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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.

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Reliability of Capacitors for DC-Link Applications in Power Electronic Converters—An Overview

TL;DR: This review serves to provide a clear picture of the state-of-the-art research in this area and to identify the corresponding challenges and future research directions for capacitors and their dc-link applications.
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Toward Reliable Power Electronics: Challenges, Design Tools, and Opportunities

TL;DR: The performance of power electronic systems, especially in terms of efficiency and power density, has continuously improved by the intensive research and advancements in circuit topologies, control schemes, semiconductors, passive components, digital signal processors, and system integration technologies.
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Transitioning to Physics-of-Failure as a Reliability Driver in Power Electronics

TL;DR: In this article, the three major aspects of power electronics reliability are discussed, respectively, which cover physics-of-failure analysis of critical power electronic components, state-ofthe-art design for reliability process and robustness validation, and intelligent control and condition monitoring to achieve improved reliability under operation.
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Low-Voltage Ride-Through of Single-Phase Transformerless Photovoltaic Inverters

TL;DR: In this article, the LVRT capability of three mainstream single-phase transformerless PV inverters under grid faults is explored in order to map future challenges, and control strategies with reactive power injection are also discussed.
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An Overview of Artificial Intelligence Applications for Power Electronics

TL;DR: The three distinctive life-cycle phases, design, control, and maintenance are correlated with one or more tasks to be addressed by AI, including optimization, classification, regression, and data structure exploration.