Transcript MS Defense Announcement Topic A Generalized Logic

MS Defense Announcement
Topic
Presented by
Date
Time
A Generalized Logic-Based Approach for Intelligent
Fault Detection and Recovery in Power Electronic
Systems
Weiqiang Chen, ECE Dept.
Monday, January 5, 2014
10:00 am – 11:30 am
Location
ITEB 301
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.
Publications
•W. Chen and A. M. Bazzi, “A Generalized Approach for Intelligent Fault Detection and Recovery in Power
Electronic Systems,” in Proc. IEEE Engineering Conversion Congress & Exposition, 2013, pp. 4559-4564.
•W. Chen, L. Wang, A. Ulatowski and A. M. Bazzi, “A Fuzzy Logic Approach for Fault Diagnosis and Recovery in
PHEV and EV Chargers,” in Proc. IEEE Transportation Electrification Conference, 2014, pp. 1-5.
•S.M. Park, A.M. Bazzi, S.Y. Park, and W. Chen, “A time-efficient modeling and simulation strategy for
aggregated multiple microinverters in large-scale PV systems,” in Proc. IEEE Applied Power Electronics
Conference and Exposition, 2014, pp. 2754-2761.
•W. Chen, A. Ulatowski and A. M. Bazzi, Threshold-based Power Grid Fault Diagnosis,” in Proc. IEEE Power &
Energy Society, 2015, Under Review.
•W. Chen and A. M. Bazzi, “A Generalized Approach for Intelligent Fault Detection and Recovery
Advisory Committee
Prof. Ali Bazzi (Major Advisor)
Prof. Sung Yeul Park(Associate Advisor)
Prof. Shalabh Gupta (Associate Advisor)