A Protocol for Predicting Lithium-Ion Battery Performances Reflecting the Three-Dimensional Structure of Electrodes

Abstract

As social needs for higher capacity and longer life of lithium-ion batteries increase, shortening the period from research to development and commercialization of batteries has become an extremely important issue. To minimize the above period, a protocol for predicting the performances of (lithium-ion) batteries is highly urged for. Many reports have been published so far regarding the simulation technology of charge-discharge profiles of lithium-ion batteries.1,2 However, in most of simulations, the porous structure of lithium-ion battery electrodes is simplified into a 1D or 2D models. To achieve more accurate battery performance prediction, we adopted the actual 3D structure of the positive and negative electrodes of lithium-ion batteries in simulations.A plasma FIB SEM (Helious5, Thermofisher Scientific Inc.) was used to obtain the 3D structures of the positive and negative electrodes of the lithium-ion battery. The porosity and tortuosity of the electrodes were calculated by reconstructing a 3D image and performing image analysis. Based on this 3D structure, we also calculated the lithium ion conductivity in the electrode. The obtained 3D structural parameters were applied to the simulation of battery characteristics and compared with actual charge/discharge test results. We have also developed a performance prediction protocol that allows to reflect the measured physical properties of battery materials in the simulation.Figure 1 shows cross-sectional images of two different high-nickel-type positive electrodes prepared under different experimental conditions. It can be seen that the active materials are packed densely for both the electrodes, but the level of conductive carbon and binder dispersion is different. The particle size distribution of the active materials was also found to be largely different between the two samples. Structural parameters were obtained from the 3D structure by image analysis, and highly accurate performance prediction was performed. It can be predicted that the rate capability reflects the structural homogeneity. Also, the simulation revealed that the particle size distribution plays an important role for achieving favorable rate capability. Acknowledgement This work was financially supported by the NEXT Center of Innovation Program (COI-NEXT, Grant Number JPMJPF2016) of the Japan Science and Technology Agency. References (1) M Doyle , J. Newman, A. S. Gozdz, C . N. Schmts, and M. Tarascon, J. Electrochem. Soc. 1996, 143, 1890(2) G. Li and C. W. Monroe, Annu. Rev. Chem. Biomol. Eng. 2020, 11 277. Figure 1