prioritize suitable nano-additives as promoters towards heat transfer enhancement to mitigate the thermal issues in energy storage devices. The COPRAS, PROMETHEE-II, and VIKOR methods are used to present ranking schemes for alternatives based on the criteria weights assigned by the AHP method. The results show that Graphene and MWCNT nano-additives are the best-suited alternatives. The sensitivity tests are carried out to describe the effect of parametric variations in the most critical risk preferences over the rankings of the alternatives. In addition, the problem of rank reversal associated with these methods is also addressed. Therefore, the evaluation criteria and methodology in this work can provide a theoretical reference for nano-additive selection. An attempt is made to discuss the technical index of efficiency assisting decision-makers to make reliable and robust decisions by employing the CCR model.