Summary: | Modeling and analysis of basic DC-DC converters is essential for enabling power-electronic solutions for the future energy systems and applications. Average-value modeling (AVM) provides a time-efficient tool for studying power electronic systems, including DC/DC converters. Many AVM techniques including the analytical and numerical state-space averaging and circuit averaging have been developed over the years and available in the literature. Average-value modeling of ideal PWM converters neglects parasitics (losses) to simplify the derivations and modeling procedures, and the resulting models may not be sufficiently accurate for practical converters.
In this work, first we consider a second-order Flyback converter, which has transformer isolation and additional parasitics such as conduction losses that have not been accurately included in the prior literature. We propose three new AVMs using the analytical state-space averaging, circuit averaging, and parametric AVM approaches, respectively. By taking into account conduction losses, the accuracy of the proposed average-value models is significantly improved. The derived (corrected) models show noticeable improvement over the traditional (un-corrected) models.
Next, we consider the Flyback converter including the snubbers and leakage inductances in the full-order model. Snubbers reduce electromagnetic interfaces (EMI) during transients and protect switching devices from high voltage, and therefore are necessary in many practical converter circuits. Including snubbers into the model improves accuracy in predicting the circuit variables during the time-domain transients as well as predicting the converter efficiency. It is shown that conventional analytical/numerical methods of averaging do not result in accurate AVM for the full-order Flyback converter. A new formulation for the state-space averaging methodology is proposed that is functional for higher-order converters with parasitics and result in highly accurate AVM. The new approach is justified mathematically and verified experimentally using hardware prototype and measurements. The new model is demonstrated to achieve accurate results in large signal time-domain transients, and small-signal frequency-domain analysis in continuous conduction mode (CCM) and discontinuous conduction mode (DCM), which represents advancement to the state-of-the-art in this field. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate
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