Design, Analysis, and Prototyping of an Axial-Flux Permanent Magnet Motor Based on Genetic Algorithm and Finite-Element Analysis

Abstract

This paper presents an axial-flux permanent magnet motor optimized by the genetic algorithm (GA)-based sizing equation and the finite-element analysis (FEA). The designed slotted TORUS motor produces sinusoidal back-EMF waveform, maximum power density, and reduced cogging torque. The GA obtained the dimensions of motors with different numbers of slots and the highest possible power density. Electromagnetic field analysis of the candidate motors obtained from GA with various dimensions is subjected through FEA to obtain the motors' characteristics. Based on the GA and FEA results, a candidate motor design is introduced and subjected to FEA for reoptimization and finalization of the motor design. Techniques like modifying winding configuration and permanent magnet skewing are investigated to attain the most sinusoidal back-EMF waveform and reduced cogging torque. FEA and GA simulation results are compared and agreed well to the flux density in various areas of the designed motor at no-load condition. The final designed motor (1 kW, 50 Hz, four poles) is fabricated and tested. Experimental results agree with those of the simulation, both satisfying the desired technical specifications.