Selection of electric vehicle using integrated Fuzzy-MCDM approach with analysis on challenges faced in hilly terrain

ABSTRACT

Electric Vehicles (EVs) are still not a preferable choice among the consumers of vehicular world. It has now become necessary to showcase the merits of EVs to the consumers. If compared to the nonhilly areas, people in hills are still reluctant toward adoption of EVs due to various constraints as mentioned in this article. Several factors affect the desirability of EVs, including technical and customer-related factors. This work also proposes a model to help customers choose the most suitable EV by adjudging vehicles concerning multiple factors. During the judging process, extra care is taken to include factors defining the viewpoint of the general customer while purchasing the EV. Distinctly, two sets of criteria, one highlighting the technical specifications of the EV and the other exclusively defining the customer’s perspective of it, including features like cost, warranty, charging facility, etc., are taken up to rank the six most popular EV models in India using a Fuzzy-based Multi-Criteria Decision-Making (MCDM) model. Here, the Quality Function Deployment (QFD) model is used to tackle the weightage of the criteria based on customer’s feedback. The outcome of this work and the evaluation process can act as a quick guideline for any arbitrary customer who plans to make a new purchase of an EV. Hyundai Kona electric scored 0.223 the highest, making it the most suitable choice, and Mahindra E20 plus scored 0.121, making it the least suitable choice among the list of EVs chosen in the study for the Indian market. An additional case study segment in this article focuses on the market penetration issues that the EVs may likely face on a hilly terrain in the perspective of energy consumption per trip and the customer woes that may arise due to terrain.

KEYWORDS:

• Electric vehicles
• Sustainable development
• Customer perspective
• MCDM
• Fuzzy-COPRAS
• QFD

Acknowledgments

The authors are indebted to the library resources provided by their institution/ organization for carrying out this research work, and also the authorities of the various data sources from which the data for the study have been taken. They also thank the team of experts who had been immensely helpful and cooperative through the course of this work.

Disclosure statement

No potential conflict of interest was reported by the author(s).