Projeto iterativo, simulação, análise e otimização de máquina a relutância variável monofásica

• Autor(a) principal: Mamede, Ana Camila Ferreira
• Data de Publicação: 2016
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFU
• Texto Completo: https://repositorio.ufu.br/handle/123456789/17586; http://doi.org/10.14393/ufu.di.2016.401
• topic: Engenharia elétrica; Algoritmos genéticos; Otimização; Eletrodinâmica; Motor de relutância variável; Procedimentos de projeto; Análise de elementos finitos; Saturação magnética; Evolução diferencial; Switched reluctance motors; Design procedures; Finite element analysis; Magnetic saturation; Differential Evolution; Genetic Algorithm; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA

Variable reluctance motors have been increasingly used as an alternative for variable speed and high speed drives in many industrial applications, due to many advantages like the simplicity of construction, robustness, and low cost. The most common applications in recent years are related to aeronautics, electric and hybrid vehicles and wind power generation. This paper explores the theory, operation, design procedures and analysis of a variable reluctance machine. An iterative design methodology is introduced and used to design a 1.25 kW prototype. For the analysis of the machine two methods are used, an analytical method and the finite element simulation. The results obtained by both methods are compared. The results of finite element simulation are used to determine the inductance profiles and torque of the prototype. The magnetic saturation is examined visually and numerically in four critical points of the machine. The data collected in the simulation allow the verification of design and operating limits for the prototype. Moreover, the behavior of the output quantities is analyzed (inductance, torque and magnetic saturation) by variation of physical dimensions of the motor. Finally, a multiobjective optimization using Differential Evolution algorithms and Genetic Algorithms for switched reluctance machine design is proposed. The optimized variables are rotor and stator polar arcs, and the goals are to maximize the average torque, the average torque per copper losses and the average torque per core volume. Finally, the initial design and optimized design are compared.