磁芯的动态特性对模拟快脉冲直线变压器驱动源(fast linear transformer driver,FLTD)在异常工况下的输出波形有很大影响,为更贴切地模拟FLTD放电过程中磁芯的磁化过程,建立了耦合Jiles-Atherton磁滞模型的四级串联FLTD电路模型,根据实...磁芯的动态特性对模拟快脉冲直线变压器驱动源(fast linear transformer driver,FLTD)在异常工况下的输出波形有很大影响,为更贴切地模拟FLTD放电过程中磁芯的磁化过程,建立了耦合Jiles-Atherton磁滞模型的四级串联FLTD电路模型,根据实测磁滞回线拟合了磁滞模型参数,将FLTD支路自放电的仿真与实验波形对比,验证了模型的有效性。模型所包含的磁滞回线特征很好地改善了仿真中自放电电压波形在第一个峰值之后的变化趋势,同时给出了放电过程中磁芯的励磁状态变化过程,为预测和分析FLTD故障提供了一种更准确的数值模型。展开更多
This paper describes a generalization methodology for nonlinear magnetic field calculation applied on two-dimensional (2-D) finite Volume geometry by incorporating a Jiles-Atherton scalar hysteresis model. The scheme ...This paper describes a generalization methodology for nonlinear magnetic field calculation applied on two-dimensional (2-D) finite Volume geometry by incorporating a Jiles-Atherton scalar hysteresis model. The scheme is based upon the definition of modified governing equation derived from Maxwell’s equations considered the magnetization M. This paper shows how to extract optimal parameters for the Jiles-Atherton model of hysteresis by a real coded genetic algorithm approach. The parameters identification is performed by minimizing the mean squared error between experimental and simulated magnetic field curves. The calculated results are validated by experiences performed in an SST’s frame.展开更多
文摘磁芯的动态特性对模拟快脉冲直线变压器驱动源(fast linear transformer driver,FLTD)在异常工况下的输出波形有很大影响,为更贴切地模拟FLTD放电过程中磁芯的磁化过程,建立了耦合Jiles-Atherton磁滞模型的四级串联FLTD电路模型,根据实测磁滞回线拟合了磁滞模型参数,将FLTD支路自放电的仿真与实验波形对比,验证了模型的有效性。模型所包含的磁滞回线特征很好地改善了仿真中自放电电压波形在第一个峰值之后的变化趋势,同时给出了放电过程中磁芯的励磁状态变化过程,为预测和分析FLTD故障提供了一种更准确的数值模型。
文摘This paper describes a generalization methodology for nonlinear magnetic field calculation applied on two-dimensional (2-D) finite Volume geometry by incorporating a Jiles-Atherton scalar hysteresis model. The scheme is based upon the definition of modified governing equation derived from Maxwell’s equations considered the magnetization M. This paper shows how to extract optimal parameters for the Jiles-Atherton model of hysteresis by a real coded genetic algorithm approach. The parameters identification is performed by minimizing the mean squared error between experimental and simulated magnetic field curves. The calculated results are validated by experiences performed in an SST’s frame.