曾伊浓, 易映萍, 董晓帅. SiC MOSFET功率器件特性参数的提取与拟合[J]. 高电压技术, 2021, 47(1): 138-149. DOI: 10.13336/j.1003-6520.hve.20200310007
引用本文: 曾伊浓, 易映萍, 董晓帅. SiC MOSFET功率器件特性参数的提取与拟合[J]. 高电压技术, 2021, 47(1): 138-149. DOI: 10.13336/j.1003-6520.hve.20200310007
ZENG Yinong, YI Yingping, DONG Xiaoshuai. Extraction and Fitting of Characteristic Parameters of SiC MOSFET Power Devices[J]. High Voltage Engineering, 2021, 47(1): 138-149. DOI: 10.13336/j.1003-6520.hve.20200310007
Citation: ZENG Yinong, YI Yingping, DONG Xiaoshuai. Extraction and Fitting of Characteristic Parameters of SiC MOSFET Power Devices[J]. High Voltage Engineering, 2021, 47(1): 138-149. DOI: 10.13336/j.1003-6520.hve.20200310007

SiC MOSFET功率器件特性参数的提取与拟合

Extraction and Fitting of Characteristic Parameters of SiC MOSFET Power Devices

  • 摘要: 为了对碳化硅(SiC) MOSFET功率器件的特性参数进行全面的研究,提出了一种碳化硅(SiC) MOSFET变温度参数模型,该模型考虑了功率器件中封装引脚寄生电感、内部寄生电容、体二极管等特性参数,并根据器件的开关过程中的不同阶段,将功率器件中的导电沟道等效为不同电路模型。为获取该模型中的涉及的特性参数,搭建了基于Agilent B1505A功率半导体分析仪和矢量网络分析仪(VNA)的测试平台对SiC MOSFET功率器件的静态特性参数进行了全面测量,然后使用基于贝叶斯正则化LM算法的改进BP人工神经网络对所测的数据进行非线性拟合。结果表明,相较于传统拟合方法,该方法具有更高的精确度与泛化能力,为SiC MOSFET功率器件建模与参数分析提供了重要依据。

     

    Abstract: In order to study the parasitic parameters of SiC MOSFET power devices comprehensively, a variable temperature parameter model of silicon carbide MOSFET is proposed. The parasitic inductance, internal parasitic capacitance, parasitic diode and other parasitic parameters are considered in this model. According to the different stages of the switching process of the device, the conductive channel of power device is equivalent to different circuit models. In order to obtain the required parameters in the proposed model, a test platform based on Agilent B1505A power semiconductor analyzer and vector network analyzer (VNA) was built to measure the static characteristic parameters of SiC MOSFET power devices comprehensively. Then an improved BP artificial neural network based on Bayesian regularized LM algorithm is used to fit the measured nonlinear data. The results of fitting show that this method has higher accuracy and generalization ability than the traditional fitting methods, which provides an important basis for the modeling and parameter analysis of SiC MOSFET power devices.

     

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