Application of MCDM Techniques for Selection of Battery for Electric Vehicle

Abstract

An electric vehicle (EV) operates using an electric motor, which differs from traditional vehicles powered by internal combustion enginesElectric motors are used to power EVs rather than gasoline and gasses. These motors are powered by fuel cells, solar panels, or battery packs that recharge.  As a result, EVs are increasingly considered as potential replacements for conventional automobiles, aiming to combat issues such as pollution, global warming, and resource depletion. Electric cars are essentially the way of his future for transportation. In order to speed up battery selection, this work presents an integrated approach to multi-criteria decision-making (MCDM) which incorporates the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) ranking technique with the Probabilistic weight method. By employing the TOPSIS framework and Entropy Weight Method (EWM), we can assess various battery options based on their relevance to specific EV requirements. Both methodologies offer valuable insights into identifying the optimal battery technology for electric vehicles, considering a range of factors

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