基于PSO-Powell混合算法的软磁复合材料二维矢量磁滞特性模拟

doi:10.19595/j.cnki.1000-6753.tces.200377

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Abstract An improved vector hysteresis model was proposed because the classical vector Preisach model can only simulate the isotropic hysteresis characteristics of materials. The improved model was utilized to regulate the curve shape of magnetic field strength by introducing the correlation parameters of its amplitude and direction angle. Accordingly, the anisotropy characteristics of soft magnetic composite (SMC) materials can be considered. The experiment for measuring the two- dimensional rotational magnetic properties of the SMC material was carried out by the vector magnetic property platform. The measured limiting hysteresis loops were required to construct the scalar and vector Everett functions. Moreover, a hybrid optimization strategy based on particle swarm optimization (PSO) and Powell technique was proposed to identify the parameters of the vector Preisach hysteresis model efficiently, which significantly improved the local optimization ability of the PSO algorithm. The simulation results are consistent with the measurement results, which verifies the effectiveness of the improved vector model and the parameter identification method proposed in this paper.

Key words： Soft magnetic composite (SMC) material vector Preisach hysteresis model rotational magnetization anisotropy parameter identification

Received: 16 April 2020

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TM153

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	Articles by authors
	Zhao Xiaojun
	Xu Huawei
	Liu Xiaona
	Li Yongjian
	Du Zhenbin

Cite this article:

Zhao Xiaojun,Xu Huawei,Liu Xiaona等. Two-Dimensional Vector Hysteresis Simulation of Soft Magnetic Composite Materials Based on the Hybrid Algorithm of PSO-Powell[J]. Transactions of China Electrotechnical Society, 2021, 36(14): 2893-2903.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.200377 OR https://dgjsxb.ces-transaction.com/EN/Y2021/V36/I14/2893

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