Lamination optimization of a given HEM motor for vacuum cleaners by using genetic algorithms
2001 - 2003
The efficiency (i.e., output power versus input power) of a universal motor depends on various losses: i.e., iron losses, copper losses and other losses like brush losses, friction and ventilation losses. Iron losses include the hysteresis and the eddy-current losses, primarily in the armature core and the pole faces. Copper losses are the joule losses in the stator's and the rotor's windings. Our evolutionary approach provides a computer support in the very early design phase, when the engineer has to find an optimal configuration of the rotor's and the stator's geometrical parameters. We have applied the GA as an optimization method that provides robust and yet flexible search in the complex space of the problem solutions. After several runs of our optimization program, we collected a set of solution candidates, which seem to be promising. The power loss was reduced by nearly 30% according to the previous design.