Switch fault diagnosis for boost DC-DC converters in photovoltaic MPPT systems by using high-gain observers

Abstract

Open- and short-circuit faults (OSCFs) in boost dc-dc converters for photovoltaic (PV) maximum power point trackers (MPPTs) imply an inefficiency after fault is triggered, which affect the security and profitability of PV projects. Hence, fault detection and isolation (FDI) techniques have become an important issue for PV technology. In this study, a model-based FDI technique is proposed to boost dc-dc converters in PV MPPT systems. As is well-known, major issues of model-based FDI techniques have always been parametric uncertainty and no-modelled dynamics. This study focuses on how to mitigate these shortcomings by applying a high-gain observer (HGO) as a residual generator. A striking feature of HGO's is that exponential stability is still guaranteed for bounded disturbances (or faults). As demonstrated in this study, under an integral control action in the closed-loop control system, OSCFs are characterised for ever-growing signals, enabling the suggested FDI scheme. Also, the FDI proposal is decoupled from PV current (irradiance changes) and load variations, thereby avoiding false alarms. Moreover, the output-injection gain and thresholds are selected such that the fault diagnosis is achieved in eight switching cycles, enabling a fast and reliable diagnosis. Experimental results are illustrated to validate the FDI scheme proposed in this study.