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The world is experiencing an accelerated energy transition that is driven by the climate goals to be met and that has driven the growth of different potential sectors such as electric mobility powered by electric motors, which continue to be the largest load globally. However, new needs in relation to power density, weight, and efficiency have led manufacturers to experiment with new technologies, such as rare earth elements (REEs). The permanent magnet motor is a candidate to be the substitute for the conventional induction motor considering the new editions of the IEC 60034-30-1, for which study and evaluation continue to be focused on identifying the weaknesses and benefits of its application on a large scale in industry and electric mobility. This work presents a FEM model to assess the line-start permanent magnet motor (LSPMM), aiming to simulate the behavior of the LSPMM under supply conditions with distorted voltages (harmonic content) and evaluate its thermal and magnetic performance. The model created in the FEM software is then validated by bench tests in order to constitute an alternative analysis tool that can be used for studies in previous project phases and even to implement predictive maintenance schemes in industries.

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Resumo: Este artigo é de natureza qualitativa e quantitativa e apresenta a perspectiva dos alunos quanto ao plano de ensino adotado na disciplina de materiais elétricos do curso de Engenharia Elétrica no período de Ensino Remoto Emergencial (ERE) da Universidade Federal do Pará (UFPA), onde a coleta desses relatos ocorreu por meio de questionário aplicado no final da matéria. Foram utilizadas metodologias como sala de aula invertida vinculada à gamificação, além de simulações computacionais. Os recursos utilizados para o desenvolvimento das atividades propostas foram videoaulas compartilhadas previamente com os alunos, aplicando assim os conceitos de sala de aula invertida, a plataforma Kahoot, que permitiu a criação de um quiz para a gamificação das atividades e o uso de um software de simulação eletromagnética para aplicação do método de Aprendizagem Baseada em Projetos (PBL). Além disso, este estudo também destaca o potencial desse modelo de ensino e mostra que a aplicação dessas metodologias são válidas e amenizam alguns problemas enfrentados pelos alunos durante o período de pandemia ocasionado pela

Electric induction motors are the type of motor most commonly operated in industry, and for this reason technologies that predict faults and reduce the corrective maintenance are of great interest. In this context, this paper presents a predictive maintenance tool of electric motors using the concepts of Digital Twin (DT) and Industrial Internet of Things (IIoT). The proposed system is innovative, as it monitors the motor current and temperature by means of sensors and a low-cost acquisition module, and these measurements are sent via Wi-Fi to a database. The concept of DT was leveraged by providing the measurements as inputs to a high-fidelity strongly-coupled model of the monitored monitor, using the Finite Element Method (FEM). The results obtained are satisfactory, because the sensors used presented acceptable errors that do not interfere with the reliability of the results. The computer simulation showed relative errors below 4% in the conductivity analysis and 10% in the temperature analysis. In addition, the simulation allows verifying the internal temperature of the motor, its resistive losses, and the intensity of the magnetic flux at each pole. It is worth pointing out that the internal analysis performed is only possible due to the combination of IIoT and computer simulations. Therefore, they allow a better diagnosis of the motor's operational status and also a time estimate for the next maintenance service, thus being ideal for the industrial sector.INDEX TERMS Condition monitoring, digital twin, finite element analysis, induction motors, Internet of Things.