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.
Abstract. In the last years we have witnessed a growing interest, by the academic community and the automotive industry, in the multi-motor electric vehicles. The electrical nature of the propulsion is going to stress even more an increasing insertion of electronic devices in the vehicles. Furthermore, carmakers are performing research and already presented some vehicles based on the concept of X-By-Wire. Consequently, the growing complexity of the actuators and their control, as well as the need of increasing the safety and reliability of the vehicles obliges to the study and development of intelligent computational systems dedicated to the detection and diagnosis of failures in the electric propulsion. Hence, it is fundamental to start advanced studies leading to the development of innovative solutions that embed fault-tolerant electric propulsion in the electric vehicles. Accordingly, the main objective of this work consists on the bibliographic revision and study of fault-tolerant diagnosis and control systems dedicated to multi-motor electric vehicles.
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 this work, 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.
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