Abstract
Recently, model-based approaches have been proposed for fault diagnosis as an emerging alternative to traditional techniques. Particularly, the inversion-and observer-based were proposed for fault diagnosis as successful model-based approaches. However, the research's results related to these approaches are reduced and generally applied to a specific converter or control type. Therefore, the inversion-and observer-based approaches performance presented in the literature does not permit to compare both techniques in order to conclude which one is more suitable for fault diagnosis. In this context, this paper presents a comparative study of inversion-and observer based approaches for fault diagnosis in a DC-DC boost converter. More specifically, after modeling both the power converter and the fault detection and isolation methods, it were inserted faults on the transistor and capacitor (degradation) in order to validate the performance of the proposed approaches. The results demonstrate that these are efficient alternatives to the conventional techniques that are usually used for fault diagnosis in power electronics systems. Both inverse-and observer-based approaches showed similarities and effectiveness in detecting and isolating faults on the studied DC-DC boost converter.

Abstract
This paper addresses the problem of the left inversion of switched linear systems from a diagnostics perspective. The problem of left inversion is to reconstruct the input of a system with the knowledge of its output, whose differentiation is usually required. In the case of thiswork, the objective is to reconstruct the system's unknown inputs, based on the knowledge of its outputs, switching sequence and known inputs. With the inverse model of the switched linear system, a real-time Fault Detection and Isolation (FDI) algorithm with an integrated Fuzzy Logic System (FLS) that is capable of detecting and isolating abrupt faults occurring in the system is developed. In order to attenuate the effects of unknown disturbances and noise at the output of the inverse model, a smoothing strategy is also used. The results are illustrated with an example. The performance of the method is validated experimentally in a DC-DC boost converter, using a low-cost microcontroller, without any additional components.

Abstract
This paper presents theory, a new approach and validation results for fault detection and isolation (FDI) in DC-DC power converters, based on inversion method. The developed method consists on the inversion-based estimation of faults and change detection mechanisms adapted to the power converters context. With the inverse model of a switched linear system, we have designed a real-time FDI algorithm with an integrated fuzzy logic scheme which detects and isolates abrupt changes (faults) at unknown time instants. A smoothing strategy is used to attenuate the effect of unknown disturbances and noise that are present at the outputs of this inverse model. Once the fault event is detected, a dedicated fuzzy-logic-based scheme is proposed to isolate the four types of faults: switch, voltage and current sensor, and capacitor. The performance of the proposed method is verified experimentally to detect and isolate the mentioned faults in the DC-DC boost power converter.

Abstract
Modeling is a key step in the design of energy and control systems. It allows us to simulate and predict the behavior of electronics converters, even before constructing them. This is instrumental, for example, for sizing, component selection and preliminary validation of the converter's functionality. It also enables us to design model-based controllers for the converter and regulate the amount of transferred power, which can be done using simulation tools. This article introduces the main tools employed in the mathematical modeling of power converters, with a particular focus on linear approximations and average models. © 2023 Elsevier Inc. All rights reserved.

Abstract
The goal of this article is to introduce the fundamental notions and concepts of stability analysis for linear and nonlinear systems in the context of electronic power conversion. Power electronic circuits have strong nonlinear behavior in their essence; often we need to linearize them to understand their properties and study their stability with the applied control laws. We present different concepts of stability (internal, input-output, Lyapunov-based), observability and controllability, as well as practical tests to check these properties. We then apply these tests in the context of a single power converter example, a DC/DC boost converter. © 2023 Elsevier Inc. All rights reserved.

Abstract
This paper presents FIEEV - Fault Injection Environment for Electric Vehicles, a Matlab/Simulink-based simulator environment for evaluating the fault impacts on vehicle stability in electrical vehicles. FIEEV makes it possible to simulate the temporal behavior of the faults and to study its effects on loss of vehicle's performance. Simulation results are presented to prove the validity of the presented framework. © 2012 IEEE.