Design optimization with genetic algorithm of open slotted axial flux permanent magnet generator for wind turbines

Abstract

In this study, the design parameters of Open Slotted Axial Flux Permanent Magnet (OSAFPM) Generator for wind turbines are presented using Genetic Algorithms (GA), an optimization algorithm based on natural selection and genetic mechanisms. Electromagnetic analysis of Open Slotted Axial Flux Permanent Magnet generator has been performed by using parameters optimized with Genetic Algorithms. The ANSYS Maxwell program, which uses the finite element method (FEM), has been used for electromagnetic analysis. Compared to ANSYS Maxwell, it is observed that the genetic algorithm significantly reduces the computational time required for design optimization. However, initial design and optimization with Genetic Algorithms have resulted by 8.94% increase in power densities. In addition, 12.71%, 38.62%, 62.02%, and 56.39% improvements have been obtained for air gap magnetic flux density, flux linkage, induced voltage, and current waveforms, respectively. This suggests that optimization with a Genetic algorithm improves the Open Slotted Axial Flux Permanent Magnet generator parameters.