A two steps method for electrochemical impedance modeling using fractional order system in time and frequency domains

Eddine, Achraf Nasser; Huard, Benoît; Gabano, Jean-Denis; Poinot, Thierry

doi:10.1016/j.conengprac.2019.03.001

Cited by 36 publications

(12 citation statements)

References 34 publications

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“…Equation (10) only uses integer derivatives at the initial time, so it is easier to apply in practice. However, the inability of the Caputo definition to provide a satisfactory solution to the initial condition problem has been pointed out [13,15], and we comment on it below.…”

Section: Fractional Derivativesmentioning

confidence: 99%

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Constant Phase Element in the Time Domain: The Problem of Initialization

López‐Villanueva

Rodríguez‐Bolívar

2022

Energies

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The constant phase element (CPE) is found in most battery and supercapacitor equivalent circuit models proposed to interpret data in the frequency domain. When these models are used in the time domain, the initial conditions in the fractional differential equations must be correctly imposed. The initial state problem remains controversial and has been analyzed by various authors in the last two decades. This article attempts to clarify this problem by proposing a procedure to prepare the initial state and defining a decay function that reveals the effect of the initial state in several illustrative examples. This decay function depends on the previous history, which is reflected in the time needed to prepare the initial state and on the current profile assumed for this purpose. This effect of the initial state is difficult to separate and can lead to the misinterpretation of the CPE parameter values.

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Section: Fractional Derivativesmentioning

confidence: 99%

“…There is interest in applying these models in the time domain [2,3,[8][9][10] where the impedance (2) corresponds to a fractional derivative, as shown in (3), which is discussed in the next section.…”

Section: Introductionmentioning

confidence: 99%

Constant Phase Element in the Time Domain: The Problem of Initialization

López‐Villanueva

Rodríguez‐Bolívar

2022

Energies

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“…It should be noted that the low frequency area with the only Warburg impedance is incomplete. If lower frequency is considered, the EIS of diffusion process in low frequency area is actually a semicircle [17]. Because of the long period of EIS measurement in the ultra-low frequency band, only the Warburg impedance at the linear part of low frequency band is generally measured.…”

Section: Modelling Of a Fractional Order Equivalent Circuit Model Of mentioning

confidence: 99%

A novel online identification algorithm of lithium‐ion battery parameters and model order based on a fractional order model

Sun

Ren

et al. 2021

IET Renewable Power Gen

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A fractional order equivalent circuit model with variable order can better reflect the internal reaction mechanism of a lithium-ion battery, however, it is not easy to simultaneously identify the parameters and order of the fractional order model online. In this paper, based on the electrochemical impedance spectroscopy of the lithium-ion battery, the FOM and its discretization are analysed in detail, and a fractional order repeated prediction recursive least square (FORPRLS) method is proposed, the approximate error of fractional derivative is corrected by the repeated identification process with changing the order, so that the parameters and order of the fractional order model can be identified online and accurately at the same time. For the second-order RC equivalent circuit model and fractional order model, different online identification algorithms including the forgetting factor recursive least square and FORPRLS are carried out under the dynamic stress test experiment, and the predicted terminal voltages are compared with the actual measured terminal voltages to judge the identification accuracy of these algorithms. The experimental results verify that the FORPRLS algorithm is superior to the FFRLS algorithm, and the identified order can better match the reaction process of the lithium-ion battery.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…8 The equivalent circuit model (ECM) is currently the most widely used. 9 Because the battery voltage changes rapidly at the beginning and end of charging and discharging, it is difficult to accurately simulate the strong nonlinearity of the battery through ECM. In n-order RC, ECMs can improve their accuracy by increasing the number of RC network modules, but this will make the model structure more complex, greatly increase the amount of calculation, and bring difficulties to model parameter identification and practical applications.…”

Section: Introductionmentioning

confidence: 99%

A novel combined estimation method of online full‐parameter identification and adaptive unscented particle filter for Li ‐ion batteries SOC based on fractional‐order modeling

Chen

Wang

Jiang

et al. 2021

Intl J of Energy Research

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Accurate estimation of the state of charge (SOC) of Li-ion battery can ensure the reliability of the storage system. A combined estimator of online fullparameter identification and adaptive unscented particle filter for Li-ion battery SOC based on an improved fractional-order model is proposed, which overcomes the shortcomings of the traditional SOC cumulative error and the difficulty of OCV acquisition. The proposed adaptive fractional unscented particle filter algorithm introduces fractional parameters as hidden parameters and reduces the complexity of the algorithm iteration by reducing the number of particles. At the same time, the noise adaptive algorithm based on the residual sequence can solve the divergence problem of the filter and improve the adaptability of the algorithm. To verify the feasibility of the algorithm under complex operating conditions, the urban dynamometer driving schedule dynamic working conditions of Li-ion batteries are verified. The experimental results show that the evaluation index of the algorithm is the best, the RMSE is 0.67%, and the SOC estimation is more accurate. It shows that the algorithm has strong robustness and fast convergence. K E Y W O R D Sadaptive fractional-order unscented particle filter, full-parameter identification, improve fractional-order equivalent circuit model, Li-ion battery, state of charge

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A two steps method for electrochemical impedance modeling using fractional order system in time and frequency domains

Cited by 36 publications

References 34 publications

Constant Phase Element in the Time Domain: The Problem of Initialization

Constant Phase Element in the Time Domain: The Problem of Initialization

A novel online identification algorithm of lithium‐ion battery parameters and model order based on a fractional order model

A novel combined estimation method of online full‐parameter identification and adaptive unscented particle filter for Li ‐ion batteries SOC based on fractional‐order modeling

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