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.

The objective of this paper is to investigate the behavior of electromagnetic forces during the occurrence of faults inside transformers as result of transients in the electrical systems. The methodology is based on the modeling of a single-phase 50-MVA transformer subjected to inrush currents through finite-element method. In this perspective, the values of inrush currents, obtained by the alternative transient program software, are used to estimate the magnetic field density dispersion in the transformer, and to find the values of forces in axial and radial directions. These forces components are distributed along the energized windings for observing the loads behavior in high-voltage windings. This paper will thus present investigations of electromagnetic forces, structural deformation, stresses, and safety factor on transformer's winding when subjected to inrush current.

Among the main problems faced in the context of electric mobility today, the management and monitoring of electric vehicle charging stations, the integration between the diverse types of technologies that make up its architecture, and its low scalability stand out. Therefore, we will present the implementation and complete integration of an electric vehicle charging system in an electric mobility pilot project being executed in the Amazon region in Brazil. Therefore, a literature review of related works will be presented, and its entire implementation will be addressed, from the charging infrastructure, through its back-end system and its Internet of things platform, to its front-end web system for monitoring charging stations. In addition, a complete prototype is created with a real testbed to verify the scalability of the implemented physical system. Based on the testbed evaluations performed, we observe that the implemented system performs well in receiving and sending data from up to 160 electric vehicle charging stations, achieving an average consumption of 26% for CPU and 95% for memory. In addition, it is important to mention that the deployed system supports horizontal scalability, enabling the connection of more charging stations and making it ideal for other integrated systems similar to ours. Based upon the main results obtained with the implemented system, the possibility of carrying out the management and monitoring of charging stations stands out; the integration of different technologies, from the back end and IoT middleware to its front end; a system that supports scalability, enabling the connection of more charging stations; and a reference architecture for charging station management and monitoring systems for the Amazon region.

The main objective of this paper is to assist in the investigation of electromagnetic forces, structural deformation, stresses, and Safety factor when energizing unloaded transformers. The methodology is based on modeling of a single-phase 50 MVA tra

Important industrial applications are based on magnetohydrodynamics (MHD), which concerns the flow of electrically conducting fluids immersed in external magnetic fields. Using the Finite Volume Method, we performed a 3D numerical study of the MHD flow of a conducting fluid in a circular duct. The flow considered was laminar and fully developed. Along the initial section of the duct, there were magnets placed around the duct producing magnetic fields in the radial direction. Two arrangements of magnetic field orientation were considered: fields pointing toward and away from the duct’s center alternately, and all fields pointing toward the duct’s center. For each arrangement of magnets, various intensities of magnetic fields were considered to evaluate two effects: the influence of the magnetic field on the flow velocity, and the influence of the flow velocity on magnetic field induction. It was found that for the second arrangement of magnets and Hartmann numbers larger than 10, the flow velocity was reduced by as much as 35%, and the axial magnetic induction was as high as the field intensity applied by each magnet. Those effects were negligible for the first arrangement and low fields because of the distribution of field lines inside the duct for these situations.