Power cycling tests for accelerated ageing of ultracapacitors

Briat, Olivier; Lajnef, Walid; Vinassa, Jean-Michel; Woirgard, Eric

doi:10.1016/j.microrel.2006.07.008

Cited by 12 publications

(3 citation statements)

References 2 publications

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“…(i) Current profiles with high peak currents imply long rest periods when the root mean square (RMS) values of current are kept fixed [107]. High peak currents lead to high peak temperatures due to Joule heating during charge/discharge.…”

Section: Aging Testsmentioning

confidence: 99%

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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%

“…For instance, Briat et al [107] observed a 10 % reduction in capacitance after charge/discharge cycles of 200 A current for 417 h at 40°C on a commercial capacitor (Maxwell BCAP2600F). More examples are shown in Table 4.8.…”

Section: Aging Testsmentioning

confidence: 99%

Influence of Temperature on Supercapacitor Performance

Xiong

Kundu

Fisher

2015

Thermal Effects in Supercapacitors

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“…As electronics is used in almost every area of human life, and as a result all of these areas being "safety critical", the prediction of the lifetime of electronic modules becomes an ever increasing necessity. This is especially true for aeronautics and automotive applications, where temperatures can sometimes well exceed the maximum guaranteed operating temperature for a particular component [5] [6].…”

Section: Introductionmentioning

confidence: 99%

Parameter monitoring of electronic circuits for reliability prediction and failure analysis

Jano

Pitica

2011

Proceedings of the 2011 34th International Spring Seminar on Electronics Technology (ISSE)

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As electronic modules are becoming ever more popular in critical safety applications, such as electronic vehicles and aeronautics, so do their operating conditions become harsher. This sometimes means using electronic components at the very limit of their functional parameters and very close to or even exceeding their maximum operating temperature. This of course leads to a dramatic decrease in component lifetimes and classical failure prediction algorithms are thrown off balance, giving unreliable results.This of course means that new prediction methods should be established. The following paper proposes a method for predicting the value of capacitors on the electronic modules, in order to perform real-time prediction of their lifetimes affected by their operational environment. First, two capacitor lifetime models are presented and compared and then the theoretical data are compared with the data obtained from accelerated ageing measurements.

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