Optimal Design of 100-2000 V 4H-SiC Power MOSFETs Using Multi-Objective Particle Swarm Optimization Algorithms

This work employed the particle swarm optimization (PSO) algorithm to assess the trade-off between breakdown voltage (BV) and on-state resistance (<inline-formula> <tex-math notation="LaTeX">\text{R}_{\textit {DS},\textit {on}}{)} </tex-math></inline-formula> in 4H-...

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Vydané v:IEEE electron device letters Ročník 45; číslo 5; s. 786 - 788
Hlavní autori: Luo, Runding, Sun, Botao, Hou, Xinlan, Shi, Wenhua, Zhang, Guoqi, Fan, Jiajie
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.05.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract This work employed the particle swarm optimization (PSO) algorithm to assess the trade-off between breakdown voltage (BV) and on-state resistance (<inline-formula> <tex-math notation="LaTeX">\text{R}_{\textit {DS},\textit {on}}{)} </tex-math></inline-formula> 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 <inline-formula> <tex-math notation="LaTeX">\text{R}_{\textit {DS},\textit {on}} </tex-math></inline-formula> under typical BV ranging from 100 to 2000 V. The <inline-formula> <tex-math notation="LaTeX">\text{R}_{\textit {DS},\textit {on}} </tex-math></inline-formula> 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.
AbstractList This work employed the particle swarm optimization (PSO) algorithm to assess the trade-off between breakdown voltage (BV) and on-state resistance ([Formula Omitted] 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 [Formula Omitted] under typical BV ranging from 100 to 2000 V. The [Formula Omitted] 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.
This work employed the particle swarm optimization (PSO) algorithm to assess the trade-off between breakdown voltage (BV) and on-state resistance (<inline-formula> <tex-math notation="LaTeX">\text{R}_{\textit {DS},\textit {on}}{)} </tex-math></inline-formula> 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 <inline-formula> <tex-math notation="LaTeX">\text{R}_{\textit {DS},\textit {on}} </tex-math></inline-formula> under typical BV ranging from 100 to 2000 V. The <inline-formula> <tex-math notation="LaTeX">\text{R}_{\textit {DS},\textit {on}} </tex-math></inline-formula> 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.
Author Fan, Jiajie
Luo, Runding
Shi, Wenhua
Sun, Botao
Zhang, Guoqi
Hou, Xinlan
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SubjectTerms Algorithms
Design parameters
Doping
Electronic devices
Field effect transistors
JFET
JFETs
Metal oxide semiconductors
Metal oxides
MOSFET
MOSFETs
multi-objective optimization
Multiple objective analysis
Numerical models
Optimization
Particle swarm optimization
Resistance
Semiconductor devices
SiC
Silicon carbide
Thickness
Threshold voltage
Transistors
Title Optimal Design of 100-2000 V 4H-SiC Power MOSFETs Using Multi-Objective Particle Swarm Optimization Algorithms
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