Open AccessZ‐source matrix rectifier
Author(s) -
Hongchen Liu,
Yuliang Ji,
Dan Zhao,
Zhang Chengming,
Wheeler Patrick,
Guolei Fan
Publication year - 2016
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2015.0966
Subject(s) - rectifier (neural networks) , precision rectifier , peak inverse voltage , control theory (sociology) , topology (electrical circuits) , inductor , voltage , power factor , computer science , voltage source , electronic engineering , electrical engineering , engineering , voltage optimisation , control (management) , stochastic neural network , artificial intelligence , recurrent neural network , artificial neural network , machine learning
This study presents a novel Z‐source matrix rectifier (ZSMR). To overcome the inherent disadvantage that the voltage transfer ratio for traditional matrix rectifier (MR) cannot be more than 0.866, a Z‐source network has been combined with the MR. The proposed rectifier realises a voltage‐boost function and the Z‐source network also serves as power storage and guarantees double filtration grade at the output of the rectifier. The open‐circuit zero state is required to obtain the voltage‐boost function and ensure the output angle of the current vector to be invariant to obtain the expected power factor. In addition, to widely extend the voltage transfer ratio of the proposed rectifier, this study presents the switched‐inductor matrix rectifier (SL‐ZSMR) and tapped‐inductor matrix rectifier (TL‐ZSMR). The corresponding circuit topologies, control strategies and operating principles are introduced. Both simulation and experimental results are shown to verify the theoretical analysis.