Multiobjective optimization of design of 4h-sic power mosfets for specific applications

The electrical characteristics of a 4H silicon carbide (4H-SiC) metal–oxide– semiconductor field-effect transistor (MOSFET) have been investigated by using a multiobjective genetic algorithm (MOGA) to overcome the existing tradeoff between main device figures of merit such as the breakdown voltage, drain current, and ON-state resistance. The aim of this work is to achieve an optimized device for a specific application. In particular, without loss of generality, we refer to a dual-implanted MOSFET (DMOSFET) dimensioned for use as a low-power transistor in direct current (DC)–DC converters for solar power optimizers. Typical blocking voltages for these transistors are around 150 V. In this investigation, both analytical and numerical models are used as objective functions in MOGA to determine a set of optimized physical and geometrical device parameters that meet the application constraints while minimizing the ON-state resistance (RON). The optimized DMOSFET exhibits an RON value of a few hundred kΩ × μm2 for different breakdown voltages in the range from 150 V to 800 V