Design and Implementation of DSP-based Intelligent Control for Series Resonant Converter

• Main Authors: Sheng-Lung Wang, 王昇龍
• Other Authors: Faa-Jeng Lin
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/81344562025394819357

碩士 === 國立中央大學 === 電機工程學系 === 101 === The purpose of this thesis is to develop a digital signal processor (DSP) based intelligent control of series resonant converter (SRC). The SRC is constructed using LLC resonant tank which is driven by a half-bridge circuit with fixed 50%-duty carrier frequency. The resonant phenomenon can be obtained by using of the leakage inductance of primary coil, the magnetizing inductance of the transformer, the resonant capacitor and parasitic component of power MOSFETs. Moreover, the zero-voltage-switching (ZVS) can be achieved using resonant phenomenon to reduce the switching loss. Furthermore, the synchronous rectifier is added in the secondary side of transformer by using the power MOSFETs in place of the diode to reduce the conduction loss. In addition, to improve the transient response of the voltage regulation during load variation, two intelligent controls are proposed. One is the probabilistic fuzzy neural network (PFNN), and the other is the TSK-type probabilistic fuzzy neural network with asymmetric membership function (TSKPFNN-AMF). The network structures, online learning algorithms and convergence analyses of the PFNN and the TSKPFNN-AMF controls are introduced in detail. Finally, the feasibility of the proposed control schemes are verified through experimentation.