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Material parameter analysis of lithium-ion battery based on laboratory X-ray computed tomography.

Authors :
Hou, Junwei
Wang, Hailin
Qi, Long
Wu, Weichuang
Li, Lifu
Lai, Rongguang
Feng, Xiaoming
Gao, Xiang
Wu, Weibin
Cai, Weizi
Source :
Journal of Power Sources. Nov2022, Vol. 549, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

Accurate analysis of electrode material parameters is of great significance for advancing Lithium-ion battery research. This paper presents the first application of the laboratory X-ray computed tomography (CT) technique for the material parameter analysis of rectangular lithium iron phosphate (LFP) battery. Firstly, performing a disassembly experiment of rectangular LFP battery, the geometric size of positive and negative electrodes and the heterogeneity of materials are analyzed. Secondly, a sine function model is proposed to identify the 2D tomographic images representing the positive and negative electrodes from the reconstructed 3D dataset. Then, the histograms of the 2D tomographic images are fitted with a Gaussian function to identify and quantify the content of electrode materials. Finally, the distributions of positive and negative materials are quantified by meshing and contour plots. The positive and negative materials are unevenly distributed on current collectors, and their distribution properties are closely related to the distance between the electrodes and the thickness center of the wound prismatic cell. The locations of the low aggregation regions of the positive and negative materials are not consistent. It can be expected that this paper will provide a new insight into the analysis of 3D imaging of electrode materials before/after battery operation. • A sine function model is constructed to identify the 2D tomographic images of electrodes. • Using a Gaussian function identify and quantify the content of electrode materials. • Using meshing and contour plots quantify the distribution of electrode materials. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03787753
Volume :
549
Database :
Academic Search Index
Journal :
Journal of Power Sources
Publication Type :
Academic Journal
Accession number :
159476059
Full Text :
https://doi.org/10.1016/j.jpowsour.2022.232131