The main objective of this work is the development of an embedded system for the diagnostics of power electronic converters. Nowadays, such systems require a high level of reliability and self-diagnostic capability; in fact, recent research has paid particular attention to diagnostic methods for DC-DC converters. For instance, estimating certain parameters in power electronic converters provides a very useful tool for diagnosing systems that integrate these converters.The occurrence of a fault is often due to the degradation of passive components in the converters, a phenomenon that can compromise the entire system and even cause its complete shutdown. For this reason, it is essential to constantly assess the condition of passive components and monitor their “health status” by observing specific vital parameters, thereby enabling the development of more reliable systems.Further improvement can be achieved from a predictive perspective, as it becomes possible to forecast the failure of certain components and identify them in advance. Consequently, the rapid replacement of faulty components allows the system to resume operation in a short time, avoiding more severe problems.In this work, a typical boost converter is considered, and the Equivalent Series Resistance (ESR) is estimated using the least squares method implemented on a Nucleo STM32 F303RE development board. From the ESR estimation, the health status of the boost converter can be determined.
Antonino Pagano (Fri,) studied this question.