Efficiency and Cost Optimized Design of an Induction Motor Using Genetic Algorithm

In the context of electricity shortage and an attempt to save the environment, introduction of energy efficient motors in different fields of application has become a necessity. This paves the way for fusing the conventional machine design procedures with optimization techniques. Unfortunately, the mathematics of electrical machine design involves calculations with highly nonlinear equation sets, and hence the conventional analytical optimization techniques do not fit well. In this study, design of an efficiency-optimized squirrel cage induction motor is considered, where genetic algorithm is chosen as the tool for optimization. The various constraints considered are selected on the basis of material, mechanical, and performance considerations as approved by standards and practices. The influence of change of materials and change of upper limit of customer's budget on different key motor design performance indicators are studied with and without cost constraints. Also, a systematic and statistics-based approach is proposed to achieve an optimized motor design, even at very low cost, provided relaxation of some constraints is allowed by the specific application. The optimized results are validated through tests on laboratory prototypes.