A Consistent Derivation of the Impedance of a Lithium-Ion Battery Electrode and its Dependency on the State-of-Charge

Schönleber, Michael; Uhlmann, Christian; Braun, Philipp; Weber, André; Ivers‐Tiffée, Ellen

doi:10.1016/j.electacta.2017.05.009

Cited by 72 publications

(48 citation statements)

References 19 publications

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“…Schönleber et al [15] derived the impedance of a LIB electrode from the intercalation reaction of lithium and studied its dependency on SOC, and the results showed that the electrolyte diffusion impedance is independent of the SOC. Huang et al [16] systematically analyzed how different SOCs of 7.5~93.0% can influence battery impedance, and the results indicated that both charge transfer resistance and diffusion resistance increased dramatically when SOC is below 26.5%.…”

Section: Introductionmentioning

confidence: 99%

Impedance Characterization and Modeling of Lithium-Ion Batteries Considering the Internal Temperature Gradient

2018

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Battery impedance is essential to the management of lithium-ion batteries for electric vehicles (EVs), and impedance characterization can help to monitor and predict the battery states. Many studies have been undertaken to investigate impedance characterization and the factors that influence impedance. However, few studies regarding the influence of the internal temperature gradient, which is caused by heat generation during operation, have been presented. We have comprehensively studied the influence of the internal temperature gradient on impedance characterization and the modeling of battery impedance, and have proposed a discretization model to capture battery impedance characterization considering the temperature gradient. Several experiments, including experiments with artificial temperature gradients, are designed and implemented to study the influence of the internal temperature gradient on battery impedance. Based on the experimental results, the parameters of the non-linear impedance model are obtained, and the relationship between the parameters and temperature is further established. The experimental results show that the temperature gradient will influence battery impedance and the temperature distribution can be considered to be approximately linear. The verification results indicate that the proposed discretization model has a good performance and can be used to describe the actual characterization of the battery with an internal temperature gradient.

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Section: Introductionmentioning

confidence: 99%

Impedance Characterization and Modeling of Lithium-Ion Batteries Considering the Internal Temperature Gradient

2018

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“…Simulated battery control strategy development necessitates a plant model representative of real battery behavior. This includes modelling nonlinear dependencies on parameters [1], [2] and a highly dynamic voltage response including a range of time constants spanning several orders of magnitude [2]- [4]. With rapid evolution of cell capabilities, having an easily calibrated model adaptable to different cells is essential for long-term usefulness.…”

Section: Introductionmentioning

confidence: 99%

“…When using an ECM approach, it is important to consider the underlying causes behind cell resistance. These are complex, being present in both electrodes, electrode surface layers [28], electrolyte [2], [4] and current collectors [29]. These contributions vary significantly in both magnitude and response time to current application [3], [4], and their dependency on usage conditions such as temperature, current and State of Charge (SoC) [1], [4], [21], [30]- [32].…”

Section: Introductionmentioning

confidence: 99%

Universal Li-Ion Cell Electrothermal Model

Stocker

Mumtaz

Paramjeet

et al. 2021

IEEE Trans. Transp. Electrific.

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“…The EIS provides the frequency-dependent impedance of an electrochemical system by applying a sinusoidal current, measuring the voltage response (galvanostatic EIS) or vice versa (potentiostatic EIS), and applying Ohm's law. The impedance spectra are interpreted regarding their high-frequency inductive behavior [11] caused by geometry, wiring and the test setup, their low-frequency diffusion behavior [12] and mainly their interphase behavior. Numerous studies focus on battery impedance, e.g., correlating aging to changes in the impedance spectrum [13] or explaining the relaxation behavior in graphite anodes [14].…”

Section: Introductionmentioning

confidence: 99%

Optimized Process Parameters for a Reproducible Distribution of Relaxation Times Analysis of Electrochemical Systems

et al. 2019

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The distribution of relaxation times (DRT) analysis offers a model-free approach for a detailed investigation of electrochemical impedance spectra. Typically, the calculation of the distribution function is an ill-posed problem requiring regularization methods which are strongly parameter-dependent. Before statements on measurement data can be made, a process parameter study is crucial for analyzing the impact of the individual parameters on the distribution function. The optimal regularization parameter is determined together with the number of discrete time constants. Furthermore, the regularization term is investigated with respect to its mathematical background. It is revealed that the algorithm and its handling of constraints and the optimization function significantly determine the result of the DRT calculation. With optimized parameters, detailed information on the investigated system can be obtained. As an example of a complex impedance spectrum, a commercial Nickel–Manganese–Cobalt–Oxide (NMC) lithium-ion pouch cell is investigated. The DRT allows the investigation of the SOC dependency of the charge transfer reactions, solid electrolyte interphase (SEI) and the solid state diffusion of both anode and cathode. For the quantification of the single polarization contributions, a peak analysis algorithm based on Gaussian distribution curves is presented and applied.

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A Consistent Derivation of the Impedance of a Lithium-Ion Battery Electrode and its Dependency on the State-of-Charge

Cited by 72 publications

References 19 publications

Impedance Characterization and Modeling of Lithium-Ion Batteries Considering the Internal Temperature Gradient

Impedance Characterization and Modeling of Lithium-Ion Batteries Considering the Internal Temperature Gradient

Universal Li-Ion Cell Electrothermal Model

Optimized Process Parameters for a Reproducible Distribution of Relaxation Times Analysis of Electrochemical Systems

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