| Title |
Robotic Disassembly Platform for Disassembly of a Plug-In Hybrid Electric Vehicle Battery: A Case Study |
| ID_Doc |
22770 |
| Authors |
Qu, M; Pham, DT; Altumi, F; Gbadebo, A; Hartono, N; Jiang, KW; Kerin, M; Lan, FY; Micheli, M; Xu, SH; Wang, YJ |
| Title |
Robotic Disassembly Platform for Disassembly of a Plug-In Hybrid Electric Vehicle Battery: A Case Study |
| Year |
2024 |
| Published |
Automation, 5.0, 2 |
| DOI |
10.3390/automation5020005 |
| Abstract |
Efficient processing of end-of-life lithium-ion batteries in electric vehicles is an important and pressing challenge in a circular economy. Regardless of whether the processing strategy is recycling, repurposing, or remanufacturing, the first processing step will usually involve disassembly. As battery disassembly is a dangerous task, efforts have been made to robotise it. In this paper, a robotic disassembly platform using four industrial robots is proposed to automate the non-destructive disassembly of a plug-in hybrid electric vehicle battery pack into modules. This work was conducted as a case study to demonstrate the concept of the autonomous disassembly of an electric vehicle battery pack. A two-step object localisation method based on visual information is used to overcome positional uncertainties from different sources and is validated by experiments. Also, the unscrewing system is highlighted, and its functions, such as handling untightened fasteners, loosening jammed screws, and changing the nutrunner adapters with square drives, are detailed. Furthermore, the time required for each operation is compared with that taken by human operators. Finally, the limitations of the platform are reported, and future research directions are suggested. |
| Author Keywords |
circular economy; remanufacturing; recycling; waste electrical and electronic equipment; electric vehicle battery; industrial automation; robotic disassembly; robotic operations; unscrewing; vision system; object localisation |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:001254727100001 |
| WoS Category |
Automation & Control Systems |
| Research Area |
Automation & Control Systems |
| PDF |
https://www.mdpi.com/2673-4052/5/2/5/pdf?version=1711980687
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