An Improved Drain-source Capacitance Characterization Method for SiC MOSFET Switching Performance Prediction

Accurate nonlinear parasitic capacitance characterization of silicon carbide (SiC) metal-oxide-semiconductor field-effect transistor (MOSFETs) is essential for device behavior modeling, circuit switching loss optimization and power electronic equipment design. This paper presents an improved characterization method of drain-source capacitance Cds for SiC MOSFET, which combines parasitic capacitance extraction in dynamic switching process and static segmented capacitance characterization. Firstly, an extraction method of parasitic capacitance during dynamic switching transient based on miller plateau is described and it can reflect the real value of Cds in actual electrical conditions, which is essential to the precise modeling and predicting of SiC MOSFET switching performance. Secondly, a segmented characterization method of Cds is proposed to deal with the challenging obstacles on the modeling of nonlinear capacitance outside miller plateau area during switching process. And then, an accurate capacitance modeling method is set up based on these two methods. Finally, the proposed method is verified by establishing a Spice model of SiC MOSFET, and a double pulse test (DPT) experimental platform is built to compare with the simulation results. The comparison results show that the simulation waveform of this proposed method fits better with the experiment one than the previous method, which indicates the high performance of the proposed method.