Work

Adaptive Fault Diagnosis of DC-DC Boost Converters in Photovoltaic Systems Based on Sliding Mode Observers with Dynamic Thresholds

Year: 2025

Type: article

Abstract: A robust methodology for parametric fault diagnosis in photovoltaic systems is proposed, focusing on DC-DC boost converters. The methodology uses Adaptive Sliding Mode Observers (ASMO) combined with adaptive thresholding. Specifically, an observer-based scheme detects and isolates faults in passive components of the converter, achieving complete isolation in about 0.05 s, even under varying environmental conditions. In addition, a dynamic fault discrimination approach is introduced, based on adaptive thresholds derived from Exponentially Weighted Moving Average (EWMA). This minimizes false alarms caused by transient conditions. Stability and robustness are guaranteed through Lyapunov-based conditions. Simulation results under sequential and simultaneous fault scenarios confirm rapid and precise fault detection, highly specific isolation, and exceptional resilience against environmental disturbances.

Source: Electronics

DOI: 10.3390/electronics15010040

Authors: Maouadda Ismail, Karim Dahech, Fernando Tadeo, Tarak Damak, Mohamed Chaabane

Institutions: University of Sfax, Universidad de Valladolid

Language: English

Topic: Fault Detection and Control Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,896