Design optimization of PMSM by particle swarm optimization and genetic algorithm

One of the electric power researches is the design optimization studies of permanent magnet synchronous motors. The main advantages of design optimizations of permanent magnet synchronous motors are to contribute to comfort, cost, and especially to energy savings. Although absence of rotor windings affects efficiencies of permanent magnet synchronous motors, stringent selection of values of geometrical design parameters affects the efficiency. Artificial intelligence techniques are satisfactory in choosing of design parameters of electric motors. This study aims to provide the design optimization of surface mounted permanent magnet synchronous motor thus. First of all geometrical design parameters of the motor were identified and then preliminary analytical design and design optimization by using genetic algorithm and particle swarm algorithm were studied. The obtained efficiency results were compared with each others and the results is satisfactory.