Cogging Torque Minimisation of PM Synchronous Motor Using Nature Based Algorithms

Abstract

The permanent magnet brushless DC motors and permanent magnet synchronous motors have been widely used in industrial high performance applications in recent years. Although they have good electrical, magnetic and performance characteristics there is one parameter named cogging torque that has a negative influence on the performance characteristics of the motor. This pulsating torque is produced due to the interaction between the stator teeth and the permanent magnets. The minimization of the torque ripple in those permanent magnet motors is of great importance and is generally achieved by a special motor design which in the design process involves a variation of many geometrical motor parameters. In this paper a novel approach is introduced where different nature inspired algorithms, such as genetic algorithm and cuckoo search algorithm are used as a torque minimization tool, where the function definition of the maximum value of the cogging torque is used as an objective function. For that purpose, a proper mathematical presentation of the maximum value of the cogging torque for the analyzed synchronous motor is developed and used. For the purpose of the different motor models analysis, the initial motor and the optimized motor models are modelled and analyzed using a finite element method approach. The cogging torque is analytically and numerically calculated and the results for all the models are presented.