Preparation of an optimisation algorithm for motor design

In this study, an optimization of a permanent magnet synchronous motor design has been aimed in terms of sensorless control using another variation of particle swarm optimization algorithm, which was developed inspired by bird or fish school moving synchronously, particle swarm optimization with passive congregation.Particle swarm optimization with passive congregation algorithm first was developed on MATLAB environment and then examined on some well-known non-linear functions such as Rastrigin, Schwefel and Michalewicz which are widely used for examination of optimization algorithms. The algorithm written was then adapted to software, previously developed on MATLAB environment again, that can obtain communication with an external finite elements analysis based, capable of designing and measuring performance of a motor.The given eight interior variables have been optimized by fixing the outer geometry of the motor. In order to enhance torque and sensorless control capability, design optimizations has been made for two different objectives. While optimizing the sensorless control capability of the permanent magnet synchronous motor, torque performance decreases. It has been tried to increase sensorless control capability by compromising torque value too little with a third design optimization.The performance results for each design optimization have been given and compared. In addition to this, the effects of ±5-10% change for each design variable have been investigated.