Time-Efficient Reparameterization and Simulation of Manufacturing Impacts on Performance of Lithium-Ion-Batteries

The high quality demands of batteries for electric vehicles require powerful tools for error detection in cell manufacturing. Furthermore, cell diagnostics is a serious challenge because performance limitations occur on atomic scale and as batteries are closed systems physical issues can hardly be detected only with the aid of experimental methods. Physico-chemical models enable to detect up to seven various mechanisms of limitations but experimental parameterization is extensive. Therefore, in this study a fast mathematical parameterization approach was used to simulate and diagnose cells with various manufacturing parameter configurations. Limitation mechanisms are shown in correlation with impacts by calendering, electrode thickness, carbon black recipe and cathode active material. Depending on the adjusted production parameters, they vary between low electronic conductivity, overpotentials due to reduction of electrochemically active solid-liquid interfacial area and lowionic conductivity. Furthermore it is shown that characteristic indicators for the particular limitationmechanisms can be observed in discharge curves at various C-Rates. Finally, a statistical analysis demonstrates how parameter identification can be performed computationally as a side product from reparameterization.