Abstract
This paper presents an optimal design method to optimize three-phase induction motor in manufacturing process. The optimally designed motor is compared with an existing motor having the same ratings. The Genetic Algorithm is used for optimization and three objective functions namely torque, efficiency, and cost are considered. The motor design procedure consists of a system of non-linear equations, which imposes induction motor characteristics, motor performance, magnetic stresses and thermal limits. Computer simulation results are given to show the effectiveness of the proposed design process.
Highlights
Induction motors are the most widely used in domestic, commercial and various industrial applications
The squirrel cage type is characterized by its simplicity, robustness and low cost, which has always made it very attractive, and it has captured the leading place in industrial sectors
If the standard non-linear programming (NLP) techniques were to be used in such cases, they would be computationally very expensive and inefficient
Summary
Induction motors are the most widely used in domestic, commercial and various industrial applications. One of the most important advantages of the GA over the standard NLP techniques is that it is able to find the global minimum, instead of a local minimum, and that the initial attempts with different starting point need not be close actual values. Another advantage is that it does not require the use of the derivative of the function, which is not always obtainable or may not even exist, for example, when dealing with real measurements involving noisy data. Threephase squirrel-cage type induction motor having specifications 30 hp,380V, star connected, 4 pole, is chosen for comparison with three optimally designed motors. It was observed that the cost optimization procedure was sensible, and the performance results obtained were promising
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