Optimization Design of Permanent Magnet Synchronous Motor Based on Multi-Objective Artificial Hummingbird Algorithm

The interior permanent magnet synchronous motor (IPMSM) is known for its high output torque, strong overload capacity, and high power density, making it a popular choice in the electric vehicle industry. This paper proposes an improved multi-objective artificial hummingbird algorithm that combines c...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Actuators Jg. 13; H. 7; S. 243
Hauptverfasser:	Zhang, Shaoru, Yan, Hui, Yang, Likun, Zhao, Hua, Du, Xiuju, Zhang, Jielu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.07.2024
Schlagworte:	Adaptive algorithms Back electromotive force Deep learning Design optimization Design techniques Efficiency Electric vehicles Electromotive forces Finite element analysis Finite element method Foraging behavior Genetic algorithms IPMSM MOAHA multi-objective optimization Multiple objective analysis Neural networks Objectives Optimization algorithms Parameter identification Permanent magnets Response surface methodology Ripples Sensitivity analysis Synchronous motors Taguchi methods Torque
ISSN:	2076-0825, 2076-0825
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!