In a design of a switched reluctance machine, there are a number of parameters that are chosen empirically inside a certain interval, therefore to find an optimum geometry it is necessary to determine how each parameter acts on the performance of the machine. This work presents a study on the influence of geometric dimensions on the performance of the switched reluctance machine. The analysis is done through finite element simulations based on the variation of one parameter while the others are fixed. Graphical and numerical results of torque and magnetic flux are presented for a 6/4 three-phase machine and an 8/6 four-phase machine. The study presented aims to provide consistent data on which dimensions should be modified for specific applications, and thus to base choices made in the design and optimization stage.
-Variable reluctance motors have been increasingly used as an alternative for variable speed drives in many industrial applications, due to many advantages like it's construction simplicity, robustness, and low cost. For low power applications, the single-phase variable reluctance motors stands out because the simplicity of the drive contributes to the cost reduction of the machine. This paper presents a design methodology for single-phase variable reluctance motors and a way to survey of ideal profiles of inductance and torque produced by the motor through computational simulation using finite element methods. The simulation is performed for various currents in order to determine the maximum motor operating current through the analysis from the saturation of magnetic materials. In addition, an analysis is made on the influence and importance of rotor and stator polar arcs in the design of reluctance motors based on its driving system. The prototype has been designed to replace a single-phase induction motor with 0.18 kW and has four poles on stator and rotor, the nominal power is 0.125 kW and can deliver up 0.30 kW when operated with the maximum allowed current.
Aos meus pais, Luiz Mamede e Márcia Mamede, pelo carinho, paciência e compreensão, pelos primeiros e mais importantes ensinamentos e por serem grandes mestres e exemplos.Às minhas irmãs, Mariana Mamede e Ana Luíza Mamede, família e amigos, pela companhia e apoio.Ao Prof. PhD José Roberto Camacho, mestre durante a graduação e pós-graduação, pelo grande incentivo, motivação, orientação, compreensão, confiança, generosidade e amizade transmitidos durante todo o trabalho.Aos colegas do Núcleo de Pesquisa e Extensão em Energias Alternativas da Universidade Federal de Uberlândia, pelo acolhimento, convívio, companheirismo, ensinamentos e amizades compartilhados durante o período do mestrado.
The work deals with the application of artificial neural networks (ANNs) in the modeling of switched reluctance machines (SRMs). The performance of a SRM is determined by its geometry, materials used and levels of excitation. In this way, this work investigates the influence of the stator and rotor back iron thickness in the performance of SRM. A multilayer neural network is proposed to learn the nonlinear characteristics of the motor. Data of flux linkages and torque are obtained through simulations of finite elements and used for ANN training. The algorithm developed in Octave allows the user to adjust the network parameters. The results presented confirm the feasibility of using ANN to establish a predictive model of SRM performance, thus enabling further investigation in the future.
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