Comparative study of Boost and Zeta converters in DC microgrid applications

Ziani, Jihen Arbi; Ghorbal, Manel Jebali Ben; Moussa, Sonia

doi:10.1109/energycon48941.2020.9236476

Cited by 4 publications

(1 citation statement)

References 14 publications

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“…In recent years, dc-dc conversion has been greatly developed in many sectors of the industrial world, and the Zeta converter has been applied with excellent results in terms of power density and output ripple [25]. Thanks to its simple structure and its ability to operate as a buck-boost converter with a noninverted output, it has been used in many different applications: as an electric vehicle battery charger powered by a photovoltaic (PV) array [26], as a dc motor controller [27], and as grid interface in a standalone dc microgrid [28].…”

Section: Zeta Convertermentioning

confidence: 99%

Failure Prevention in DC–DC Converters: Theoretical Approach and Experimental Application on a Zeta Converter

Bindi

Corti

Grasso

et al. 2023

IEEE Trans. Ind. Electron.

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In this article, we propose a monitoring procedure based on a multilayer neural network with multivalued neurons (MLMVN) capable of preventing catastrophic failures of dc-dc converters. The neural classifier allows both the detection of any malfunction and its localization. Thanks to the low computational complexity, the proposed method operates online, estimating the deviations of the passive components from their nominal values: this allows control strategies to be promptly adopted and operation of the dc-dc converter to be kept in high efficiency and reliability conditions. Since measuring the voltage and current on each component increases the complexity of the system, a testability analysis is proposed with the aim of identifying the minimum number of measurements needed to distinguish the classes of failure. To make the testability phase easier and more intuitive, a graphical representation is proposed. As a case study, prognostic analysis has been applied to prevent catastrophic failures in a synchronous Zeta converter. Several fault conditions have been analyzed through simulations and experimental tests. The obtained results confirm the ability of the proposed method to prevent failures and, also, show that the application of MLMVN results in a better performance than classic solutions available in the literature, such as support vector machine.

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