
1. 中国矿业大学机械与电气工程学院,北京,100083
2. 中国电力科学研究院有限公司,北京,100192
Published:2025
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WANG Ning, ZHANG Pengning, MIAO Dengji, et al. 变温条件下纳米晶材料的Steinmetz损耗模型[J]. 2025, (11): 5673-5682.
WANG Ning, ZHANG Pengning, MIAO Dengji, et al. 变温条件下纳米晶材料的Steinmetz损耗模型[J]. 2025, (11): 5673-5682. DOI: 10.13336/j.1003-6520.hve.20250295.
为提高变温条件下纳米晶材质电磁设备的建模和设计精度,该文提出一种考虑温度影响的纳米晶材料Steinmetz损耗预测模型。首先,搭建了由恒温箱和BROCKHAUS软磁测量仪组成的变温磁特性测试系统,对纳米晶材料在1~20 kHz频率、25~125 ℃温度下的磁特性进行测量。测量结果表明:纳米晶材料饱和磁通密度与温度呈线性负相关;不同频率段饱和磁通密度与温度之间的线性拟合方程具有相同的斜率−0.001,说明频率与温度不存在耦合关系;饱和磁通密度点对应的损耗与温度存在非线性关系,且损耗随温度上升而降低。其次,将经典Steinmetz公式中的磁通密度项由常量修正为随温度线性变化的变量,并推导出一种二次温度修正项来表征损耗与温度之间的非线性关系,建立了应用于纳米晶材料饱和阶段的Steinmetz损耗预测模型。最后,采用依赖域反射优化算法对改进Steinmetz损耗预测模型和经典Steinmetz公式的参数进行拟合,本文所提损耗预测模型平均预测误差为0.62%,最大预测误差为2.66%,经典Steinmetz损耗模型平均预测误差为5.26%,最大误差为14.85%,验证了所提模型在变温条件下高精度的预测能力,为电磁设备的饱和控制和设计优化提供了理论依据和数据支撑。
To improve the modeling and design accuracy of electromagnetic devices made from nanocrystalline materials under varying temperature conditions
this paper proposes a Steinmetz loss prediction model for nanocrystalline materials under varying temperature conditions. Initially
a temperature-variable magnetic property testing system
consisting of a thermostatic chamber and a BROCKHAUS soft magnetic measuring instrument
was set up to measure the magnetic properties of nanocrystalline materials in a frequency range from 1 kHz to 20 kHz and temperatures from 25 ℃ to 125 ℃. The results indicate that the saturation magnetic flux density of nanocrystalline materials is linearly negatively correlated with temperature; the linear fitting equations between saturation magnetic flux density and temperature across different frequency ranges have the same slope of −0.001
indicating no coupling relationship between frequency and temperature. The loss corresponding to saturation magnetic flux density points has a nonlinear relationship with temperature
decreasing as temperature increases. Furthermore
the magnetic flux density term in the classical Steinmetz formula was modified from a constant to a variable linearly changing with temperature
and a quadratic temperature correction term was derived to represent the nonlinear relationship between loss and temperature
and a Steinmetz loss prediction model applicable to the saturation stage of nanocrystalline materials was established. Finally
the parameters of the improved Steinmetz loss prediction model and the classical Steinmetz formula were fitted using the trust-region-reflective optimization algorithm. The proposed loss prediction model can achieve an average prediction error of 0.62% and a maximum prediction error of 2.66%
compared to the classical Steinmetz loss model's average prediction error of 5.26% and maximum error of 14.85%. The results validate the high-precision prediction capability of the proposed model under varying temperature conditions
providing a theoretical basis and data support for saturation control and design optimization of electromagnetic equipment.
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