Dominant Model-Parameter Determination for the Analysis of Current Imbalance Across Paralleled Power Transistors

Abstract

In this article, we propose a new sensitivity-based analytical equation, the nn -devices forward propagation of variance (NFPV). Using the proposed NFPV equation, the dominant device model parameters— essential for accurate analysis of energy-loss variation due to the current imbalance across paralleled power transistors from statistical parameter variations—are efficiently determined. The proposed method with the NFPV equation is faster than conventional methods that use Monte Carlo simulation. We conducted experimental validation using the measured current–voltage characteristics of commercially available 100 silicon mosfet s and 300 silicon carbide mosfet s. The results show that the proposed NFPV-based method efficiently finds the dominant device model parameters, which are sufficient and necessary to reproduce the energy-loss variation, regardless of the number of parallel transistors. The results also show that the determined dominant device model parameters are valid under practical situations, such as uneven parasitic inductances and device temperature imbalance among paralleled transistors. The proposed method determines the dominant device model parameters 9.33× faster than the conventional method while maintaining the same accuracy. Additionally, we demonstrate that, compared with the conventional method, an increase in the number of candidate statistical model parameters increases the efficiency of the proposed method.