Fe-Ni-Y2O3 nanocomposites with uniform distribution of fine oxide particles in the gamma Fe Ni matrix were successfully fabricated via solution combustion followed by hydrogen reduction. The morphological characterist...Fe-Ni-Y2O3 nanocomposites with uniform distribution of fine oxide particles in the gamma Fe Ni matrix were successfully fabricated via solution combustion followed by hydrogen reduction. The morphological characteristics and phase transformation of the combusted powder and the Fe-Ni-Y2O3 nanocomposites were characterized by XRD, FESEM and TEM.Porous Fe-Ni-Y2O3 nanocomposites with crystallite size below 100 nm were obtained after reduction. The morphology, phases and magnetic property of Fe-Ni-Y2O3 nanocomposites reduced at different temperatures were investigated. The Fe-Ni-Y2O3 nanocomposite reduced at 900 °C has the maximum saturation magnetization and the minimum coercivity values of 167.41 A/(m2·kg)and 3.11 k A/m, respectively.展开更多
软磁复合材料因其突出的高频特性而被广泛用作变压器和电机的铁心材料。为了提高高频磁化下变压器或电机的效率与功率密度,需要提高产品设计阶段铁损的计算精度。该文提出一种基于梯形等效电路与神经网络结合的动态磁滞模型,可用以计算...软磁复合材料因其突出的高频特性而被广泛用作变压器和电机的铁心材料。为了提高高频磁化下变压器或电机的效率与功率密度,需要提高产品设计阶段铁损的计算精度。该文提出一种基于梯形等效电路与神经网络结合的动态磁滞模型,可用以计算高频软磁复合材料铁损。该模型通过非理想电感、恒定电阻和非线性电阻分别计算静态磁滞损耗、涡流损耗和异常损耗;其中,为了提高低磁密下静态磁滞回环的模拟精度,引入能够表征磁化过程的神经网络算法模拟静态磁滞部分;同时,在采用梯形等效电路计算涡流损耗和异常损耗时,考虑趋肤效应对铁损的影响;最后,搭建高频正弦激励下的软磁材料磁特性测试系统,在频率为1 Hz~10 k Hz范围内对软磁复合材料的磁滞回线和铁损进行实验测量,并将铁损计算方法与实测数据进行对比,验证该模型在高频正弦激励下预估损耗的准确性,为变压器和电动机优化设计提供一种模型结构简单、精度较高且工程实用性强的损耗计算方法。展开更多
基金Project(51104007)supported by the National Natural Science Foundation of ChinaProject(2132046)supported by Beijing Natural Science Foundation,China
文摘Fe-Ni-Y2O3 nanocomposites with uniform distribution of fine oxide particles in the gamma Fe Ni matrix were successfully fabricated via solution combustion followed by hydrogen reduction. The morphological characteristics and phase transformation of the combusted powder and the Fe-Ni-Y2O3 nanocomposites were characterized by XRD, FESEM and TEM.Porous Fe-Ni-Y2O3 nanocomposites with crystallite size below 100 nm were obtained after reduction. The morphology, phases and magnetic property of Fe-Ni-Y2O3 nanocomposites reduced at different temperatures were investigated. The Fe-Ni-Y2O3 nanocomposite reduced at 900 °C has the maximum saturation magnetization and the minimum coercivity values of 167.41 A/(m2·kg)and 3.11 k A/m, respectively.
文摘软磁复合材料因其突出的高频特性而被广泛用作变压器和电机的铁心材料。为了提高高频磁化下变压器或电机的效率与功率密度,需要提高产品设计阶段铁损的计算精度。该文提出一种基于梯形等效电路与神经网络结合的动态磁滞模型,可用以计算高频软磁复合材料铁损。该模型通过非理想电感、恒定电阻和非线性电阻分别计算静态磁滞损耗、涡流损耗和异常损耗;其中,为了提高低磁密下静态磁滞回环的模拟精度,引入能够表征磁化过程的神经网络算法模拟静态磁滞部分;同时,在采用梯形等效电路计算涡流损耗和异常损耗时,考虑趋肤效应对铁损的影响;最后,搭建高频正弦激励下的软磁材料磁特性测试系统,在频率为1 Hz~10 k Hz范围内对软磁复合材料的磁滞回线和铁损进行实验测量,并将铁损计算方法与实测数据进行对比,验证该模型在高频正弦激励下预估损耗的准确性,为变压器和电动机优化设计提供一种模型结构简单、精度较高且工程实用性强的损耗计算方法。
