학술논문

Data-Driven Switch Fault Diagnosis for DC/DC Boost Converters in Photovoltaic Applications
Document Type
Periodical
Source
IEEE Transactions on Industrial Electronics IEEE Trans. Ind. Electron. Industrial Electronics, IEEE Transactions on. 71(2):1631-1640 Feb, 2024
Subject
Power, Energy and Industry Applications
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Switches
Inductors
Circuit faults
Switching circuits
Fault diagnosis
Fault detection
Voltage control
Multiclass classifiers
open-circuit faults
photovoltaic systems
short-circuit faults
Language
ISSN
0278-0046
1557-9948
Abstract
Switch semiconductors are essential components in power electronics stages for photovoltaic (PV) systems, which are prone to failures caused mainly by thermal stress, thereby affecting PV energy production. Specifically, dc/dc boost power converters are commonly used as maximum power point tracking (MPPT) systems. Several works have been reported so far in the literature for switch fault detection and isolation (FDI) purposes in boost power converters. However, most of them require additional sensors and circuitry to those included in any PV system, which generate extra costs on the overall system. Hence, this work presents an efficient and low-cost switch fault diagnosis proposal, which requires only the most common measurements in PV systems, namely, PV current and voltage. This work departs from a data-driven FDI methodology for diagnosing switch open- and short-circuit faults in dc/dc boost converters. The experimental results have been evaluated against sudden irradiance changes and switch faults in a test bench of 350 $\text {W}$ operating under a closed-loop nonlinear control action for MPPT purposes by using the dSpace 1104 board.