Framework for Selecting the Most Effective State of Health Method for Second-Life Lithium-Ion Batteries: A Scientometric and Multi-Criteria Decision Matrix Approach

AbdulRahman Salem, Basil M. Darras () and Mohammad Nazzal
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AbdulRahman Salem: Department of Mechanical Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates
Basil M. Darras: Department of Mechanical Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates
Mohammad Nazzal: Duroub Academy, Amman 11118, Jordan

Energies, 2025, vol. 18, issue 6, 1-24

Abstract: The predicted rapid accumulation of end-of-life lithium-ion batteries (LIBs) from electric vehicles (EVs) has raised environmental concerns due to the toxic nature of LIB materials. Consequently, researchers have developed reusing and recycling plans for end-of-life LIBs to extend their life spans, mitigate residual capacity loss, and reduce their environmental impact. As a result, many studies have recommended establishing a lifecycle framework for LIBs to identify and manage the potential options for reusing, recycling, remanufacturing, or disposal of second life LIBs. In response, the state of health (SOH) and state of safety (SOS) methods were introduced as key performance indicators (KPIs) to determine the batteries’ health and usability based on their capacity levels. Thus, both SOH and SOS methods are crucial for battery cell selection frameworks employed to designate batteries’ second-life applications. Various papers have analyzed and compared SOH methods, yet none have clearly quantified their differences, to determine the most effective method. Therefore, this study aims to create a framework for selecting the most effective SOH method for use in LIB frameworks by identifying and quantifying their main KPIs. The proposed framework will utilize scientometric analysis to identify the KPIs necessary for a gray relation analysis (GRA)-based multi-criteria decision matrix (MCDM) to select the appropriate SOH method.

Keywords: electric vehicle batteries; battery life cycle analysis; state of health; scientometric analysis; multi-criteria decision matrices (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: 2025
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