AI Integrated Neutrosophic MCDM Framework for Promoting Carbon Neutrality through Li-Ion Battery Selection for Electric Vehicles

Nivetha Martin; Rajkumar S; Broumi Said

doi:10.63924/jau.v1i2.296

Authors

Nivetha Martin Madurai Kamaraj University https://orcid.org/0000-0001-9942-1320
Rajkumar S Madurai Kamaraj University https://orcid.org/0000-0003-0865-2516
Broumi Said Regional Center for the Professions of Education and Training (CRMEF) https://orcid.org/0000-0002-1334-5759

DOI:

https://doi.org/10.63924/jau.v1i2.296

Keywords:

MCDM Framework, Li-ion, Battery Electric Vehicles, Optimal Ranking, RFA, FIA, SHAP

Abstract

vehicles in the coming decades to promote carbon neutrality. The compatibility and robustness of Li-ion based batteries make them more preferable in BEVs. A recent study has identified five different groups of Li- ion based batteries used in BEVs and applied a very simple multi–criteria decision making (MCDM) method of Weighted sum with equal criterion weights and linguistic matrix to rank the batteries. The present research work considers the same decision making problem and applies different MCDM methods to determine the criterion weights and ranking of the batteries with Triangular Neutrosophic matrix. The methodology proposed in this work works in five phases. The consistency of the neutrosophic ranking results is validated using Random forest technique, Feature importance analysis and SHAP explainability analysis. The comprehensive MCDM framework presented in this work will enable the decision makers of manufacturing company to make ideal selection of the electric vehicle batteries on comparing the ranking scores of the batteries using different methods with different criterion weights.

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