Optimal Design of 100–2000 V 4H–SiC Power MOSFETs using Multi-objective Particle Swarm Optimization Algorithms

Abstract

This work employed the particle swarm optimization (PSO) algorithm to assess the trade-off between breakdown voltage (BV) and on-state resistance (R DS,on ) in 4H–SiC metal oxide semiconductor field effect transistors (MOSFET) for power devices. In this work, the numerical model obtained after analyzing the resistance composition is utilized as the objective function in PSO to determine characteristic parameters in double-diffused metal oxide semiconductor field effect transistors (DMOSFET). These equations are input for the PSO algorithm. The derived characteristic parameters include the drift region doping concentration and thickness, cell size, channel length, JFET region length, JFET region thickness, and doping concentration. To adhere to common application constraints, this work optimizes these characteristic parameters to minimize the R DS,on under typical BV ranging from 100 to 2000 V. The R DS,on for some typical applications was extracted and validated through TCAD simulations to ensure algorithm accuracy. The reported results confirm that PSO yields superior outcomes and may be considered when designing devices. This work offers helpful insights into the design of characteristic parameters for 4H–SiC power DMOSFET devices and evaluates the feasibility of using PSO to optimize the characteristic parameters of power devices.