磁滞
纳米晶材料
材料科学
涡流
磁滞
热力学
变量(数学)
控制理论(社会学)
凝聚态物理
磁化
数学
物理
计算机科学
磁场
数学分析
工程类
纳米技术
电气工程
量子力学
控制(管理)
人工智能
作者
Xueping Xu,Zhenming Zhao,Jianyi Ren,Danyue Ma
标识
DOI:10.1088/1361-6463/ad0fbc
摘要
Abstract The magnetic characteristics of Fe-based nanocrystalline alloys can be influenced by temperature. The conventional dynamic Jiles–Atherton (J-A) hysteresis model does not take into consideration the impact that temperature has on magnetic characteristics. A novel variable-temperature dynamic J-A hysteresis model is proposed in this paper to effectively address the issue. Firstly, the hysteresis loops of Fe-based nanocrystalline are measured at −50 °C–130 °C and DC state. The five parameters of the J-A hysteresis model are identified at various temperatures using the particle swarm optimization algorithm, and five parameters are fitted as functions of temperature. Subsequently, the five parameters as functions of temperature are introduced into the conventional dynamic J-A hysteresis model to construct a novel variable-temperature dynamic J-A hysteresis model, which can not only reflect the impact of temperature but also accurately calculate the losses. Finally, hysteresis loops and losses of Fe-based nanocrystalline alloy are simulated and calculated at different temperatures and frequencies by the variable-temperature dynamic J-A hysteresis model. Meanwhile, this paper also investigates the trends and percentages of hysteresis loss, excess loss as well as eddy current loss with frequency and temperature. Compared to the results of measured data, the maximum average error of the variable-temperature dynamic J-A hysteresis model is 5.83%.
科研通智能强力驱动
Strongly Powered by AbleSci AI