Optimization Of Interior Permanent Magnet Synchronous Motor Using Evolutionary Optimization Algorithm

Abstract

The development of the interior permanent magnet synchronous motor has drawn a big interest over the last decade. This is due to the use of this kind of machine in the automotive industry, thanks to the machine high efficiency and high overload capability compare to other machine types. Using artificial intelligence or evolutionary optimization algorithms is possible to optimize the motor with maximum efficiency, lowest torque ripple and highest average torque, because a huge ammount and variety of geometry combinations are tested. This paper is focused on the overview of generally used optimization algorithms and optimization is demonstrated on Self-Organizing Migrating Algorithm (SOMA). Cost function and weight coefficients are also presented and used for optimization.