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Review of Converter Circuits with Power Factor Correction
by
Espitia, Helbert
, Bayona, Jhon
, Quiroga, Angel
in
Alternative energy sources
/ Artificial intelligence
/ Circuits
/ Computer engineering
/ Control
/ Controllers
/ converters
/ Design and construction
/ Efficiency
/ Electric current converters
/ Electric power factor
/ Electrical engineering
/ Energy consumption
/ Energy conversion
/ half-bridge
/ Industrial applications
/ Neural networks
/ Power factor
/ power factor correction
/ Topology
2025
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Review of Converter Circuits with Power Factor Correction
by
Espitia, Helbert
, Bayona, Jhon
, Quiroga, Angel
in
Alternative energy sources
/ Artificial intelligence
/ Circuits
/ Computer engineering
/ Control
/ Controllers
/ converters
/ Design and construction
/ Efficiency
/ Electric current converters
/ Electric power factor
/ Electrical engineering
/ Energy consumption
/ Energy conversion
/ half-bridge
/ Industrial applications
/ Neural networks
/ Power factor
/ power factor correction
/ Topology
2025
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Do you wish to request the book?
Review of Converter Circuits with Power Factor Correction
by
Espitia, Helbert
, Bayona, Jhon
, Quiroga, Angel
in
Alternative energy sources
/ Artificial intelligence
/ Circuits
/ Computer engineering
/ Control
/ Controllers
/ converters
/ Design and construction
/ Efficiency
/ Electric current converters
/ Electric power factor
/ Electrical engineering
/ Energy consumption
/ Energy conversion
/ half-bridge
/ Industrial applications
/ Neural networks
/ Power factor
/ power factor correction
/ Topology
2025
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Journal Article
Review of Converter Circuits with Power Factor Correction
2025
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Overview
This article reviews converter circuits with power factor correction considering issues that arise in implementing such circuits. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedure are employed for the review. Six topologies with power factor correction were considered including boost, buck, buck-boost, Cük, dual boost, and totem pole bridgeless. The main findings highlight various implementation alternatives for these converters, taking into account complexity, performance, control strategies, and applications. Additionally, the review identified studies based on simulation and hardware implementation. Several alternatives exist for research to improve energy conversion circuits using conventional techniques such as PI controllers or novel controllers using artificial intelligence techniques such as neural networks. Finally, it should be noted that converter circuits with power factor correction are crucial for developing various electrical and electronic devices in domestic and industrial applications.
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