An Expert System for Ranking and Matching Electric Vehicles to Customer Specifications and Requirements

Yossi Hadad (), Baruch Keren and Dima Alberg
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Yossi Hadad: Department of Industrial Engineering and Management, SCE—Shamoon College of Engineering, Beer-Shvea 8410802, Israel
Baruch Keren: Department of Industrial Engineering and Management, SCE—Shamoon College of Engineering, Beer-Shvea 8410802, Israel
Dima Alberg: Department of Industrial Engineering and Management, SCE—Shamoon College of Engineering, Beer-Shvea 8410802, Israel

Energies, 2023, vol. 16, issue 11, 1-18

Abstract: Electric vehicles (EVs) have become popular in the last decade because of their advantages compared to conventional vehicles. The market offers dozens of EV models in a large range of prices, performances, and specifications. This paper presents an expert system we developed to support sellers and customers in choosing an EV that matches the customers’ specifications. The system enables ranking-specific EVs according to the customers’ specifications and counting the number of mismatches. The paper analyzes a database of 53 different EVs, each with 22 different characteristics, enabling customers to choose the EV that best suits their most important specifications. Based on the customer’s requirements and the principle of fuzzy sets, the system assigns a matching value to each criterion. These matching values are the input matrix for the TOPSIS procedure that ranks all the EVs according to their matching scores for a specific customer. The applicability of the proposed method is demonstrated for one customer with specific preferred EV requirements. A Python code of this method is also available herein.

Keywords: energy; electric vehicle (EV); TOPSIS; fuzzy sets; expert system; multicriteria decision analysis (MDCA) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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