Physics Based Temperature Dependent EIS Simulation on 18650 NMC/Graphite Cell

Abstract

Electrochemical Impedance Spectroscopy (EIS) is a non-destructive method that provides crucial insights regarding the battery processes. EIS is mainly done by applying a small amplitude AC with a 10 mHz to 1 MHz frequency range. One can determine the electrolyte's ohmic resistance, the Solid Electrolyte Interface (SEI) capacitance, electron transfer rate and the diffusion mechanisms at separate frequency regions from each other.One disadvantage of EIS is the ambiguity of the analyses of the data. The equivalent circuit models used are not unique, and the correspondence between the various elements in the equivalent circuits to electrochemical phenomena are suspect. A new approach on EIS analysis is sought after in order to improve the interpretation. For example, distribution of relaxation times (DRT) was proposed by Zhang et al. in 2015 .Using physics-based models in order to model EIS has been published by Murbach and Schwartz in 2018. In their work, they created a physics-based simulation which uses a pseudo two-dimensional battery model. Their main aim was to present a new approach to EIS data analysis by using a physics-based model rather than equivalent circuit models. They created a data set with 38.800 separate spectra and match the experimental data by using least squares matching approach with the previously computed data. Though this work improved the understanding, multiple calculated data sets matched the experiments with similar errors.Ultimately, in order to achieve an EIS analysis method that is directly related to the fundamental parameters regarding the electrochemistry, degeneracies have to be removed via temperature dependence and the non-linearities as extra dependent variables. This way, the ambiguities and the suspicious parameter assigning can be fixed.We will be reporting on T-dependent linear and nonlinear simulations on 18650 NMC/Graphite battery. All the simulations were done on Python by using a physics-based model PyBaMM (Sulzer, Valentin, et al. "Python battery mathematical modelling (PyBaMM)." Journal of Open Research Software 9.1 (2021).). Impedance data was obtained via simulating voltage as a function of current within 100 µHz to 10 kHz frequency range. Temperature range was set to -25°C to 65°C with 10°C increments. The linear and non-linear impedance is analyzed as a function of temperature. Our results will be compared with experimental temperature dependent linear/nonlinear spectra in order to obtain proper fundamental parameters