Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation

Abstract

Both permanent magnet brushless DC motors and permanent magnet synchronous motors have been of wide interest and increasingly used in industrial high performance applications in recent years. Those motors are known for their good electrical, magnetic and performance characteristics, but there is one parameter known as cogging torque that has a negative influence on the performance characteristics of the motor. This pulsating torque is generated as a result of the interaction between the stator teeth and the permanent magnets. The minimization of the ripple of this torque is of great importance. In this research work a novel approach will be introduced where two different nature inspired algorithms, such as genetic algorithm and cuckoo search algorithm are used as an optimization tool, in which the defined equation for the maximum value of the cogging torque is applied as an objective function. Therefore, a proper mathematical presentation of the maximum value of the cogging torque for the analysed synchronous motor is developed and implemented in the research work. For the deepened analysis of the three different motor models, the initial motor and the two optimized motor models are modelled and analysed using a finite element method approach.