Model-Based Uncertainty Quantification for the Product Properties of Lithium-Ion Batteries

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)O-2 (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.