重新调整用途
计算机科学
电池(电)
电动汽车
动力传动系统
航程(航空)
系统工程
对象(语法)
汽车工程
弹性(材料科学)
电池容量
电动汽车蓄电池
制造工程
作者
Gerald Bräunig,Dominik Hertel,Sara Menetrey,Kai Kaufmann,Thomas Reuter,Jonas Hummel,Florian Richter
标识
DOI:10.1016/j.procs.2026.02.127
摘要
Advancing electric mobility is essential for meeting worldwide climate objectives. Yet, this advancement will lead to a surge in battery systems, sparking concerns over their sustainable and eco-friendly recycling practices. The disassembly of these systems is a critical step for either recycling or repurposing them. To enhance both cost-effectiveness and operational efficiency, there is a pressing need to automate the disassembly process. Existing disassembly lines highlight the requirement for a system that can adapt to handle multiple battery model variants efficiently. As the number of batteries needing disassembly is expected to grow exponentially with the rise in electric vehicle sales, continuing with current manual methods may soon become impractical. Addressing this challenge, this paper introduces a new approach using artificial intelligence to disassemble a broad range of battery models efficiently down to the module level. The article further elaborates on the integration of the technology into the demonstrator system, including the object and camera-based recognition components, and presents initial training data utilized in the system’s development.
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