Energy Management System Strategy Evaluation for E-Vehicles Using Proportional Pythagorean Fuzzy AHP

  • Irem Otay*
  • , Irem Ucal Sari
  • , A. Çağr I. Tolga
  • , Selcuk Cebi
  • , Sezi cevik Onar
  • , Basar Oztaysi
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The shift from conventional vehicles to electric vehicles (EVs) is essential for sustainability. Energy management strategies play a crucial role in this transition, as they affect battery performance, extend lifespan, and ensure cost-effectiveness. This study evaluates energy management system (EMS) strategies for EVs using the Proportional Pythagorean Fuzzy Analytical Hierarchy Process (PPF-AHP) to prioritize decision criteria. To achieve this, a decision model is constructed involving four main criteria—sustainability and resilience, cost efficiency, performance and reliability, and competitiveness—as well as sixteen sub-criteria. Then, pairwise evaluations from five experts are collected and aggregated leading to the prioritization of decision criteria. In order to show the robustness of the methodology, the PPF-AHP results are compared with Buckley’s Fuzzy AHP and Decomposed Fuzzy AHP.

Original languageEnglish
Pages (from-to)217-245
Number of pages29
JournalJournal of Multiple-Valued Logic and Soft Computing
Volume46
Issue number2-4
Publication statusPublished - 2025

Bibliographical note

Publisher Copyright:
©2025 Old City Publishing, Inc.

Keywords

  • Battery performance Proportional Pythagorean fuzzy AHP
  • Electrical vehicles (EVs)
  • Energy management strategies

Fingerprint

Dive into the research topics of 'Energy Management System Strategy Evaluation for E-Vehicles Using Proportional Pythagorean Fuzzy AHP'. Together they form a unique fingerprint.

Cite this