
The study uses a hybrid simulation model combining system dynamics and agent-based modelling, followed by a multicriteria decision-making method, to evaluate the role of remanufacturing in managing end-of-life electric vehicle batteries. This approach addresses the increasing battery volumes and the need for sustainable strategies by European manufacturers to comply with regulations and reduce recycling demand. Recycling, while straightforward for compliance, faces logistical challenges and limited capacity, making alternative solutions critical. Through 15 simulations across three scenarios from 2024 to 2035, considering agents like collection points and treatment facilities, the study highlights key findings: A 90% State of Health threshold for remanufacturing results in a 47-kilotonne recycling deficit, €359 million in storage costs, and 2,089 KtCO2e emissions. Locating remanufacturers closer to collection points with a 70% SOH threshold adds 224 Kt of recycling capacity, cuts €91 million in storage costs, reduces emissions by 600 KtCO2e, and supports second-life options for 420 Kt of batteries.
[SPI.AUTO] Engineering Sciences [physics]/Automatic, [SPI] Engineering Sciences [physics], [SPI.OTHER] Engineering Sciences [physics]/Other, Hybrid simulation model, Sustainable manufacturing, Recycling capacity, [MATH.MATH-CV] Mathematics [math]/Complex Variables [math.CV], Electric vehicles batteries, Logistics, Remanufacturing
[SPI.AUTO] Engineering Sciences [physics]/Automatic, [SPI] Engineering Sciences [physics], [SPI.OTHER] Engineering Sciences [physics]/Other, Hybrid simulation model, Sustainable manufacturing, Recycling capacity, [MATH.MATH-CV] Mathematics [math]/Complex Variables [math.CV], Electric vehicles batteries, Logistics, Remanufacturing
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
