<![CDATA[In a wide range of applications, such as smart buildings, electric vehicles, hybrid systems, and renewable energy, dc dc converters are crucial. The dc dc converters have many topologies, and the boost converter is one of the most important. The problem. The boost converter is connected to other sensitive devices and components, so any fault in the Boost converter will lead to a system issue, which may cause catastrophic damage to humans and related devices. These faults include parameter degradation of passive components, open switch failure, and sensors failures. Goal. The development of a fault detection and identification scheme for a dc-dc boost converter is the main goal of this study. Therefore, it is essential to make sure that the converters are safe from malfunctions and that there are no major accidents or disasters in order for them to carry out their vital jobs. Methodology. The scheme covers a wide range of potential faults, such as parametric degradation of passive components, open switch fault, and sensors failures. We created the scheme as a structured algorithm based on residuals between observers and measurements from the sensors, residuals between open switch fault signature and measurements from the sensors, residuals between assumed values of the sensors and real measurements, and carefully considered thresholds to compare these residuals with. Results. Simulations were used to assess the proposed scheme. The results show the effectiveness of the scheme in detecting and identifying faults quickly and accurately. The originality. of this work lies in the creation of a fault detection and identification scheme using luenberger observers and specific thresholds without the need for additional sensors or devices.]]>
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