Title

Assessment of the automation potential of electric vehicle battery disassembly

Document Type

Article

Date of Original Version

4-1-2021

Abstract

Electric vehicles (EV) offer an environment friendly solution to transportation and there are predictions for high sales of EVs in future. The most expensive parts of those vehicles are their batteries which need to be recycled after use. Currently, there are major challenges in disassembling and recycling EV batteries due to the large variety of types, sizes and design complexity. This paper provides a brief summary on current studies for the disassembly of EV batteries as well as the assessment of automation potential for EV battery disassembly steps. A 2017 Chevrolet Bolt battery was used to generate a disassembly graph, which shows connections and constraints of all parts and fasteners, and a 46-step disassembly sequence. An automation assessment of the 2017 Chevrolet Bolt battery and Audi Q5 battery was conducted on all the steps to determine, based on two categories, the technical possibility and the necessity of automating a given disassembly step. To score these different steps, which could range from a -100 to 100, an easy-to-use criteria catalog was developed and applied on these batteries. This criteria catalog consisted of a total of ten criteria, five criteria for the technical possibility to automate the step and five criteria for the necessity to automate that step. Disassembly steps that score above 50 for the technical ability to automate and had a positive necessity of automating score are steps that should be automated. The scores generated for both batteries showed that most of the unscrewing operations should be automated while most of the lifting operations should be performed by human workers. The results from the automation assessment of the Audi Q5 battery compared similarly to approaches found in literature but was able to produce more extreme scorings because of the simplified criteria catalog. The work presented in this paper gives an approach to assess the automation potential of a given disassembly step in any EV battery.

Publication Title

Journal of Manufacturing Systems

Volume

59

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