Selection of nanoparticles for battery thermal management system using integrated multiple criteria decision‐making approach. (31st August 2022) - Dwivedi, Ankur; Kumar, Anoop; Goel, Varun
Summary: The selection of suitable nanoparticles is an important task for their applications as heat transfer promoters for the mitigation of thermal issues in energy storage systems. This paper aims to present a systematic framework for the selection of nanoparticles based on multiple attribute decision‐making tools. A hybrid Grey relational analysis‐based technique for order preference by similarity to ideal solution (GRA‐TOPSIS) approach combining the advantages of both GRA and TOPSIS methodologies is proposed and opted for evaluation, comparison, and ranking of different alternatives under the influence of several objective and subjective criteria weights. The criteria importance through inter‐criteria correlation (CRITIC) and entropy weighing methods are employed to determine the objective weights, while the subjective weights are calculated using the analytic hierarchy process (AHP). Also, an attempt is made to present a generalized weight integration formula that combines several objective and subjective weights of attributes. The results demonstrate Al2 O3 nanoparticles as the most acceptable alternative. The sensitivity analysis performed proves the robustness and feasibility of the adopted decision framework. Additionally, the rank reversal issue is also addressed to present the qualitative assessment of estimated results. Thus, the evaluation methodology discussed in this paper seems to provide a theoretical reference strategy for nanoparticle selection in heat transfer enhancement applications. Highlights: A novel integrated multiple criteria decision making scheme for nanoparticle selection is presented An attempt is made to present a generalized weight integration formula combining several objective and subjective weights of attributes Thermal conductivity and specific surface area are reported as the most significant attributes. Al2 O3 is highlighted as the best choice. The sensitivity analysis and rank‐reversal test have also been performed to check the robustness of suggested procedures and Al2 O3 has outperformed all other alternatives under consideration. Abstract : The present work deals with the selection of suitable nanoparticles as cooling agents for battery thermal management systems. A systematic framework has been suggested by integrating the GRA‐TOPSIS ranking scheme with several objective and subjective criteria weights determination techniques. The CRITIC and entropy weighing methods are employed to determine the objective weights; while the subjective weights are calculated using the AHP scheme. The analysis was performed for several beneficial (specific he at capacity, thermal conductivity, specific surface area, zeta potential) and non‐beneficial (density, cost) attributes, while; CuO, Al2 O3, TiO2, SiO2, Fe3 O4, ZnO, and MgO are selected potential alternatives. The results demonstrate Al2 O3 nanoparticles as the most suitable alternative.