A new global optimization approach for induction motor design
K. Idir, Liuchen Chang, Heping Dai · 2002
This paper proposed a new global optimization approach for electric machine design problems. Its algorithm uses the error function between the actual cost function at a given computational step, and its limit value which is lower than the desired global minimum. The error function provides a good indication of how far or close the cost function is approaching its limit solution. This method may be considered to be self adaptive in a sense that the higher the error is, the higher the step size of the variables will be. This feature will help the function to escape local solutions and tend to reach the targeted solution. The proposed approach has been tested on various typical multimodal functions and particularly, applied to induction motor design optimization problems. The algorithm of this method is very simple and easy to implement but yet powerful and effective as highlighted in the test results.