This paper investigates the optimization of power converters using ferrite inductors in Sustainable Saturation Operation (SSO), performed by means of an Evolutionary Algorithm (EA). The EA is adopted to identify viable optimal solutions providing a trade-off among efficiency, inductor volume, reliability and electromagnetic emissions. Three non-isolated low-power converters of different voltage and current ratings and based on buck, boost and buck-boost topologies, have been considered for the investigation. The results show that the EA is able to identify design solutions achieving best efficiency, volume, reliability and emissions performances with inductors in SSO.
Optimizing power converters with partially saturated inductors by evolutionary algorithms
DI CAPUA, Giulia
2017-01-01
Abstract
This paper investigates the optimization of power converters using ferrite inductors in Sustainable Saturation Operation (SSO), performed by means of an Evolutionary Algorithm (EA). The EA is adopted to identify viable optimal solutions providing a trade-off among efficiency, inductor volume, reliability and electromagnetic emissions. Three non-isolated low-power converters of different voltage and current ratings and based on buck, boost and buck-boost topologies, have been considered for the investigation. The results show that the EA is able to identify design solutions achieving best efficiency, volume, reliability and emissions performances with inductors in SSO.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
