A Novel Crosstalk Suppression Method for SiC MOSFET Discrete Device With Crosstalk Type Determination

IF 7.2 1区 工程技术 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Industrial Electronics Pub Date : 2024-11-13 DOI:10.1109/TIE.2024.3488284
Han Peng;Qing Xin;Qiaozhi Yue;Yong Kang
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Abstract

The fast switching speed of silicon carbide (SiC) metal oxide semiconductor field effect transistor (MOSFET) leads to serious crosstalk problems in half bridge structures. State-of-the-art crosstalk suppression methods have the following limitations: crosstalk caused by common source inductance is ignored; crosstalk is not correctly reflected by external gate source voltage sampling. To overcome above defects, this letter proposes a novel crosstalk suppression method to suppress the crosstalk caused by miller capacitance and common source inductance through automatic switching of loop impedance and drive voltage. In addition, the proposed method can correctly determine the crosstalk type based on the internal gate source voltage detection. Experimental results show that the crosstalk voltage under the proposed method can be reduced by 21.36% and 49.15% during turn-on transient and 27.78% and 76.56% during turn-off transient at 800 V/60 A compared with no crosstalk suppression and with only active miller clamp.
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带串音类型确定功能的 SiC MOSFET 分立器件串音抑制新方法
碳化硅(SiC)金属氧化物半导体场效应晶体管(MOSFET)的快速开关速度导致了半桥结构中严重的串扰问题。现有串扰抑制方法存在以下局限性:忽略共源电感引起的串扰;外部栅极源电压采样不能正确反映串扰。为了克服上述缺陷,本文提出了一种新的串扰抑制方法,通过回路阻抗和驱动电压的自动切换来抑制米勒电容和共源电感引起的串扰。此外,该方法还能基于内部栅极源电压检测正确判断串扰类型。实验结果表明,在800 V/60 A时,与不加串扰抑制和只加有源米勒箝位相比,采用该方法的串扰电压在导通时分别降低21.36%和49.15%,在关断时分别降低27.78%和76.56%。
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来源期刊
IEEE Transactions on Industrial Electronics
IEEE Transactions on Industrial Electronics 工程技术-工程:电子与电气
CiteScore
16.80
自引率
9.10%
发文量
1396
审稿时长
6.3 months
期刊介绍: Journal Name: IEEE Transactions on Industrial Electronics Publication Frequency: Monthly Scope: The scope of IEEE Transactions on Industrial Electronics encompasses the following areas: Applications of electronics, controls, and communications in industrial and manufacturing systems and processes. Power electronics and drive control techniques. System control and signal processing. Fault detection and diagnosis. Power systems. Instrumentation, measurement, and testing. Modeling and simulation. Motion control. Robotics. Sensors and actuators. Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems. Factory automation. Communication and computer networks.
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