STRUCTURAL OPTIMIZATION OF AN INDUCTION-MOTOR USING A GENETIC ALGORITHM AND A FINITE-ELEMENT METHOD

Several dozen variables affect the characteristics of an electric moto r. The magnetic circuit of an electric motor is highly non-linear and analytically it is not possible to calculate the torque or losses in m otors with sufficient accuracy for optimisation of the near air gap re gion. Only with the finite element method (FEM) is it possible to obta in sufficient accuracy. To be able to accurately evaluate the losses c aused by higher harmonics the time-stepping method is needed to simula te the rotation of the rotor. The purpose of this work is to design an d to test a method for structural optimisation and to use this method for the design of a new slot shape for induction motors, especially in the optimisation of the near air gap region. This method enables the design of more efficient and smaller motors, or vice versa, design of motors with a higher shaft power from the same amount of materials. Th is optimisation method is based on a genetic algorithm, and it is appl ied to the optimisation of the slot dimensions and the whole slot geom etry with different voltage sources and optimisation constraints. In t he genetic algorithm, optimisation is based on a population. The algor ithm changes an entire population of designs instead of one single des ign in optimisation. The FEM is not accurate, i.e. all the changes in the mesh do not necessarily correspond real improvements in the charac teristics of a motor. To improve the reliability of the optimisation r esults with FEM, the average design of the population is studied. The results obtained clearly indicate the usefulness and the effectiveness of both the optimisation method selected and the FEM in a design for induction motors.