Abstract
The development of the robotics and the automation and the need for the motors that can work in the applications that require high speed, precision and increased efficiency have led to the increased use of permanent magnet synchronous motors and their continuous development in terms of improving their performance. Cogging torque is one of the features of these types of the motors that deteriorate motor performance especially at low speeds. Therefore, in this paper the method of genetic algorithms (GA) is applied as an optimization tool, for minimizing the cogging torque without changing the other important operating parameters like output power, torque or current. Even more, the optimized motor model has improved efficiency compared to the starting model and has the decreased weight of the permanent magnets. The optimization is done by changing the rotor design in terms of the magnet thickness, pole span and shape of the magnets. Finite elements (FE) models of the optimized and the basic motor were derived and from them the flux density distribution in the motor cross section and in the air gap was calculated. In addition, the improvement of the motor operation is observed from the torque characteristics calculated by the FE models.