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A Single-Stage Isolated AC–DC Converter Based on the Impedance Control Network Architecture

Mausamjeet Khatua, Ashish Kumar, Saad Pervaiz, Sombuddha Chakraborty, Khurram K. Afridi

2021IEEE Transactions on Power Electronics27 citationsDOI

Abstract

This article introduces a new single-stage universal-input isolated ac-dc converter based on the impedance control network (ICN) architecture. This resonant converter performs both power factor correction and output voltage regulation while operating at a constant switching frequency and duty ratio, by modulating the phase-shift between its two half-bridge inverters and the phase-shift between the two legs of its full-bridge rectifier. This phase-shift control strategy along with the ICN architecture also enables the converter to achieve high efficiency by ensuring zero-voltage-switching and near-zero-current-switching of all its inverter transistors throughout the line cycle and across wide ranges of input line voltage and output power. Power density is enhanced by realizing the three ICN inductors using a single magnetic structure with two coupled windings. This coupled inductor and a transformer constitute the two magnetic components of the proposed converter. A systematic methodology to design this ICN ac-dc converter is also introduced. A universal-input (90-265 V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rms</sub> ), 20-V output, 330-W, 400-kHz ICN ac-dc converter prototype is built and tested. This prototype achieves a power density of 37.9 W/in <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> and peak efficiencies of 91.7%, 92.2%, 93.2%, and 93.4% at 90, 120, 230, and 265 V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rms</sub> input, respectively.

Topics & Concepts

InductorDuty cycleElectrical engineeringTransformerRectifier (neural networks)Electromagnetic coilElectrical impedanceInverterVoltagePhysicsComputer scienceElectronic engineeringTopology (electrical circuits)EngineeringRecurrent neural networkMachine learningArtificial neural networkStochastic neural networkAdvanced DC-DC ConvertersMultilevel Inverters and ConvertersSilicon Carbide Semiconductor Technologies
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