基于内置温度传感器的碳化硅功率模块结温在线提取方法

doi:10.19595/j.cnki.1000-6753.tces.201442

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摘要

碳化硅（SiC）MOSFET具有耐压高、开关速度快、导通损耗低等优点,将越来越广泛地应用于高效、高功率密度场合。在这些应用场合中,SiC MOSFET面临着严峻的可靠性考验,而结温的在线准确提取是实现器件寿命预测和可靠性评估的重要基础。该文提出一种基于功率模块内置负温度系数（NTC）温度传感器的器件结温在线提取方法。首先建立考虑多芯片热耦合效应的内置温度传感器至功率芯片的热网络模型,并建立SiC MOSFET的损耗快速计算方法;通过有限元仿真提取热网络模型的阻抗参数,并验证该热网络参数在不同边界条件下的稳定性。仿真和实验结果表明,所提出的结温在线估计方法能够准确地获得器件的动态结温,且热网络模型参数不受环境温度、散热条件等边界条件变化的影响,适用于实际任务剖面下的结温监测与寿命预测。

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	刘平
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	黄守道

关键词 ：负温度系数温度传感器, SiC MOSFET, 热网络模型, 芯片温度

Abstract：

Silicon carbide (SiC) MOSFET has the advantages of high switching speed and low loss, which will be more and more widely used in high efficiency and high power density applications. In these applications, SiC MOSFETs are facing severe reliability tests, and the online accurate extraction of junction temperature is essential for lifetime prediction and health assessment. This paper proposed an online junction temperature extraction method for power module based on built-in negative temperature coefficient (NTC) temperature sensor. First, the thermal network model between the built-in NTC sensor and the power chips considering the thermal coupling effect was established, and a fast loss calculation method for SiC MOSFET was proposed. Then, the thermal network parameters were extracted by finite element simulation, and the stability of thermal network parameters under different boundary conditions was verified. Simulation and experimental results show that the proposed method can accurately obtain the dynamic junction temperature, and the thermal network model parameters are not affected by changes in boundary conditions such as ambient temperature and heat dissipation conditions. It is suitable for junction temperature monitoring and lifetime prediction under real mission profiles.

Key words： Negative temperature coefficient temperature sensor SiC MOSFET thermal network model chip temperature

收稿日期: 2020-10-30

PACS:

TM46

基金资助:

国家自然科学基金项目（51977065）和天水大型电气传动系统与装备技术国家重点实验室开放资金项目（SKLLDJ022019003）资助

通讯作者: 通信作者刘平, 男,1983年生,博士,副教授,研究方向为电动车辆高性能电力电子变换与电机驱动控制。E-mail: pingliu@hnu.edu.cn

作者简介: 李海鹏,男,1995年生,硕士研究生,研究方向为宽禁带半导体器件驱动与可靠性。E-mail:2099325157@qq.com

引用本文:

刘平, 李海鹏, 苗轶如, 陈常乐, 黄守道. 基于内置温度传感器的碳化硅功率模块结温在线提取方法[J]. 电工技术学报, 2021, 36(12): 2522-2534. Liu Ping, Li Haipeng, Miao Yiru, Chen Changle, Huang Shoudao. Online Junction Temperature Extraction for SiC Module Based on Built-in Temperature Sensor. Transactions of China Electrotechnical Society, 2021, 36(12): 2522-2534.

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