Buck Converter Modeling in High Frequency using Several Transfer Function-based Approaches

被引:0
作者
Shiri, Imen [1 ]
Lefteriu, Sanda [1 ]
Labarre, Cecile [1 ]
机构
[1] IMT Lille Douai, Unite Rech Informat & Automat, 941 Rue Charles Bourseul, F-59500 Douai, France
来源
ICINCO: PROCEEDINGS OF THE 16TH INTERNATIONAL CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS, VOL 1 | 2019年
关键词
Buck Converter; Modeling; Transfer Function; High Frequency; Parasitic Elements;
D O I
10.5220/0007927407220729
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The recent development of large gap (GaN) components adapted to high frequency operation opens up interesting perspectives for the emergence of high power density static converters. However, the implementation of GaN components requires the development of new characterization, modeling and design methods adapted to these fast components. In this paper, we present three modeling techniques for a static converter in the frequency domain. They are all characterizing the input - output transfer function and they are: the average model, the generalized transfer function (GTF) and the modified nodal analysis technique (MNA). These models, already existing in the literature, are extended to account for the parasitic effects of the switching elements (diodes or transistors). In fact, parasitic elements associated with the different passive and active components are inherent in a power electronics structure. Their effects are negligible in low frequency but they are preponderant in high frequency. Simulation results performed for a Buck converter show that, while the GTF and the MNA are able to predict the resonances present at multiples of the switching frequency, the average model does not. In terms of the influence of the parasitic elements on the transfer function, the peak which is due to the output filter parameters is attenuated. Lastly, the experimental validation shows that, even with the introduction of the parasitic elements of the switching components, there are still discrepancies between the models and the data, so additional parasitics still need to be accounted for.
引用
收藏
页码:722 / 729
页数:8
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