Global sizing optimisation using dual-level response surface method based on mixed-resolution central composite design for permanent magnet synchronous generators

This study presents a global sizing design optimisation of a permanent magnet synchronous generator (PMSG) using the three-dimensional finite-element analysis (3D FEA). To build an optimal parametric model structure, the efficiency improvement of the PMSG is taken as the main objective, where iron a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IET electric power applications 2018-05, Vol.12 (5), p.684-692
Hauptverfasser: Asef, Pedram, Perpina, Ramon Bargallo, Barzegaran, Mohammadreza
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This study presents a global sizing design optimisation of a permanent magnet synchronous generator (PMSG) using the three-dimensional finite-element analysis (3D FEA). To build an optimal parametric model structure, the efficiency improvement of the PMSG is taken as the main objective, where iron and copper losses were minimised. A dual-level response surface methodology (D-RSM) with a window-zoom-in approach for a variable-speed-range analysis as a global optimisation technique is employed to find out the optimal design variables of the objective function. The D-RSM using mixed-resolution central composite design (MR-CCD), full factorial design, central composite design (CCD), and box-Behnken design are applied to optimise the geometry with very small error. Analysis of variance and multi-level RSM plots are used to check the adequacy of fit. However, the MR-CCD exceeds the range of the boundary in the design region. Hence, a modified MR-CCD is used that improves the efficiency and proposes the parameter settings to manufacture the high-class quality wind generator. The validation of the analytical and numerical fashions is successfully achieved through rigorous FEA, and the experimental verifications perfectly marked the theoretical and significance optimisation design.
ISSN:1751-8660
1751-8679
1751-8679
DOI:10.1049/iet-epa.2017.0810