Equivalent circuit model analysis on electrochemical impedance spectroscopy of lithium metal batteries

Gao, Peng; Zhang, Cuifen; Wen, Guangwu

doi:10.1016/j.jpowsour.2015.06.032

Cited by 79 publications

(43 citation statements)

References 16 publications

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“…In the literature,ag reat variety of options for modeling Li-ion batteries with electrical equivalent circuits has been presented. [6] The choice of the equivalent circuit depends strongly on the cell chemistry and the detailed characteristics.T herefore no standard modelc an be used for every battery type, [7,8] as the probabilityt hat the model is over-o ru nder-modeled is high. To obtain am odel with an optimalr eproductiono ft he cell characteristics,t he basic structure of ab attery has to be known.A dditionally,a na pproach is needed for thee stimation of the parameters of the equivalentc ircuit.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Lithium‐Ion Battery Models Based on Electrochemical Impedance Spectroscopy

et al. 2016

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This work is an overview of various equivalent circuits (ECs) containing various degrees of detail. The ECs are evaluated in terms of model accuracy and parameterization time for the systematic assignment of an equivalent circuit to application fields. For this purpose, impedance spectra were measured using electrochemical impedance spectroscopy at different states of charge, health and temperatures. Then the parameters of the EC were extracted using the least‐squares method and the Levenberg–Marquardt algorithm. After comparing the simulated to the measured impedance spectrum, a review and assignment of equivalent circuits for potential applications is given. Simple equivalent circuits with a series resistor and a maximum of two resistance–capacitance (RC) elements are ideal for simulations with lower dynamics. Equivalent circuits with up to five RC elements or even a constant‐phase element (CPE) are promising for simulating highly dynamic processes. By using RCPE elements the impedance spectrum can be modeled with the highest accuracy, which is why this type of model should be used for diagnostic purposes.

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Section: Introductionmentioning

confidence: 99%

Analysis of Lithium‐Ion Battery Models Based on Electrochemical Impedance Spectroscopy

et al. 2016

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“…EIS is frequently used for extracting kinetic and transport properties of electrode materials, aging studies, modelling purposes, and determination of SoC and SoH [260][261][262][263][264][265][266][267][268][269][270][271][272]. However, EIS can also be used to measure the internal battery temperature by relating impedance parameters, such as the phase shift, real part, or imaginary part to the temperature.…”

Section: Impedance-based Temperature Measurementsmentioning

confidence: 99%

A review on various temperature-indication methods for Li-ion batteries

et al. 2019

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Temperature measurements of Li-ion batteries are important for assisting Battery Management Systems in controlling highly relevant states, such as State-of-Charge and State-of-Health. In addition, temperature measurements are essential to prevent dangerous situations and to maximize the performance and cycle life of batteries. However, due to thermal gradients, which might quickly develop during operation, fast and accurate temperature measurements can be rather challenging. For a proper selection of the temperature measurement method, aspects such as measurement range, accuracy, resolution, and costs of the method are important. After providing a brief overview of the working principle of Li-ion batteries, including the heat generation principles and possible consequences, this review gives a comprehensive overview of various temperature measurement methods that can be used for temperature indication of Li-ion batteries. At present, traditional temperature measurement methods, such as thermistors and thermocouples, are extensively used. Several recently introduced methods, such as impedance-based temperature indication and fiber Bragg-grating techniques, are under investigation in order to determine if those are suitable for largescale introduction in sophisticated battery-powered applications.

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“…When the temperature becomes higher, the positive material will start decomposing (LiCoO 2 will start decomposing at temperature of about 150 • C, LiNi 0.8 Co 0. 15 Al 0.05 O 2 at about 160 • C, LiNi x Co y Mn z O 2 at about 210 • C, LiMn 2 O 4 at about 265 • C, and LiFePO 4 at about 310 • C) and produce oxygen. When the temperature is above 200 • C, the battery electrolyte will decompose and produce combustible gas [73].…”

Section: State Of the Artmentioning

confidence: 99%

“…According to USABC, today's lithium-ion batteries cannot meet the standards of EVs. At present, lots of scholars, scientists, and engineers are focusing on new battery research such as Li-O 2 batteries [2,7], lithium-sulfur batteries [8][9][10][11][12][13][14], lithium metal batteries [15,16], all-solid-state lithium batteries [17], al-ion batteries [18], fuel cells [19][20][21][22], supercapacitors [23,24], and so on. Electric vehicles require a high power and…”

Section: Introductionmentioning

confidence: 99%

State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles

et al. 2018

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Sate of charge (SOC) accurate estimation is one of the most important functions in a battery management system for battery packs used in electrical vehicles. This paper focuses on battery SOC estimation and its issues and challenges by exploring different existing estimation methodologies. The key technologies of lithium-ion battery state estimation methodologies of the electrical vehicles categorized under five groups, such as the conventional method, adaptive filter algorithm, learning algorithm, nonlinear observer, and the hybrid method, are explored in an in-depth analysis. Lithium-ion battery characteristic, battery model, estimation algorithm, and cell unbalancing are the most important factors that affect the accuracy and robustness of SOC estimation. Finally, this paper concludes with the challenges of SOC estimation and suggests other directions for possible research efforts.

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Equivalent circuit model analysis on electrochemical impedance spectroscopy of lithium metal batteries

Cited by 79 publications

References 16 publications

Analysis of Lithium‐Ion Battery Models Based on Electrochemical Impedance Spectroscopy

Analysis of Lithium‐Ion Battery Models Based on Electrochemical Impedance Spectroscopy

A review on various temperature-indication methods for Li-ion batteries

State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles

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