Integrated High Frequency Coaxial Transformer Design Platform Using Artificial Neural Network Optimization and FEM Simulation

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Author(s)
Li, Jeffrey
Water, Wayne
Zhu, Boyuan
Lu, Junwei
Year published
2015
Metadata
Show full item recordAbstract
Designing a high frequency (HF) power transformer is a complicated task due to its multiple interrelation design procedures, large number of variables and other relevant factors. Traditional transformer design relies on manual paper work and personal experience, which requires engineering design man-hours and long delivery cycles. In this paper, a developed transformer computer design environment is addressed. It helps engineers to automatically model, simulate and optimize transformer design using an artificial neural network (ANN) algorithm and the finite element method (FEM), and delivers a reliable design result. By ...
View more >Designing a high frequency (HF) power transformer is a complicated task due to its multiple interrelation design procedures, large number of variables and other relevant factors. Traditional transformer design relies on manual paper work and personal experience, which requires engineering design man-hours and long delivery cycles. In this paper, a developed transformer computer design environment is addressed. It helps engineers to automatically model, simulate and optimize transformer design using an artificial neural network (ANN) algorithm and the finite element method (FEM), and delivers a reliable design result. By utilizing the proposed platform, an 8kW coaxial transformer is successfully designed, tested and manufactured.
View less >
View more >Designing a high frequency (HF) power transformer is a complicated task due to its multiple interrelation design procedures, large number of variables and other relevant factors. Traditional transformer design relies on manual paper work and personal experience, which requires engineering design man-hours and long delivery cycles. In this paper, a developed transformer computer design environment is addressed. It helps engineers to automatically model, simulate and optimize transformer design using an artificial neural network (ANN) algorithm and the finite element method (FEM), and delivers a reliable design result. By utilizing the proposed platform, an 8kW coaxial transformer is successfully designed, tested and manufactured.
View less >
Conference Title
The Sixteenth Biennial IEEE Conference on Electromagnetic Field Computation 2014
Copyright Statement
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Subject
Renewable Power and Energy Systems Engineering (excl. Solar Cells)
Physical Sciences
Engineering