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Electrochemical Impedance Spectroscopy measurements and simulations are performed on a nickel manganese cobalt oxide (NMC)/graphite pouch cell. A physico-chemical continuum battery model is extended by a physical ageing model including a Solid Electrolyte Interphase. The model assumes a loss of electrochemically active surface area at anode and cathode as well as a growth of solid electrolyte interphase (SEI) layer thickness. These ageing parameters have been adjusted with an algorithm to achieve agreement between simulated and measured spectra. The results for a 28 mAh pouch cell show that the ageing model is suitable to correlate the change of the impedance spectrum with the degree of degradation of the cell. In detail, SEI thickness is shown to increase by 45 nm, while the anode and cathode loose 20 % and 57 % of their electrochemically active surface area, respectively. In addition, deviating measurement conditions and the end of life of the cell can be indicated by the parameter identification algorithm. Furthermore, it is demonstrated, that the change of the high and low frequency semicircles can be assigned to the anode SEI and cathode respectively.

All‐solid‐state batteries currently have the disadvantage of low conductivity of the solid electrolytes (SEs) at room temperature and have issues with nonutilized active material (AM) and high reaction overpotentials due to a low SE/AM interface area. These limitations are partially due to the material properties because of the complex, yet nonoptimal production process. Therefore, a model‐based investigation of the influence of microstructural properties on the electronic and ionic conductivities of all‐solid‐state electrodes is conducted. The objective of this work is to highlight the optimization potential of the mixing and premixing of AM, SE, and conducting additive. The results show that the premixing of AM and conducting additives increases the effective electronic conductivity compared with that of the nonpremixed electrodes. It allows a significantly lower additive volume fraction as the percolation threshold of the conducting additive network reaches earlier. Conducting additives are shown to decrease the effective ionic conductivity by increasing the tortuosity of the microstructures, an effect which can be reduced by premixing the conducting additive and SE.

Evidence for multiscale interaction of processes during surface film growth is provided using a multiscale modeling approach. The model directly couples a continuum pseudo two dimensional (P2D) battery model and a heterogeneous surface film growth model based on the kinetic Monte Carlo (kMC) method. Key parameters have been identified at basic electrochemical experiments, i. e., open circuit potential (OCP), C‐rate tests, and potential during filmformation. Simulations are in very good agreement with these experiments. Simulation results are shown for various formation procedures, i. e., for different applied C‐rates. Interaction between macroscopic transport processes on electrode scale and elementary reaction steps on atomistic scale are observed. Results reveal a distinct impact of the applied procedures on the atomistic structure of surface films. It can be seen that locally heterogeneous films are formed with very slow charging rate due to stochasticity of the growth process, while spatially heterogeneous films are formed with very fast charging rate due to the spatial heterogeneous distribution of concentration and potential. Therefore, the author's emphasize that in order to identify charging protocols for optimal film morphology multiscale interactions should be considered.

A model‐based uncertainty quantification (UQ) approach is applied to the manufacturing process of lithium‐ion batteries (LIB). Cell‐to‐cell deviations and the influence of sub‐cell level variations in the material and electrode properties of the cell performance are investigated experimentally and via modeling. The electrochemical battery model of the Doyle–Newman type is extended to cover the effect of sub‐cell deviation of product properties of the LIB. The applied model is parameterized and validated using a stacked pouch cell containing Li(Ni1/3Co1/3Mn1/3)O2 (NMC) and graphite (LixC6). It is integrated into a sampling‐based UQ framework. A nested point estimate method (PEM) is applied to a large number of independent normal distributed parameters. The simulations follow two consecutive nonideal manufacturing process steps: coating and calendering. The nested PEM provides a global sensitivity analysis that shows a change in sensitivity of the investigated parameters depending on the applied C‐rate. Furthermore, the sub‐cell level deviation of parameters in heterogeneous electrodes provokes a nonuniform current distribution in the cell. This alters the variance of the discharge capacity distribution. Therefore, sub‐cell deviation has to be considered to quantify process uncertainties. The applied method is feasible and highly efficient for this purpose.