Title :
Electrical machine optimization using a kriging predictor
Author :
Duchaud, J.-L. ; Hlioui, S. ; Louf, F. ; Gabsi, Mohamed
Author_Institution :
SATIE, ENS Cachan, Cachan, France
Abstract :
This paper presents an optimization on a surface response created by kriging. It focuses on the predictor creation, its refinement and on the advantage of such a method over a direct optimization. In order to reduce the number of evaluations needed to construct the predictor, an adaptive method for the trial site selection is introduced as an improvement for the Latin Hypercubic Sample (LHS) algorithm. The method is applied to the optimization of a flux switching synchronous machine and the results are illustrated for two and four parameters.
Keywords :
interpolation; optimisation; regression analysis; sampling methods; synchronous machines; LHS algorithm; computation time reduction; direct optimization; electrical machine optimization; flux switching synchronous machine optimization; kriging predictor; latin hypercubic sample algorithm; surface response optimization; trial site selection; Computational modeling; Correlation; Optimization; Prediction algorithms; Predictive models; Switches; Torque; Adaptive kriging; computation time reduction; electrical machine; metamodel; optimization; surrogate model;
Conference_Titel :
Electrical Machines and Systems (ICEMS), 2014 17th International Conference on
Conference_Location :
Hangzhou
DOI :
10.1109/ICEMS.2014.7014091
