Genetic algorithm based design optimization of a three-phase multiflux Induction Motor

More than 80% of three-phase Squirrel Cage Induction Motors(SCIMs) are widely used in industrial and domestic applications because of the relatively low cost and high reliability. When oversized, most of these motors operate with low efficiency. The objective of this paper is to develop a unique design for a three phase, multi-flux, stator winding SCIM to improve the efficiency. Adjustable flux motors with multiple winding connections can be an energy efficient solution in variable and fixed load applications, improving the efficiency by means of properly adapting motor flux to the actual load. In this paper, a design optimization method is proposed. The optimal design of multiconnection, multiflux stator winding to improve motor efficiency in a wide load range is proposed using Genetic Algorithm (GA). This algorithm is a population-based search algorithm characterized as conceptually simple, easy to implement and computationally efficient. A parameter-less loss approach is incorporated in the proposed algorithm to handle the constraints effectively. A comparison of the final optimum designs with the existing design for a 7.5-kW motor is presented, demonstrating that the optimal designs produce larger efficiency in all load range. The importance of this work is highlighted by the recent concerns about the need to achieve energy savings in industry.