Método de detecção de falhas em motores decorrente contínua sem escovas utilizando análise do caos

Abstract

This presented work contributes to the development of a novel fault diagnosis method in Brushless Direct Current (BLDC) motors. These have been used in several applications of electric vehicles. Some advantages, such as low maintenance demand and ability to work in hostile environments. One of the applications given to BLDC motors is in Remotely Piloted Aircraft (RPA), popularly known as drones, that have a wide variety of uses and applications. So, there is a growing need for security and safety solutions. Thus, it was noticed that there is a demand to develop a real-time diagnostic strategy to be embedded in RPA. This work present a technique for the diagnosis of working behavior in BLDC motors. From analysis of the chaotic behavior of the electric current signal, measured by the maximum density of the function, preliminary results demonstrated the efficacy of new technique under stationary and non-stationary conditions, opening the possibility of improving the technique and developing the embedded motor diagnostic solution.