3 research outputs found

    Fractional - order impedance identification for Inductors

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    The accuracy of a model is required to represent the integrated device in any electrical system for quality assurance. This article intends to measure the accurate and realistic impedance of the inductor, called pseudo-inductance. For this purpose, we have applied fractional-order modeling and a simple scheme to estimate the impedance value of the inductor (or inductive coils). Also, the approach does not require any high-end measurement device like the impedance meter. The complexity of the fractional-order derivative for identification purpose is simplified using the block-pulse-operational-matrix. The complexity of the fractional-order derivative for identification purpose is simplified using the block-pulse operational matrix to approximate the time response behaviour in terms of the inductor model’s parameters. The study goes on to highlight the importance of fractional derivative and its interpretation in terms of the phase difference. The proposed model can be used to accurately model any inductor based on its time response data. The purpose of the study is validated through the experimental results

    Fractional - order system modeling and its applications

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    In order to control or operate any system in a closed-loop, it is important to know its behavior in the form of mathematical models. In the last two decades, a fractional-order model has received more attention in system identification instead of classical integer-order model transfer function. Literature shows recently that some techniques on fractional calculus and fractional-order models have been presenting valuable contributions to real-world processes and achieved better results. Such new developments have impelled research into extensions of the classical identification techniques to advanced fields of science and engineering. This article surveys the recent methods in the field and other related challenges to implement the fractional-order derivatives and miss-matching with conventional science. The comprehensive discussion on available literature would help the readers to grasp the concept of fractional-order modeling and can facilitate future investigations. One can anticipate manifesting recent advances in fractional-order modeling in this paper and unlocking more opportunities for research

    Parameter- und Ordnungsidentifikation von fraktionalen Systemen mit einer Anwendung auf eine Lithium-Ionen-Batteriezelle

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    Model-based methods are increasingly being used for a safe and efficient operation of battery cells. For modeling battery cells, fractional models which are characterized by non-integer derivative orders have become established due to their electrochemical interpretability. In this work, methods for parameter and derivative order identification of fractional systems are derived without restriction with respect to the excitation at the begin of identification
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