Abstract

The aim of this paper is to present an application of the generalized Warburg element and Constant Phase Element (CPE) for non-Fickian diffusion modeling. These distributed elements are intended to provide a better fit of low-frequency impedance data than the standard finite-length Warburg element in the case of most batteries. In addition, the current study demonstrates the ambiguity of the finite-length Warburg element if impedance data is insufficient within the very-low-frequency impedance spectrum. In order to select the appropriate Randles circuit for non-Fickian diffusion modeling, several configurations have been investigated. Based on the best fit of impedance data, the State-of-Charge (SoC) dependency of the Randles circuit parameters has also been analyzed. This study concerns a Samsung ICR18650-26F 2600 mAh battery cell which was subjected to Electrochemical Impedance Spectroscopy (EIS) measurements between 10 mHz and 100 kHz as a function of SoC. The results were plotted and compared in the form of Nyquist plots. The Randles circuit parameters such as the resistances Rs and Rct, double-layer Cdl, leaky capacitance CPE andWarburg coefficients were estimated using ZView software. The present paper shows that CPE – and its QPE form – is a recommended choice to yield the best fit in terms of non-Fickian diffusion impedance. In addition, using CPE is a better alternative to avoid problems with initial values and multiple local solutions, which may exist in the case of the Warburg element. The resultant Randles circuit parameters and their SoC characteristics can be effectively used in further electrochemical modeling.

Highlights

  • The State of Health (SoH) of a battery plays an important role in electric applications since it has a great influence on the available capacity and power of a battery [1]

  • The current work demonstrated an improved method of diffusion modeling

  • Several configurations of Randles circuits were studied in order to obtain the best fit of the impedance characteristics of a battery

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Summary

Introduction

The State of Health (SoH) of a battery plays an important role in electric applications since it has a great influence on the available capacity and power of a battery [1]. A common and reliable electrochemical model used in Finite Element Analysis (FEA) is based on the work of Newman et al [2]. It consists of charge and mass balance equations in both solid (electrode) and liquid (electrolyte) materials, which describe the main operating characteristics of the cell. Even though these formulae could describe the behavior of the cell in 3D, due to their high degree of nonlinearity and complexity, Pseudo-2D (P2D) modeling is favorable in terms of FEA [3].

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