Predesign Methodology of Voltage Inverters Using a Gradient-Based Optimization Algorithm

This article presents an optimization process applied to the sizing of high-power silicon carbide inverters. The case study is the design of an aeronautical converter. A gradient-based optimization method is chosen for its ability to explore a wide solution space with a large amount of constraints,...

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Vydané v:IEEE journal of emerging and selected topics in power electronics Ročník 9; číslo 5; s. 5895 - 5905
Hlavní autori: Voldoire, Adrien, Schanen, Jean-Luc, Ferrieux, Jean-Paul, Sarrazin, Benoit, Gautier, Cyrille
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.10.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Predmet:
Algorithms
Analytical models
Capacitors
Case studies
Converters
Design automation
Electric power
Engineering Sciences
Inductors
interleaving
Inverters
Magnetic cores
Mathematical models
Model accuracy
Optimization
Passive components
Power harmonic filters
SiC
Silicon carbide
Solution space
Spectrum analysis
Topology
voltage source inverter
Interleaving
SiC
Design Automation
Voltage Source Inverter
Index Terms -Optimization
ISSN:2168-6777, 2168-6785, 2168-6785
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Popis
Shrnutí:This article presents an optimization process applied to the sizing of high-power silicon carbide inverters. The case study is the design of an aeronautical converter. A gradient-based optimization method is chosen for its ability to explore a wide solution space with a large amount of constraints, which is the case during the predesign phase. Many topologies are selected and the associated models are developed. Among all these models, active and passive component design and spectral analysis of voltages and currents are presented. The optimization results, with the goal of minimizing the global mass of the converter, are provided. The different topologies are compared to find the best one for the selected case study. The relevance of the optimization result is evaluated with the study of the optimality of the solution. Finally, the experimental results are compared with the optimization ones, which validates the good accuracy of analytical models.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2168-6777
2168-6785
2168-6785
DOI:10.1109/JESTPE.2021.3092576