DocumentCode :
1582350
Title :
Use of genetic algorithms to design and optimize a high-efficiency LCIPT system
Author :
Kwimang, Gatien ; Ferrieux, Jean-Paul ; Meunier, Gerard
Author_Institution :
ENSE3, G2Elab (Grenoble Electr. Eng. Lab.), Grenoble INP, St. Martin d´Hères, France
fYear :
2013
Firstpage :
1
Lastpage :
10
Abstract :
This article deals with the design of loosely coupled inductive power transfer (LCIPT) systems applied to electric vehicle charging, and will focus on the optimization of a high-efficiency large air-gap transformer with the help of Genetic Algorithms (GA), and the choice of the most appropriate resonant converter topology. In this paper, a model at first harmonic of a series-series resonant converter (SSRC) and one of a series-parallel resonant converter (SPRC) are developed. It is shown that the choice of the resonant converter has a major influence on the transformer design. An optimization of an 18cm air-gap I-shaped transformer is performed in order to minimize its overall volume with efficiency greater than 98%.
Keywords :
air gaps; battery powered vehicles; genetic algorithms; inductive power transmission; power transformer insulation; resonant power convertors; GA; LCIPT system; SPRC; SSRC; air-gap I-shaped transformer; electric vehicle charging; genetic algorithm; loosely coupled inductive power transfer system; optimization; resonant converter topology; series-parallel resonant converter; series-series resonant converter; size 18 cm; Air gaps; Capacitors; Integrated circuit modeling; Linear programming; Magnetic cores; Optimization; Windings; Electric vehicle; LCIPT systems; Modeling; Resonant converter; Transformer;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Electronics and Applications (EPE), 2013 15th European Conference on
Conference_Location :
Lille
Type :
conf
DOI :
10.1109/EPE.2013.6634341
Filename :
6634341
Link To Document :
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