An Application of Latin Hypercube Sampling Strategy for Cogging Torque Reduction of Large-Scale Permanent Magnet Motor

An adaptive response surface method with Latin hypercube sampling strategy is employed to optimize a magnet pole shape of large-scale brushless direct current (BLDC) motor to minimize the cogging torque. The proposed algorithm consists of the multi-objective Pareto optimization and (1+ lambda) evolu...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on magnetics 2008-11, Vol.44 (11), p.4421-4424
Hauptverfasser:	Shin, P.S., Woo, S.H., Zhang, Y., Koh, C.S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Brushless DC motors Brushless direct current (BLDC) motor cogging torque Cross-disciplinary physics: materials science rheology Exact sciences and technology Forging Hypercubes Large-scale systems Latin hypercube sampling Magnetism Materials science optimization Optimization methods Other topics in materials science Permanent magnet motors Physics response surface method Response surface methodology Sampling methods Shape Torque
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!