Deformation measurement within lithium-ion battery using sparse-view computed tomography and digital image correlation. (1st February 2023)

• Record Type: Journal Article
• Authors: Wu, Yapeng; Sun, Liang; Zhang, Xiangchun; Yang, Min; Tan, Dalong; Hai, Chao; Liu, Jing; Wang, Juntao
• Is Part Of: Measurement science & technology. Volume 34:Number 2(2023)
• Publication Date: 2023-02-01
• Subjects: lithium-ion battery -- sparse-view -- computed tomography -- SVRNet -- digital image correlation; Physical measurements -- Periodicals; Scientific apparatus and instruments -- Periodicals; Equipment and Supplies -- Periodicals; Science -- instrumentation -- Periodicals; Technology -- instrumentation -- Periodicals; Mesures physiques -- Périodiques; Physical measurements; Scientific apparatus and instruments; Periodicals; 502.87
• DOI: 10.1088/1361-6501/ac9c21
• Languages: English
• ISSNs: 0957-0233

Abstract

Abstract: Electrode deformation can cause high local strain and serious capacity degradation in lithium-ion batteries (LIBs) during cycling. Risk reduction in many applications requires an understanding of the effects of the charging/discharging rate on the electrode structure during the battery life cycle. Cyclic charging/discharging experiments of wound 18 650 cylindrical LIBs were conducted at different charging/discharging rates (1C and 2C) to determine the effect of rate on electrode deformation. The charging/discharging capacity as well as battery voltage and time were analyzed during cycling. To acquire electrode deformation images and meet the requirements of computed tomography (CT) within 2 min during the charging/discharging process, sparse-view CT was performed at fixed cycle intervals. Subsequently, a sparse-view reconstruction network was proposed to generate a slice image. Finally, the electrode displacement and strain fields were calculated using the augmented Lagrangian digital image correlation algorithm. The causes of electrode deformation were analyzed and discussed from the perspective of molecular and macroscopic structure. Experimental results show that the structural similarity, peak signal-to-noise ratio and root mean square error in the reconstructed image of the axial section within the battery obtained via the proposed network were 0.9616, 38.7411 dB and 0.0108, respectively, which were better than the other methods of comparison. After 100 cycles, the capacity decay of the battery at 2C was 9.23-fold higher than that at 1C. After 100 cycles at 2C, the maximum displacement of the electrode reached 0.46 mm along the x -direction. The electrode structural deformation of the battery can be intuitively understood at different rates, which facilitates reasonable utilization and structural optimization of the battery.