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...

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Vydané v:	Actuators Ročník 13; číslo 7; s. 243
Hlavní autori:	Zhang, Shaoru, Yan, Hui, Yang, Likun, Zhao, Hua, Du, Xiuju, Zhang, Jielu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.07.2024
Predmet:	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
On-line prístup:	Získať plný text
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