DemoSens

The BMBF-funded joint project DemoSens - Digitalization of automated dismantling and sensor-based mechanical processing of lithium-ion batteries for high-quality recycling - aims to comprehensively digitalize and automate the recycling of lithium-ion batteries from electric vehicles along the entire process chain from dismantling and sorting to mechanical processing. The project is assigned to the BMBF competence cluster Recycling / Green Battery.


Within the project, the Institute for Enterprise Cybernetics (IfU) is developing, testing and implementing machine learning methods for the automated disassembly of EV battery systems by self-learning robot systems. The goal is to further develop previously existing algorithms based on machine learning so that robot-assisted disassembly can be adaptive and generalizable to subcomponents of the EV battery system. The developed adaptive algorithms will be pre-validated within a micro-demonstrator and subsequently transferred to the pilot plant.

Keyfacts
Funding Body
BMBF
Consortium Leader
Institut für Infrastruktur ∙ Wasser ∙ Ressourcen ∙ Umwelt (IWARU) – FH Münster
Project Partner
Institut für Metallurgische Prozesstechnik und Metallrecycling (IME), Institut für Unternehmenskybernetik e.V. (IfU) und Production Engineering of E-Mobility Components (PEM), (alle RWTH Aachen University)
Project Holder
Jülich
Project Duration
01.10.2020 – 30.09.2023
Contact Christoph Henke, M.Sc.Forschungsgruppenleiter
Room
D 2.15
Phone
+49 241 92782250

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