Design Optimization of a 4-Poled 1500 rpm 25 kVA SG to Obtain the Desired Magnetic Flux Density Distributions by using RSM
In this study design optimization for 4-poled 1500 rpm 25 kVA synchronous generator (SG) is performed. The aim is to determine the optimum factor levels for the design parameters namely slot opening width (Bs0), height, and width to keep the responses namely ‘pole-body flux density’ and ‘air-gap flux density’ distributions in a desired range. The target values are determined as 1.75 Tesla and 0.9 Tesla for the ‘pole-body flux density’ and ‘air-gap flux density’ respectively. For this purpose, Response Surface Methodology (RSM) is used for optimization. Numerical simulations are performed in the Maxwell environment and the optimization by RSM is performed by Minitab statistical package. Desired goals were achieved and optimum factor levels were determined with RSM. Then the results of RSM are compared by Genetic Algorithm (GA), Particle Swarm Optimization algorithm (PSO), and Modified Social Group Optimization (MSGO) algorithm. These methods are evaluated together in terms of advantages and disadvantages. The comparisons indicate that using RSM provides acceptable results without performing coding effort and also provides users to understand the relations visually between the factors and the responses by the aid of ‘Minitab Response Optimizer Module’.
Electric machine design, Genetic algorithm, Regression, Response surface methodology, Synchronous generator
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