Nonlinear Electrochemical Impedance Spectroscopy for Lithium-Ion Battery Model Parameterization

In this work we analyze the local nonlinear electrochemical impedance spectroscopy (NLEIS) response of a lithium-ion battery and estimate model parameters from measured NLEIS data. The analysis assumes a single-particle model including nonlinear diffusion of lithium within the electrode particles and asymmetric charge transfer kinetics at their surface. Based on this model and assuming a moderately-small excitation amplitude, we systematically derive analytical formulae for the impedances up to the second harmonic response, allowing the meaningful interpretation of each contribution in terms of physical processes and nonlinearities in the model. The implications of this for parameterization are explored, including structural identifiability analysis and parameter estimation using maximum likelihood, with both synthetic and experimentally measured impedance data. Accurate fits to impedance data are possible, however inconsistencies in the fitted diffusion timescales suggest that a nonlinear diffusion model may not be appropriate for the cells considered. Model validation is also demonstrated by predicting time-domain voltage response using the parameterized model and this is shown to have excellent agreement with measured voltage time-series data (11.1 mV RMSE).

Automated summary

In this work, the local nonlinear electrochemical impedance spectroscopy (NLEIS) response of a lithium-ion battery is analyzed and model parameters are estimated from measured NLEIS data. The analysis assumes a single-particle model that includes nonlinear diffusion of lithium within the electrode particles and asymmetric charge transfer kinetics at their surface. Analytical formulae for the impedances up to the second harmonic response are systematically derived, allowing the interpretation of each contribution in terms of physical processes and nonlinearities in the model. The validation of the model is demonstrated by predicting time-domain voltage response using the parameterized model, showing excellent agreement with measured voltage time-series data (11.1 mV RMSE).