Study on correlation with SOH and EIS model of Li-ion battery

Wang, Haiying; He, Long; Sun, Jianhua; Shuanquan, Liu; Wu, Feng

doi:10.1109/ifost.2011.6021018

Cited by 17 publications

(6 citation statements)

References 2 publications

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“…Due to its higher accuracy when compared to alternate methods, and the fact that the EIS method allows determination of both the SoC and the SoH by one test containing an AC frequency sweep, the EIS method was chosen for this work and further work to be completed at a later date. The EIS method works by measuring the impedance of the cell through a range of AC signals at varying frequency (Haiying et al 2011). The measured impedance can be displayed in a Nyquist plot as seen in Figure 1.…”

Section: Eis Methodologymentioning

confidence: 99%

Advanced EIS Techniques for Performance Evaluation of Li-ion Cells

Thanapalan

Bowkett²,

Williams³

et al. 2014

IFAC Proceedings Volumes

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Section: Eis Methodologymentioning

confidence: 99%

Advanced EIS Techniques for Performance Evaluation of Li-ion Cells

Thanapalan

Bowkett²,

Williams³

et al. 2014

IFAC Proceedings Volumes

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“…Figure 3 shows the structure proposed by Wang, He, Sun, Liu, and Wu (2011) for the equivalent model of the internal impedance of a Li-ion battery. In their work, the authors use the following elements: a resistor that represents the resistance of the electrolyte, two RC-parallel branches to represent the negative and positive pole.…”

Section: Empirical Modelsmentioning

confidence: 99%

Guidelines for the Characterization of the Internal Impedance of Lithium-Ion Batteries in PHM Algorithms

Pérez

Benavides

Rozas

et al. 2020

IJPHM

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This article aims to describe the most important aspects to consider when using the concept of internal impedance in algorithms that focus on characterizing the degradation of lithium-ion (Li-ion) batteries. The first part of the article provides a literature review that will help the reader understand the concept of electrochemical impedance spectroscopy (EIS) and how Li-ion batteries can be represented through electrochemical or empirical models, in order to interpret the outcome of typical discharge and/or degradation tests on Li-ion batteries. The second part of the manuscript shows the obtained results of an accelerated degradation experiment performed under controlled conditions on a Li-ion cell. Results show that changes observed on the EIS test can be linked to battery degradation. This knowledge may be of great value when implementing algorithms aimed to predict the End-of-Life (EoL) of the battery in terms of temperature, voltage, and discharge current measurements. The purpose of this article is to introduce the reader to several types of Li-ion battery models, and show how the internal impedance of a Li-ion battery is a dynamic parameter that depends on different factors; and then, illustrate how the EIS can be used to obtain an equivalent circuit model and how the different electronic components vary with the use given to the battery.

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“…This task is not easy due to the nonlinearities present due to the internal chemical processes. In Haiying et al 29 a frequency-based method to determine the internal impedance is presented. In this case, the authors prove that there is a direct linear relationship between the internal impedance and the SOH, in the frequency domain.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Characterization of the degradation process of lithium-ion batteries when discharged at different current rates

Pérez

Quintero

Jaramillo

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part I:

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The use of energy storage devices, such as lithium-ion (Li-ion) batteries, has become popular in many different domains and applications. Hence, it is relatively easy to find literature associated with problems of battery state-of-charge estimation and energy autonomy prognostics. Despite this fact, the characterization of battery degradation processes is still a matter of ongoing research. Indeed, most battery degradation models solely consider operation under nominal (or strictly controlled) conditions, although actual operating profiles (including discharge current) may differ significantly from those. In this context, this article proposes a Li-ion battery degradation model that incorporates the impact of arbitrary discharge currents. Also, the proposed model, initially calibrated through data reported for a specific Li-ion battery type, can characterize degradation curves for other Li-ion batteries. Two case studies have been carried out to validate the proposed model, initially calibrated by using data from a Sony battery. The first case study uses our own experimental data obtained for a Panasonic Li-ion cell, which was cycled and degraded at high current rates. The second case study considers the analysis of two public data sets available at the Prognostics Center of Excellence of NASA Ames Research Center website, for batteries cycled using nominal and 2-C (twice the nominal) discharge currents. Results show that the proposed model can characterize degradation processes properly, even when cycles are subject to different discharge currents and for batteries not manufactured by Sony (whose data was used for the initial calibration).

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Study on correlation with SOH and EIS model of Li-ion battery

Cited by 17 publications

References 2 publications

Advanced EIS Techniques for Performance Evaluation of Li-ion Cells

Advanced EIS Techniques for Performance Evaluation of Li-ion Cells

Guidelines for the Characterization of the Internal Impedance of Lithium-Ion Batteries in PHM Algorithms

Characterization of the degradation process of lithium-ion batteries when discharged at different current rates

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