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Mechanical Response of Laterally-Constrained Prismatic Battery Cells under Local Loading
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 14, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
The crash safety of lithium-ion batteries has received great attention in recent years because of their growing popularity in electric vehicles. However, the safety issues of prismatic batteries have not been thoroughly studied; in particular, the mechanical responses of prismatic battery cells with lateral constraints under varied loading conditions still remain unclear.
In this study, indentation tests are conducted to study the mechanical response of prismatic battery cells. Fixtures providing lateral constraint which simulates the real packing situation in battery module are designed. Firstly, the effects of lateral constraints on coupled mechanical and electrical responses of prismatic battery cells are analyzed and discussed. Secondly, dynamic indentation tests of prismatic cells with lateral constraints are carried out. The response of the stacked batteries under local loading is revealed. Thirdly, non-destructive X-ray computed tomography imaging technique is employed to detect the fracture patterns in battery cells caused by indentation.
The results of indentation tests indicate that the indentation depth and the peak force for the battery internal failure are affected by the side constraint conditions and the responses of battery cells vary under different loading speeds. Also, the XCT scanning results of the samples clearly show the different levels of internal damage and fracture patterns under varied conditions. The detailed mechanical responses of the prismatic battery cell disclosed in the present study can provide support for modeling and protection of batteries under side impact.
CitationXiao, F., Xing, B., and Xia, Y., "Mechanical Response of Laterally-Constrained Prismatic Battery Cells under Local Loading," SAE Technical Paper 2020-01-0200, 2020, https://doi.org/10.4271/2020-01-0200.
Data Sets - Support Documents
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