A comparative study of different equivalent circuit models for estimating state-of-charge of lithium-ion batteries

Lai, Xin; Zheng, Yuejiu; Sun, Tao

doi:10.1016/j.electacta.2017.10.153

Cited by 330 publications

(145 citation statements)

References 43 publications

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“…At low frequencies, the frozen mass transport of charge carriers in the porous electrodes leads to a more or less constant capacitance. According to Equation (11), the value C = [ω Im Z] −1 , at any given frequency, changes roughly linearly with the state-of-charge (SoC, α), as shown in Figure 2. …”

Section: Impedance Spectramentioning

confidence: 97%

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State-of-Charge Monitoring by Impedance Spectroscopy during Long-Term Self-Discharge of Supercapacitors and Lithium-Ion Batteries

Kurzweil

Shamonin

2018

Batteries

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Frequency-dependent capacitance C(ω) is a rapid and reliable method for the determination of the state-of-charge (SoC) of electrochemical storage devices. The state-of-the-art of SoC monitoring using impedance spectroscopy is reviewed, and complemented by original 1.5-year long-term electrical impedance measurements of several commercially available supercapacitors. It is found that the kinetics of the self-discharge of supercapacitors comprises at least two characteristic time constants in the range of days and months. The curvature of the Nyquist curve at frequencies above 10 Hz (charge transfer resistance) depends on the available electric charge as well, but it is of little use for applications. Lithium-ion batteries demonstrate a linear correlation between voltage and capacitance as long as overcharge and deep discharge are avoided.

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Section: Impedance Spectramentioning

confidence: 97%

“…Therefore, the equivalent circuit provides a leakage resistance in parallel to the capacitance (Figure 1). Under the assumption that this leakage resistance is infinitely large, Equation (10) becomes Equation (11).…”

Section: Frequency Response Of Capacitancementioning

confidence: 99%

State-of-Charge Monitoring by Impedance Spectroscopy during Long-Term Self-Discharge of Supercapacitors and Lithium-Ion Batteries

Kurzweil

Shamonin

2018

Batteries

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“…In fact, the battery transient voltage can be fitted by a function that is the sum of exponential functions with different time constants. As widely documented in the literature, a good compromise between accuracy and computational effort is obtained when two time constants, corresponding to the two RC branches, are considered [46]. However, attention must be paid in the selection of the transient period, as it will be discussed in more detail in the next sections.…”

Section: Battery Modellingmentioning

confidence: 99%

Battery Modelling and Simulation Using a Programmable Testing Equipment

2018

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Abstract:In this paper, the study and modelling of a lithium-ion battery cell is presented. To test the considered cell, a battery testing system was built using two programmable power units: an electronic load and a power supply. To communicate with them, a software/hardware interface was implemented within the National Instruments (NI) LabVIEW environment. This dedicated laboratory equipment can be used to apply charging/discharging cycles according to user defined load profiles. The battery modelling and the parameters identification procedure are described. The model was used to estimate the State Of Charge (SOC) under dynamic loading conditions. The most spread techniques used in the field of battery modelling and SOC estimation are implemented and compared.

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“…Repeating the above operation at the other five temperatures of 10,20,30,40, and 50 °C, we acquire six pairs of , . Then, the correlations of -and -can be approximated by polynomials as…”

Section: Peukert Coefficient Identification Testmentioning

confidence: 99%

Peukert-Equation-Based State-of-Charge Estimation for LiFePO4 Batteries Considering the Battery Thermal Evolution Effect

Xie

2018

Energies

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To achieve accurate state-of-charge (SoC) estimation for LiFePO 4 (lithium iron phosphate) batteries under harsh conditions, this paper resorts to the Peukert's law to accommodate different temperatures and load excitations. By analyzing battery heat generation and dissipation, a thermal evolution model (TEM) is elaborated and exploited for on-line parameter identification of the equivalent circuit model (ECM). Then, a SoC estimation framework is proposed based on the Adaptive Extended Kalman Filter (AEKF) algorithm. Experimental results on a LiFePO 4 pack subject to the Federal Urban Driving Schedule (FUDS) profile under different temperatures and initial states suggest that the proposed SoC estimator provides good robustness and accuracy against changing temperature and highly dynamic loads.

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A comparative study of different equivalent circuit models for estimating state-of-charge of lithium-ion batteries

Cited by 330 publications

References 43 publications

State-of-Charge Monitoring by Impedance Spectroscopy during Long-Term Self-Discharge of Supercapacitors and Lithium-Ion Batteries

State-of-Charge Monitoring by Impedance Spectroscopy during Long-Term Self-Discharge of Supercapacitors and Lithium-Ion Batteries

Battery Modelling and Simulation Using a Programmable Testing Equipment

Peukert-Equation-Based State-of-Charge Estimation for LiFePO4 Batteries Considering the Battery Thermal Evolution Effect

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