Parameters identification of 11-phase Torus generator using particle swarm optimization technique

Axial-flux, Permanent-magnet machines are used in different applications where the power and torque density requirements are very high. These machines have simple structures, relatively high efficiencies and low cost. The parameters of these machines are very small compared with the parameters of conventional machines. Different measuring methods are normally used in order to obtain good estimates of the machine parameters. These methods are difficult to perform, costly and time consuming. This paper proposes the use of particle swarm optimization (PSO) technique to predict the self and mutual inductances of the 11-phase torus machine automatically.