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IEEE Journal of Emerging and Selected Topics in Power Electronics
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An Improved Linear Model for High-Frequency Class-DE Resonant Converter Using the Generalized Averaging Modeling Technique

Authors: Nicolai J. Dahl; Ahmed M. Ammar; Arnold Knott; Michael A. E. Andersen;

An Improved Linear Model for High-Frequency Class-DE Resonant Converter Using the Generalized Averaging Modeling Technique

Abstract

As the operating frequency of power converters increases, the passive component values likewise decrease. This results in the effect of the parasitic components becoming more prominent, leading to significant modeling errors if not considered. For resonant converters this especially becomes a problem at high frequencies. This paper presents a reduced model for a class-DE series resonant converter based on generalized averaging that incorporates the relevant parasitics and uses multiple harmonics to obtain an accurate linear model. Comparison between the proposed model, prior art, and a prototype converter running at 1 MHz is conducted, and a PI-controller is designed based on each model and tested. The results show that the parasitics have a significant impact on the DC-gain and dynamics of the converter, and that the proposed model improves on the prior art by reducing the DC-gain error by more than 7 dB, and the error in the low frequency pole from 168 % to 16.9 %. Furthermore, the PI-controller designed on the prior art was found to have more than 40 times larger overshoot in the control signal when measured compared to the model prediction, while the controller based on the proposed model showed correct performance when simulated and measured.

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Keywords

PI control, State-space methods, DC-DC power converters, Modeling, Resonant converters

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citations
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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