Online Estimation of State-of-Charge, State-of-Health and Temperature of Supercapacitor

Saha, Pankaj; Khanra, Munmun

doi:10.1109/iscas45731.2020.9180494

Cited by 5 publications

(5 citation statements)

References 28 publications

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“…e validation results show that the fitted results are in good agreement with the actual decay data, and most of the relative errors are within 3%. In the literature [36], an online estimation scheme based on particle filtering (PF) is proposed to estimate the state of health (SOH) of SC by combining the electrical equivalent circuit model (ECM) and thermal model and to monitor the SOH of SC by estimating the equivalent series resistance (ESR) and device capacity in real-time.…”

Section: Model-based Prediction Methodsmentioning

confidence: 99%

Prediction of the Remaining Useful Life of Supercapacitors

Zhao²,

Sun³

et al. 2022

Mathematical Problems in Engineering

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As a new type of energy-storage device, supercapacitors are widely used in various energy storage fields because of their advantages such as fast charging and discharging, high power density, wide operating temperature range, and long cycle life. However, the degradation and failure of supercapacitors in large-scale applications will adversely affect the operation of the whole system. To maximize the efficiency of supercapacitors without damaging the equipment and to ensure timely replacement before reaching the end of their useful life, it is critical to accurately predict the remaining useful life of supercapacitors. This paper presents a comprehensive review of model-based and data-driven approaches to predict the remaining useful life of supercapacitors, introduces the characteristics of the various methods, and foresees future trends, with the expectation of providing a reference for further research in this field.

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Section: Model-based Prediction Methodsmentioning

confidence: 99%

Prediction of the Remaining Useful Life of Supercapacitors

Zhao²,

Sun³

et al. 2022

Mathematical Problems in Engineering

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“…As can be seen in this Figure, the current profile represents the real driving profile in hybrid and electric vehicles, which corresponds to the repeated braking and acceleration. Since the SC resistance and capacitance are influenced by operating temperature [23], the supercapacitor (BCAP1500 Maxwell Technologies) used in this study is aged 228 hours, it is maintained at a temperature of 65°C (operating temperature) during the experiment using a temperature-controlled chamber [40].…”

Section: Experimental Studymentioning

confidence: 99%

“…They used Lyapunov-based adaptation law to estimate the supercapacitor's parameters. Saha et khanra [23]proposed an online identification scheme based on Particle Filter (PF) for the estimation of State-of-Charge, SoH, and temperature of SC by combining electrical equivalent circuit model and thermal model. They found that the proposed estimation scheme performs SoH estimation with acceptable accuracy.…”

Section: Introductionmentioning

confidence: 99%

Comparison Between Recursive Least Squares Method and Kalman Filter for Online Identification of Supercapacitor State of Health

Bououchma

Sabor

2022

Stat., optim. inf. comput.

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Supercapacitors are electrochemical components with high-power density and an intermediate energy density between batteries and conventional capacitors. They are characterized by low series resistance, signifificant equivalent capacitance, and long service life. Nowadays, they have become an attractive alternative storage device for several applications. However, supercapacitors are subject to degradation due to aging, in addition to other factors, such as temperature and high voltage. Therefore, it is very important to be able to estimate their State-of-Health during operation. Electrochemical Impedance Spectroscopy and Maxwell test are very recognized techniques to determine supercapacitors’ state-of-health. However, these methods require the interruption of system operation and thus cannot be performed in real-time (online). The purpose of this paper is the real-time estimation of supercapacitor resistance and capacitance, which are the main indicators of supercapacitor state-of-health. The electrical behavior of the supercapacitor is modeled using equivalent RC circuit model and the identifification is performed using two methods: recursive least squares method and Kalman fifilter. The resistance and the capacitance values obtained with the two methods are compared with capacitance and resistance values using Maxwell experimental test. The values obtained by Kalman fifilter are more accurate for both resistance and capacitance.

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“…One of the advantages of using extended Kalman filter (EKF) is its ability to deal with nonlinear systems, as it is the case capacitance and the bias voltage behavior of SCs. It has been used with success in order to estimate systems states in many applications [16], [18], [19], [29]. Its recursive structure and low computational cost make it suitable for real-time identification of system state parameters.…”

Section: Extended Kalman Filter Schemementioning

confidence: 99%

“…According to [28] suggested a procedure integrating fuzzy logic and artificial neural network (ANN) to estimate supercapacitors' internal resistance and capacitance. ANN can be a powerful technique to provide a robust identification for systems that are subjected to uncertainties [29]. However, this technique usually requires long offline tests to have the enough training data.…”

Section: Introductionmentioning

confidence: 99%

Online diagnosis of supercapacitors using extended Kalman filter combined with PID corrector

Bououchma

Sabor

2021

IJPEDS

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<span>Supercapacitors are electrical energy storage devices with a high specific power density, a long cycle life and a good efficiency, which make them attractive alternative storage devices for various applications. However, supercapacitors are subject to a progressive degradation of their perfor-mance because of aging phenomenon. Therefore, it is very important to be able to estimate their State-of-Health during operation. Electrochemical Impedance Spectroscopy (EIS) is a very recog-nized technique to determine supercapacitors’ state-of-health. However, it requires the interrup-tion of system operation and thus cannot be performed in real time (online). In this paper, a new online identification method is proposed based on extended Kalman observer combined with a complementary PID corrector. The proposed method allows to accurately estimating supercapacitor resistance and capacitance, which are the main indicators of supercapacitor state-of-health. The new online identification method was applied for two voltage/current profiles using two different supercapacitors. The resistance/capacitance estimated by the new method and the conventional EKF were compared with those obtained by an experimental offline method. In comparison with conventional EKF, the capacitance obtained by the new method is significantly more accurate.</span>

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Online Estimation of State-of-Charge, State-of-Health and Temperature of Supercapacitor

Cited by 5 publications

References 28 publications

Prediction of the Remaining Useful Life of Supercapacitors

Prediction of the Remaining Useful Life of Supercapacitors

Comparison Between Recursive Least Squares Method and Kalman Filter for Online Identification of Supercapacitor State of Health

Online diagnosis of supercapacitors using extended Kalman filter combined with PID corrector

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