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Light-Load Performance Enhancement Technique for <i>LLC</i>-Based PEV Charger Through Circuit Reconfiguration

Dongdong Shu, Haoyu Wang

2021IEEE Transactions on Transportation Electrification31 citationsDOI

Abstract

In <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> -based plug-in electric vehicle (PEV) charging system, light-load condition occupies a large portion of the charging process. However, at light load, the parasitic capacitance of full-bridge <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> converter leads to poor voltage regulation. Besides, the magnetic core loss and circulating loss are load-independent and jeopardize the light-load efficiency. To resolve those two issues in a coupled manner, a light-load performance enhancement technique is proposed in this article. At light load, the primary side is reconfigured as a half-bridge inverter and the secondary side is reconfigured as a voltage doubler rectifier, while the voltage gain is roughly unchanged. Therefore, both the equivalent resistance and capacitance of the secondary resonant network are effectively reduced, which contributes to an enhanced voltage-regulation capability. Moreover, the core loss and circulating current-induced conduction loss are both effectively reduced, which contributes to a boosted efficiency. A 2-A rated, which converts 390-V input to 250–450-V output, converter prototype is designed and tested to validate the concept. The light-load mode exhibits an obvious efficiency improvement. The frequency regulation range is also effectively squeezed.

Topics & Concepts

Electrical engineeringControl reconfigurationCapacitanceVoltageCapacitorRectifier (neural networks)Topology (electrical circuits)PhysicsOptoelectronicsComputer scienceEngineeringEmbedded systemArtificial neural networkQuantum mechanicsMachine learningStochastic neural networkRecurrent neural networkElectrodeAdvanced DC-DC ConvertersAdvanced Battery Technologies ResearchWireless Power Transfer Systems
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