Journal
IEEE TRANSACTIONS ON POWER ELECTRONICS
Volume 32, Issue 7, Pages 5323-5340Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPEL.2016.2609501
Keywords
High step-up dc gain converters; switched-capacitor cell; switched-inductor cell; large dc gain converter systematic derivation; switched-capacitor-inductor cell
Categories
Ask authors/readers for more resources
A very simple geometric structure whose branches can be filled by inductors, capacitors, diodes, short-circuits, or open-circuits is proposed. It serves for generating large dc gain-purposed switching cells by making different choices of the type of component on each branch. The switching cells are integrated in basic converters. It is shown that almost all the high dc gain nonisolated converters based on switched-capacitor-inductor cells proposed in the last years, regardless of their complexity, can be derived through this method. From the same geometric structure, new high dc gain boosting converters can be derived in a systematic manner. The available and the new converters in each class as defined by the number of reactive components are compared in terms of their performance: dc gain, semiconductor elements count, voltage and current stress on transistors and diodes, character of the input current, easiness of the transistor driving, and easiness of the control as determined by common/uncommon line-load ground, power stage efficiency. This comparison allows us to choose the optimal solution for each specific application in conjunction with the green sources of energy, multisource microgrids, electric vehicles, data and communications systems, and so on. The geometric structure is generalized in different ways, allowing for the development of ultrahigh dc gain converters. One of the proposed generalized ultrahigh dc gain converters is fully analyzed and built in the laboratory, with the experimental results verifying the theoretical analysis.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available