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氮化镓高电子迁移率晶体管功率器件动态功率损耗的解析模型

An Analytical Model of Dynamic Power Losses in eGaN HEMT Power Devices.

作者信息

Lei Jianming, Liu Yangyi, Yang Zhanmin, Chen Yalin, Chen Dunjun, Xu Liang, Yu Jing

机构信息

The School of Electrical Engineering, Nanjing Vocational University of Industry Technology, Nanjing 210023, China.

The Key Laboratory of Advanced Photonic and Electronic Materials, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China.

出版信息

Micromachines (Basel). 2023 Aug 18;14(8):1633. doi: 10.3390/mi14081633.

DOI:10.3390/mi14081633
PMID:37630169
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10456439/
Abstract

In this work, we present an analytical model of dynamic power losses for enhancement-mode AlGaN/GaN high-electron-mobility transistor power devices (eGaN HEMTs). To build this new model, the dynamic on-resistance () is first accurately extracted via our extraction circuit based on a double-diode isolation (DDI) method using a high operating frequency of up to 1 MHz and a large drain voltage of up to 600 V; thus, the unique problem of an increase in the dynamic is presented. Then, the impact of the current operation mode on the on/off transition time is evaluated via a dual-pulse-current-mode test (DPCT), including a discontinuous conduction mode (DCM) and a continuous conduction mode (CCM); thus, the transition time is revised for different current modes. Afterward, the discrepancy between the drain current and the real channel current is qualitative investigated using an external shunt capacitance (ESC) method; thus, the losses due to device parasitic capacitance are also taken into account. After these improvements, the dynamic model will be more compatible for eGaN HEMTs. Finally, the dynamic power losses calculated via this model are found to be in good agreement with the experimental results. Based on this model, we propose a superior solution with a quasi-resonant mode (QRM) to achieve lossless switching and accelerated switching speeds.

摘要

在这项工作中,我们提出了一种增强型氮化铝镓/氮化镓高电子迁移率晶体管功率器件(eGaN HEMT)动态功率损耗的分析模型。为建立这个新模型,首先通过我们基于双二极管隔离(DDI)方法的提取电路,在高达1 MHz的高工作频率和高达600 V的大漏极电压下准确提取动态导通电阻();由此,呈现了动态导通电阻增加这一独特问题。然后,通过双脉冲电流模式测试(DPCT)评估电流工作模式对通断转换时间的影响,包括不连续导通模式(DCM)和连续导通模式(CCM);从而针对不同电流模式修正转换时间。之后,使用外部并联电容(ESC)方法定性研究漏极电流与实际沟道电流之间的差异;由此,也考虑了器件寄生电容引起的损耗。经过这些改进后,该动态模型将与eGaN HEMT更兼容。最后,发现通过该模型计算的动态功率损耗与实验结果吻合良好。基于此模型,我们提出了一种采用准谐振模式(QRM)的卓越解决方案,以实现无损开关和加快开关速度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/c59b221c8ed2/micromachines-14-01633-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/ca4db66b9e11/micromachines-14-01633-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/82d8fbb7f2df/micromachines-14-01633-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/903f59329a04/micromachines-14-01633-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/64e8beb4cc37/micromachines-14-01633-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/31ca781e1e7c/micromachines-14-01633-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/1b6094f765dc/micromachines-14-01633-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/bc7b54cd681b/micromachines-14-01633-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/15dd8fc74896/micromachines-14-01633-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/c59b221c8ed2/micromachines-14-01633-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/517e764df03e/micromachines-14-01633-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/fcdb5dd4e49f/micromachines-14-01633-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/ca4db66b9e11/micromachines-14-01633-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/82d8fbb7f2df/micromachines-14-01633-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/903f59329a04/micromachines-14-01633-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/64e8beb4cc37/micromachines-14-01633-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/31ca781e1e7c/micromachines-14-01633-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/1b6094f765dc/micromachines-14-01633-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/bc7b54cd681b/micromachines-14-01633-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/15dd8fc74896/micromachines-14-01633-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f7/10456439/c59b221c8ed2/micromachines-14-01633-g011.jpg

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