1 research outputs found

    Prediction Aging Model for Supercapacitor's Calendar Life in Vehicular Applications

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    International audienceSupercapacitors have received increasing interest from the vehicular community due to their high power density and compact size, making them good candidates for high-performance applications, such as electric/hybrid vehicles and railway transportation. However, supercapacitors have a finite lifespan due to the occurrence of unwanted physical changes. These changes are usually irreversible, which yield capacitance loss and performance deterioration, regardless of the components' usage. Most of the available aging models are based on particular assumptions of capacitance loss. Unlike these techniques, this paper considers different capacitance aging models and compared them to verify their accuracy. In addition, a generalized prediction aging model for the calendar life is presented based on chemical reactions causing degradation. The performance of the proposed model is compared with the classical and modified Eyring's law. To better show the effectiveness of the proposed prediction aging strategy and capacitance loss models, 12 supercapacitors are tested under 12 different operating temperatures and bias voltage conditions. Experimental results highlight the high estimation accuracy of the proposed prediction aging model under various operating conditions
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