Analysis of Lithium‐Ion Battery State and Degradation via Physicochemical Cell and SEI Modeling

Abstract

The quality of lithium-ion batteries is affected by the formation of the solid electrolyte interphase (SEI). For a better understanding of its effect on cell performance and aging, fast and economically scalable SEI diagnostics are indispensable. Battery models promise to extract hardly accessible interfacial and bulk properties of the SEI from electrochemical impedance spectra and discharge data. The common analysis of only one measurement, often with empirical models, impedes a precise localization of degradation-related and performance-limiting proc-esses. This work offers a solution by combining physicochemical SEI and cell modeling for the joint analysis of both measurement types. Our analysis highlights the minor importance of the SEI ionic conductivity for cell performance along with a significant improvement and notable effect of its interfacial properties along aging. Such a detailed understanding of the initial SEI and its evolution over time could enable, e. g., a knowledge-based optimization of the cell formation process.

Species Distribution During Solid Electrolyte Interphase Formation on Lithium Using MD/DFT-Parameterized Kinetic Monte Carlo Simulations

“…Results from the simulated SEI species distribution may be used in future to determine the conductivity and thus the resistance of the SEI. However, the vice versa calculation of SEI composition from a high frequency resistance value from impedance spectra is not feasible . The consumption of the anode leads to a capacity loss of roughly 6.69 nobreak0em0.25em⁣ mAh normalm 2 .…”

“…However, physicochemical parameters are extractable for usage in models of longer time scales. A further group of SEI models is taking a macroscopic view and use continuum and mean-field models which do not resolve stochastic molecular processes but use mean-field approaches. , Clusters or other heterogeneities in the SEI are not covered by such models and thus cannot give an in-depth perspective …”

“…A further group of SEI models is taking a macroscopic view and use continuum and mean-field models which do not resolve stochastic molecular processes but use mean-field approaches. 18,35 Clusters or other heterogeneities in the SEI are not covered by such models and thus cannot give an indepth perspective. 36 A modeling methodology bridging the scale of molecular and continuum, i.e., macroscopic modeling, is essential to understand formation of the heterogeneous SEI structure including clusters.…”

Data Specifications for Battery Manufacturing Digitalization: Current Status, Challenges, and Opportunities

“…Continuum models based on the Newman approach typically consider electrochemical parameters to predict the SEI thickness evolution [60,176,177] …”

A Review and Perspective on Path Dependency in Batteries

“…[ 47 ] This approach further enables detailed characterization of single degradation processes such as the degradation of the SEI. [ 48 ] Beyond that, also data‐driven estimation of SOH is a possible alternative, which was reviewed by Li et al [ 49 ] As described earlier, EIS and NFRA are useful methods to depict lithium‐ion battery degradation. In contrast to DVA and ICA, these measurements are less time‐consuming.…”