Date of Completion

3-12-2015

Embargo Period

3-11-2015

Advisors

Sung-Yeul Park, Shalabh Gupta

Field of Study

Electrical Engineering

Degree

Master of Science

Open Access

Open Access

Abstract

This thesis presents a generalized logic-based approach for intelligent fault diagnosis in power electronic converters based on correlation between faults and basic measurements. Fault recovery is then applied based on this correlation by using specific signals and quantities from existing measurements. The main purpose is for power electronic systems to cope with the notion of a smart grid and its different smart components. Existing intelligent control of power electronic systems is reviewed along with various short- and open-circuit faults in major power electronic components. Two methods are established to diagnose faults and engage redundancy for fault recovery with one method using combinational logic and another using fuzzy logic. In both methods, two quantities are observed for each of the measured signals: 1) average value and 2) RMS value. A systematic methodology to reduce the number of measured quantities while maintaining effective diagnosis is introduced. Since solar photovoltaic (PV) panels typically have longer lifetime than their connected electronics especially from a warranty perspective, a solar PV micro-inverter in stand-alone mode is used as an example testing platform for the proposed methods to increase the inverter’s lifetime to match a PV panel. A simulation model is experimentally validated and the effect of each fault on different voltage and current measurements are observed, then both methods are tested in simulation and hardware. Results show the ability of both methods to diagnose several faults in the inverter’s power stage along with their ability to engage redundancy for fault recovery.

Major Advisor

Ali Bazzi

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