An integrated entropy-based multi-attribute decision-making model for phase change material selection and passive thermal management

Abstract

The growing environmental concerns related to fossil-based power usage have led to a global transition towards renewable and conservative energy usage practices. In the context of human thermal comfort within enclosures, Phase Change Materials (PCMs) are deployed as effective passive conditioning media to curtail active air-conditioning demands. The successful functioning of PCM is strongly dependent upon a match between its thermophysical properties and the working environment’s thermal attributes. This creates a multifaceted selection scenario, given the availability of PCMs with a wide range of thermophysical properties. In this study, we investigate the case of selecting suitable PCM for passive thermal management in an automobile cabin. Various decision strategies and analytical methods are implemented to evaluate the efficacy of PCM selection using Multiple Objective Decision-Making (MODM) and Multiple Attribute Decision-Making (MADM) approaches. This study integrates different approaches and provides a comparative analysis of the selection processes. MODM is used for objectively evaluating the attributes (or properties of the PCMs) with Ashby’s approach. The Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are used along with the entropy-based weights. The selection algorithms suggest the suitability of Gallium and a few other PCMs for the desired application. This study could be a precursor to experimental and computational fluid dynamics (CFD)-based investigations for problems where the test set of PCMs could be narrowed down in the initial stage to save subsequent analysis time and money.