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Jones D.C.,University of Colorado at Boulder | Jones D.C.,Phobos Energy Inc. | Erickson R.W.,University of Colorado at Boulder | Erickson R.W.,Phobos Energy Inc.
IEEE Transactions on Power Electronics | Year: 2013

A new nonlinear state machine is proposed as the solution to an operational dead zone near the buck/boost interface of the noninverting buck-boost converter. This dead zone avoidance and mitigation (DZAM) state machine transforms the sequence of buck and boost duty cycles applied to the converter to a new sequence which completely avoids the dead zone while largely shielding the rest of the converter from its presence. The state machine contains one of several possible embedded nonlinearities, the choice of which determines the exact characteristics of the DZAM algorithm and is application specific. Previously published attempts to deal with the noninverting buck-boost dead zone either double switching loss or apply only to systems with slowly changing input/output conditions. By contrast, the high-speed DZAM technique proposed here does not increase switching loss and operates autonomously, independent of external conditions, thereby allowing its use in all applications. © 1986-2012 IEEE. Source


Jones D.C.,Phobos Energy Inc. | Jones D.C.,University of Colorado at Boulder | Erickson R.W.,Phobos Energy Inc. | Erickson R.W.,University of Colorado at Boulder
IEEE Transactions on Power Electronics | Year: 2013

Local maxima in the measured power curve of a photovoltaic (PV) panel, called traps, are caused by switching transients and other deterministic phenomena in PV power converters. Traps exist even in the absence of shading, and degrade the performance of perturb and observe (PO) maximum power point trackers. A generalized PO (GPO) algorithm is proposed which eliminates this degradation. PO/GPO algorithms in the presence of random noise are shown to be modeled by multidimensional Markov chains. These models quantify the tendency for PO at low random noise levels to become stuck in traps following insolation changes, thereby decreasing tracking performance and reducing harvested power. By contrast, GPO tracks insolation changes unhindered by traps. All theoretical results are experimentally verified using a hardware PV converter. © 2013 IEEE. Source

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