A sustainable echelon re-utilization and recycling for dynamic end-of-life electric vehicle battery packs

Electric vehicle (EV) batteries inevitably degradation with long-term use that hierarchically reuse EV battery packs after meeting their related recycling standards to maximize its potential values by application environments, battery characteristics, product types, etc. However, these factor uncertainties pose a major challenge to effective evaluation from inconsistent performance, widely varied remaining capacities, and potential safety concerns. Therefore, it is imperative to achieve a more accurate evaluation for echelon re-utilization to provide a sounder rationale for decisions regarding the recycling of EV battery modules or cells. In this paper, a reasonable and efficient intelligent evaluation system has been provided to solve these challenges caused by the uncertainties of EV battery packs that hierarchically consider the possible applications of echelon re-utilization and recycling. The unique contribution of this system lies in its novel integration of knowledge reasoning with relation mining, which surpasses traditional evaluation methodologies by systematically analyzing the complex and intrinsic dependencies among various battery characteristics, moving beyond simple parameter-based assessments. Moreover, big data calculation and relation analysis of EV battery pack characteristics with GB/T_34015.3–2021 standard can be used to recommend the possible scenarios of echelon re-utilization and recycling. Finally, a case study was conducted using 18650 lithium iron phosphate (LFP), Nickel-Cobalt-Manganese (NCM), and Nickel-Cobalt-Aluminum (NCA) batteries to validate the proposed methodology by evaluating the echelon re-utilization and the selection of application scenarios based on complex data analysis and relation mining.