Distribution of Relaxation Times Analysis for Impedance Spectra Containing Resistive-Inductive Characteristics: Part I. Deconvolution Methods

The distribution of relaxation times analysis is a powerful and non-destructive technique based on electrochemical impedance spectroscopy to analyze and identify electrochemical reactions and processes in batteries, fuel cells, and other electrochemical systems. However, there are inherent challenges to this analysis method that affect the accuracy of the results and impede their interpretation, particularly when capacitive, inductive or resistive-inductive characteristics are present. In this case, data truncation is often used, which leads to incorrectly identified time constants and polarization contributions as well as an ohmic offset. An approach that is capable of analyzing arbitrary spectra and determining the true ohmic offset is presented and applied to three algorithms to evaluate the influence of different regularization techniques: the generalized DRT analysis, the VanCittert algorithm and the separated sparse spike deconvolution. To validate the results, they are compared to the electrochemical system analysis (ELSA), which is a complementary data-driven method. It can be demonstrated that the proposed approach efficiently handles resistive-capacitive and resistive-inductive effects without requiring any non-negativity constraint for the parameters nor data truncation and without adding complexity.