Using Fuzzy Inputs to Analyze Factors in the Adoption of Electric Vehicles (EVs)

Arnab Sircar

Abstract

This research applies a set of mathematical techniques to a setting where precise values cannot be obtained for opinions from experts. In order to demonstrate the applicability of these techniques, a research study was designed to measure the importance of factors responsible for increased usage and adoption of electric vehicles (EVs). In the design, various factors were considered where their measured values were subjective since in such situations, the factors are not like typical variables that occur naturally. Further, these measured values may also be imprecise. So, the idea of fuzzy numbers and fuzzy sets were utilized to capture measured values of these factors. Twelve factors were identified under three different categories of environment and sustainability, performance and efficiency, and design and manufacture. Then, fuzzy inputs were sought from six experts as a means of measuring the importance of these twelve factors. The fuzzy numbers from the six experts were aggregated using a similarity-based method and ranked based on a concept of centroids of fuzzy numbers. Thus, the top three factors were determined by developing an adoption score and ranking them in order. The top three factors determined were battery recharge time, battery cost, and environmental pollution.

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