H
Huai Wang
Researcher at Aalborg University
Publications - 376
Citations - 10932
Huai Wang is an academic researcher from Aalborg University. The author has contributed to research in topics: Capacitor & Power electronics. The author has an hindex of 38, co-authored 328 publications receiving 7480 citations. Previous affiliations of Huai Wang include Yangtze University & City University of Hong Kong.
Papers
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Proceedings ArticleDOI
A Modified PBC Controller Using Dynamic Damping Injection for LCL-Filtered Grid-Tied Inverter with Zero Steady State Error
TL;DR: A modified PBC controller by using Dynamic Damping Injection for LCL-filtered GTI is proposed to eliminate the steady state error and the state observer is used to reduce the number of sensors.
Proceedings ArticleDOI
Loss Analysis of SiC-based Three-Level Active Neutral-Point-Clamped Inverters under Different Modulation Schemes
TL;DR: In this article, the power losses of three-level active neutral-point-clamped (3L-ANPC) inverters fully utilizing silicon-carbide (SiC) MOSFETs are studied and compared under three typically modulation schemes (i.e., the outer mode, inner mode, and full mode).
Proceedings ArticleDOI
Single-stage Bridgeless Buck-boost PFC Converter with DC Split for Low Power LED applications
TL;DR: In this paper, a bridgeless buck-boost converter with DC split configuration is proposed to minimize conduction losses, and harmonic injection is applied to further reduce output current ripple.
Proceedings ArticleDOI
System-Level Power Loss Evaluation of Modular Multilevel Converters
TL;DR: A system-level power loss evaluation for MMCs from the perspective of reliability assessment is proposed, which covers switching devices, capacitors, and inductors and is computation-efficient and easy to update parameters.
Proceedings ArticleDOI
Parameters Identification of Buck Converter Based on Dynamic Characteristics
Yingzhou Peng,Huai Wang +1 more
TL;DR: A parameter identification method for DC-DC power converters by taking advantage of its dynamic characteristics, which is non-invasive, computation efficient and without additional hardware compared to existing methods is proposed.