Optimizing Electric Mobility: A Multi-Criteria Decision-Making Approach for Sustainable Future of Electric Vehicles Through Smart Motor Choices

• Published in: Journal Europeen des Systemes Automatises Vol. 57; no. 6; p. 1825
• Main Authors: Kumar, Pulkit, Channi, Harpreet Kaur, Kumar, Raman, Stević, Željko, Singh, Sehijpal, Bhattacherjee, Abhishek, Bhowmik, A
• Format: Journal Article
• Language: English
• Published: Edmonton International Information and Engineering Technology Association (IIETA) 01.12.2024
• Subjects: Automobile industry; Cost analysis; Data envelopment analysis; Decision making; Electric vehicles; Energy efficiency; Fuzzy logic; Multiple criteria decision making; Sustainability
• ISSN: 1269-6935; 2116-7087; 2116-7087
• DOI: 10.18280/jesa.570630

To decrease reliance on fossil fuels and carbon emissions, electric vehicles (EVs) have emerged as indispensable instruments in the automotive industry's shift toward more sustainable methods. The achievement of peak efficiency in EVs is contingent upon the appropriate selection of motors and batteries; therefore, exploring methods that ensure sustainable decisions is imperative. The article employs Multi-Criteria Decision-Making (MCDM) techniques to assess and propose the most environmentally friendly amalgamation of batteries and motors for EVs. The research investigates many sustainability-related factors, encompassing energy density, power density, cost, longevity, and environmental impact. By employing MCDM methodologies, including the Analytic Hierarchy Process (AHP), Simple Additive Weighting (SAW), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a comprehensive decision framework is developed with an emphasis on sustainability. The research outcomes provide a thorough understanding of the trade-offs between battery life and motor efficiency, which holds significance for policymakers, academics, and manufacturers dedicated to endorsing sustainable energy practices. The suggested methodology not only streamlines the decision-making process but also promotes the development of environmentally sustainable and highly efficient EVs.