A Model-Based Gate-Driving Strategy with Adjustable Negative Turn-Off Voltage for SiC MOSFETs

Owing to the stringent reliability requirements of silicon carbide (SiC) MOSFETs, conventional gate-driving methods with fixed parameters are no longer sufficient to ensure reliable operation under varying operating conditions. To address this issue, this study proposes an adaptive gate-driving method based on model prediction dealing with operating conditions. First, the influence of operating conditions on crosstalk is comprehensively analyzed, starting with an explanation of the crosstalk mechanism. Then, a two-variable behavioral model is established to estimate the amplitude of the crosstalk voltage under the specified operating condition. Based on this prediction model, a lightweight optimization algorithm is developed to select the negative gate turn-off voltage according to the operating conditions. Finally, a double-pulse test platform is built to validate the proposed dynamic gate-voltage selection strategy. The experimental results show that, compared with the fixed −3 V turn-off voltage scheme, the proposed method selects the optimal turn-off voltage of −2 V under specific operating conditions, which can reduce unnecessary negative gate-voltage stress while maintaining the gate-source voltage within the allowable range. Additionally, the measured turn-off loss of the proposed method is 172.7 μJ, lower than the 222.3 μJ loss of the parallel gate-source capacitance method, indicating a better trade-off between crosstalk suppression and switching loss. The proposed behavioral model requires only 69.5 microseconds to predict positive and negative crosstalk peaks, whereas the analytical model requires 46.6 milliseconds. The low computational burden makes the proposed method suitable for potential real-time implementation on resource-constrained microcontrollers.