Discrete-event simulation of semi-destructive disassembly technologies for end-of-life automotive traction batteries

Abstract Battery-powered electromobility is a key strategy for mitigating climate change since it directly reduces transport-related greenhouse gas emissions. As electric vehicle batteries reach their end-of-life, recovery of valuable materials through recycling offers not only lower greenhouse gas emissions than virgin material sourcing but also supply chain resilience. To ensure profitable recycling, the disassembly of electric vehicle battery packs is required, with the removal of the top cover as the first step. While today’s end-of-life volumes still allow manual top cover disassembly, future growth in end-of-life battery returns makes automated disassembly necessary. This study aims to benchmark laser cutting and milling for automated top cover removal based on production and cost metrics. The simulation of two automated work cells yields cycle times and annual throughput. This serves as input for the subsequent cost analysis, modeling capital and operating expenditures across five recycling plant scales, reporting total costs and unit costs per pack, per kilowatt-hour, and per metric ton processed. Results indicate laser cutting’s suitability for handling large volumes. While laser cutting is dominated by fixed CAPEX that benefit from scale, milling is driven by variable operating expenditures that constrain competitiveness as disassembly volume increases. Given surging future end-of-life battery volumes, recyclers must consider further semi-destructive disassembly approaches besides unscrewing. Laser cutting shows strong economic potential for high-volume top cover removal. Ultimately, this work provides data-driven guidance for recyclers on selecting the most economically viable disassembly technology for removing top covers based on the intended disassembly volume.