Electric Vehicle Selection Using the Technique of Precise Order Preference

Abstract

Conventional vehicles rely on petrol and its derivatives to deliver strong performance and extended range. However, these vehicles significantly contribute to environmental pollution and the depletion of fossil fuels. Consequently, alternative-fuelled vehicle technologies have been developed, leading to a paradigm shift in the transportation sector toward electric vehicles (EVs) that reduce greenhouse gas emissions and lessen their environmental impact. For potential EV buyers, a selection problem exists due to the diverse range of alternatives. This study proposes an integrated model that selects and ranks EVs based on three main criteria: cost, driving performance and technical features. Hierarchical best worst method (HBWM), full consistency method (FUCOM), and step-wise weight assessment ratio analysis (SWARA) methods are employed to determine the importance weights for the main criteria and their sub-criteria. A sample EV set consisting of 10 potential alternatives was created for the study, and these EVs were ranked by combining the weights of the main criteria and sub-criteria obtained using the three aforementioned methods employing the technique of precise order preference (TPOP) method. Our experiments suggest that the most critical criterion among the 10 sub-criteria was price, and the least important criterion was high speed.