Study of Supercapacitor Aging and Lifetime Estimation According to Voltage, Temperature, and RMS Current

Kreczanik, Paul; Venet, Pascal; Hijazi, Alaa; Carrault, Guy

doi:10.1109/tie.2013.2293695

Cited by 158 publications

(89 citation statements)

References 12 publications

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“…Apart from the average temperature, other features of the current profile (e.g., pulse duration and rest period) also influence aging characteristics. Shorter pulse durations of higher charge/discharge rates lead to faster expansion/contraction of the electrode due to ion insertion/deinsertion in the electrode [112][113][114]. This alternate expansion/contraction causes mechanical stresses in the electrode that accelerate aging.…”

Section: Aging Testsmentioning

confidence: 99%

Influence of Temperature on Supercapacitor Performance

Xiong

Kundu

Fisher

2015

Thermal Effects in Supercapacitors

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Because of the negligible faradic reactions in double-layer capacitors, heat generated during charge/discharge processes derives mostly from Joule heating, which is determined by internal resistance (or equivalent series resistance, ESR). However, heat generated in pseudo-capacitors derives from both Joule heating and exothermic/ endothermic Faradic reactions. Thus, understanding how temperature affects capacitance and ESR is essential to predict supercapacitor performance under different operating conditions. The general techniques (e.g., CV, constant current-charge/ discharge and EIS) to evaluate capacitance and ESR have been discussed in Sect. 2.4.Many factors contribute to ESR in a supercapacitor: (i) interfacial resistance (contact resistance) between the electrode and the current collectors; (ii) electronic resistance of the electrode material; (iii) resistance of ions migrating through the electrode pores; (v) electrolyte resistance, and (vi) resistance of ions migrating through the separator [2,3]. Consequently, ESR depends on the active area and porosity of electrodes, ionic conductivity of the electrolyte, and physical properties of the separator (e.g., porosity, thickness and tortuosity). Notably, electrolyte resistance is only part of ESR. ESR depends on many factors (e.g., electrode structure, materials, electrolytes, fabrication and temperature). ESR is suggested to be inversely proportional to σ within certain ranges [4], but this relation can be violated. For instance, ESR is more dominated by the carbon electrode resistance and the interface resistance at the current collector than electrolyte resistance, as indicated by a much smaller activation energy of ACN-based supercapacitors than that of the electrolyte [5]. Capacitance is a function of surface area and volume of the electrodes, and ionic conductivity of electrolytes, which strongly depends on temperature variations.The operating temperature strongly influences the properties of electrolytes (e.g., viscosity, solubility of the salt in solvents, ionic conductivity, and thermal stability), leading to dramatic changes of capacitance and ESR, particularly at extreme temperatures (ultra-low and ultra-high temperatures). Consequently, the influence of

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Section: Aging Testsmentioning

confidence: 99%

Influence of Temperature on Supercapacitor Performance

Xiong

Kundu

Fisher

2015

Thermal Effects in Supercapacitors

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“…When one ageing acceleration factor, SoC, is variable over time, the parameter identification of [20,21] and batteries [17,22].…”

mentioning

confidence: 99%

Eyring acceleration model for predicting calendar ageing of lithium-ion batteries

Redondo-Iglesias

Venet

Pélissier

2017

Journal of Energy Storage

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Modelling of lithium-ion batteries calendar ageing is often based on a semi-empirical approach by using, for example the Arrhenius acceleration model. Our approach is based on Eyring acceleration model, which is not widely used for electrochemical energy storage components. Parameter identification is typically performed without taking into account the state-of-charge (SoC) drifting. However, even in rest condition, battery cells' SoC drifts because of capacity losses (self-discharge and capacity fade). In this work we have taken into account the SoC drift during calendar ageing tests. For this, we considered available capacity (Ah) instead of SoC (%) as ageing factor. Then, the analytical solution of the problem leads to the use of the Lambert W function in the model formulation. Simulation results show that Lambert-Eyring model is more accurate and allows a reduction in the number of parameters to be identified.

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“…5 In order to mitigate/eliminate this bias, we Table 2 we can see that the inferred value of the C PC1 is of 302.6 F. Also this value can be considered reasonable since is lower than the corresponding one after a LE test (it has been already underlined that during a PC stress test the ageing phenomena are amplified compared to those during a LE stress test). 5 Further details concerning this aspect can be found in [16].…”

Section: General Overviewmentioning

confidence: 88%

“…Refs. [1][2][3][4][5] have discussed the use of the SOH of these devices for predicting the remaining lifetime and to define optimal energy management strategies.…”

Section: Introductionmentioning

confidence: 99%

Modelling of current and temperature effects on supercapacitors ageing. Part II: State-of-Health assessment

Torregrossa

Paolone

2016

Journal of Energy Storage

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This second part of the paper proposes a model for predicting the State-of-Health (SOH) of electrochemical double layers supercapacitors (SCs) during combined high-pulsed power cycling and high-temperature life endurance stresses. The evolutions of the SC capacitance, C SC , during these specific types of stresses have been discussed in part I and, based on the phenomenological observations we made, we here predict the C SC evolution by means of a dedicated model. The inputs of the proposed model are the SC delivered charge and the duration of the temperature stress above the rated one; the output is the C SC . The main virtue of the model is its capability to take into account the presence of the C SC recovering and accelerated ageing that cannot be represented by other models available in the literature. The validation of the proposed SC ageing model is carried out by means of experimental results, other than those used to infer the model, obtained on a 365 F SC stressed by combined life-endurance and power-cycling stresses over a time window of 35 days.

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Study of Supercapacitor Aging and Lifetime Estimation According to Voltage, Temperature, and RMS Current

Cited by 158 publications

References 12 publications

Influence of Temperature on Supercapacitor Performance

Influence of Temperature on Supercapacitor Performance

Eyring acceleration model for predicting calendar ageing of lithium-ion batteries

Modelling of current and temperature effects on supercapacitors ageing. Part II: State-of-Health assessment

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