Computer Simulations of the Impedance Response of Lithium Rechargeable Batteries

The active particle morphology and microstructure affect the impedance behavior of intercalation electrodes due to the underlying charge transport, active material/electrolyte interfacial surface area, and solid-phase diffusion in lithium-ion batteries (LIB). In order to capture the impact of the electrode microstructural variability on the impedance response, an integrated electrochemical impedance predictive analysis is presented. In the analysis, stochastically reconstructed 3-D microstructures of representative LIB electrodes are considered with variations in the active material morphology and particle size distribution. With the properties evaluated from the virtual 3-D microstructures, the corresponding impedance response is predicted. The concept of electrochemical Sauter mean diameter (ESMD) has been introduced to investigate the effect of active particle morphology, such as particle agglomeration. This integrated analysis is envisioned to offer a virtual impedance response probing framework to elucidate the influence of electrode microstructural variability and underlying electrochemical and transport interactions. Lithium-ion batteries (LIBs), due to their favorable energy density and power capability, are considered as the candidate of choice for vehicle electrification. [1][2][3][4] To further improve the cell performance, different efforts have been undertaken to study the microstructural characteristics, including electrode thickness, 5 porosity, 6 particle size, 7 conductive additives 8 and composition. 9 Particularly, the influence of electrode microstructure on charge (i.e. electron and ion) transport, and solid-phase diffusion is critical, which ultimately affects the cell performance.One of the powerful methods for analyzing the electrochemical and transport behavior in porous electrodes is the electrochemical impedance spectroscopy (EIS), which measures the response of a small perturbation of potential or current.10-17 By investigating the impedance response, the charge transport resistance, including electron transport in the solid phase, ionic transport in the electrolyte, solid-state diffusion in the active material, and the intercalation process, can be quantified.14,18-26 Meyers et al. proposed a mathematical model to capture the impedance behavior of a spherical active particle dependent on the physical properties related to the faradaic and nonfaradaic impedance.14 The model also included the effect of particle size distribution on the impedance response.The impedance response of intercalation electrodes, which is sensitive to the interfacial processes, the surface morphology, and the charge transport, has been described mathematically by the fundamental physical approach for various electrochemical systems.14,27-39The effect of various properties, such as electrical and ionic conductivity, and layer thickness, have been investigated by Levi and Aurbach. 28 Besides the electrode properties (e.g. electrical conductivity, ionic conductivity, and layer thickness), the electrode microst...

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confidence: 99%

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Influence of Microstructure on Impedance Response in Intercalation Electrodes

Cho

Chen

Mukherjee

2015

“…z E-mail: setzler@gatech.edu literature provides important context and insight, beginning with the work of Doyle et al 9 and Meyers et al…”

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confidence: 99%

A Physics-Based Impedance Model of Proton Exchange Membrane Fuel Cells Exhibiting Low-Frequency Inductive Loops

Setzler

Fuller

2015

A physics-based impedance model of a proton exchange membrane fuel cell is developed, incorporating a coupled oxide growthoxygen reduction reaction kinetic model. The oxide layer is shown to produce a low frequency inductive loop that agrees quantitatively with the experimental inductive loop at current densities as high as 800 mA/cm 2 , even when kinetic and mass-transfer parameters are fit from polarization curves and cyclic voltammetry instead of electrochemical impedance spectroscopy. The importance of the inductive loop in explaining both AC and DC results is discussed. © The Author(s) 2015. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 License (CC BY, http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse of the work in any medium, provided the original work is properly cited. [DOI: 10.1149/2.0361506jes] All rights reserved.Manuscript submitted October 31, 2014; revised manuscript received February 16, 2015. Published March 3, 2015 Electrochemical impedance spectroscopy (EIS) is a widely used technique in proton exchange membrane fuel cells (PEMFCs) that separates differential contributions to cell overpotential by characteristic time constants. Analysis of EIS is difficult because there may be dozens of processes involved. It is standard to analyze EIS using equivalent electrical circuit models of the PEMFC, in which several key processes are represented by circuit elements such as the resistor, capacitor, Warburg element, and constant phase element. Fitting the experimental EIS data with an equivalent circuit model and obtaining circuit parameters is straightforward. Often, a close fit can be achieved with relatively few components, especially when constant phase elements are used. However, the challenge becomes determining which processes to include and converting the electrical circuit parameters back to meaningful cell parameters.Although the basic building blocks of equivalent circuits, for example the Randles circuit, have an exact physical interpretation, these elements are often applied to more complex processes without accounting for the differences. The circuits may fit the data perfectly, but the parameters have lost their original meaning. Often, some transport processes are faster than double layer charging, and as a result, are inseparable from charge-transfer resistance. Additionally, slow transport processes often contribute impedance that scales with chargetransfer resistance, rather than being independent. Unfortunately, it is common in the literature to see circuit parameters reported as results without a translation to meaningful physical parameters.An alternative approach is to model the physical processes occurring in an electrochemical cell during EIS experiments. This approach was pioneered by De Levie, 1 who calculated an analytical solution for the impedance of a porous electrode with a potential gradient, assuming linear kinetics and no concentration gradient. Keddam et al. 2 cons...

“…[5][6][7] Closed-form analytical or symbolic solutions are also presented for such systems but under certain limiting operational and design conditions. Meyers et al 8 presented an analytical solution for the impedance response of a porous intercalation electrode in the absence of solution phase diffusion limitations.…”

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Analytical Expression for the Impedance Response for a Lithium-Ion Cell

Sikha

White

2008

An analytical expression to predict the impedance response of a dual insertion electrode cell (insertion electrodes separated by an ionically conducting membrane) is presented. The expression accounts for the reaction kinetics and double-layer adsorption processes at the electrode-electrolyte interface, transport of electroactive species in the electrolyte phase, and insertion of species in the solid phase of the insertion electrodes. The accuracy of the analytical expression is validated by comparing the impedance response predicted by the expression to the corresponding numerical solution. The analytical expression is used to predict the impedance response of a lithium-ion cell consisting of a porous LiConormalO2 cathode and mesocarbon microbead anode. A qualitative graphical method to identify the co-existence of solid and solution phase transport limitations in the impedance spectra of insertion electrodes is also discussed in the paper.