李凯伟,何怡刚,李 兵,朋张胜.IGBT功率模块热网络模型建立及其 参数辨识方法综述和展望[J].电子测量与仪器学报,2020,34(1):51-60
IGBT功率模块热网络模型建立及其 参数辨识方法综述和展望
Review and prospect of IGBT power module thermal network modelestablishment and parameter extraction method
  
DOI:
中文关键词:  IGBT模块  结温提取  热网络模型  参数辨识
英文关键词:IGBT modules  junction temperature extraction  thermal network model  parameter identification
基金项目:国家自然科学基金(51977153,51577046)、国家自然科学基金重点项目(51637004)、国家重点研发计划“重大科学仪器设备开发”项目(2016YFF0102200)、装备预先研究重点项目(41402040301)资助
作者单位
李凯伟 1.合肥工业大学 电气与自动化工程学院 
何怡刚 1.合肥工业大学 电气与自动化工程学院 
李 兵 1.合肥工业大学 电气与自动化工程学院 
朋张胜 1.合肥工业大学 电气与自动化工程学院 
AuthorInstitution
Li Kaiwei 1.School of Electrical Engineering and Automation, Hefei University of Technology 
He Yigang 1.School of Electrical Engineering and Automation, Hefei University of Technology 
Li Bing 1.School of Electrical Engineering and Automation, Hefei University of Technology 
Peng Zhangsheng 1.School of Electrical Engineering and Automation, Hefei University of Technology 
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中文摘要:
      绝缘栅双极型晶体管(IGBT)作为功率变流器的核心器件,其可靠性受到广泛重视。而结温过高或者温度波动过高是导致功率器件失效的主要因素,故实时精确地监测IGBT模块结温对于提高其可靠性具有重要意义。通过建立热网络模型,然后对其电路进行仿真可获取结温,该方法因简单易行且可实现对结温的在线监测从而得到广泛应用。对现有的热网络模型进行了总结和归纳,并根据模型结构将其分为一维、二维和三维三类。然后,对近年来热网络模型的参数辨识方法的研究情况进行探讨,并对各个方法进行了比较和评价。在此基础上,对未来新的热网络模型和模型参数辨识方法的研究方向进行了展望。
英文摘要:
      As the core component of power converter, the reliability of insulated gate bipolar transistor (IGBT) is widely concerned. High junction temperature or high temperature fluctuation are the main factors leading to the failure of power devices. Therefore, accurate monitoring of IGBT module junction temperature in real time is of great significance to improve its reliability. The junction temperature is obtained by building a thermal network model and simulating its circuit. This method is widely used because of its simplicity and feasibility and the realization of on line monitoring of junction temperature. In this paper, the existing thermal network models are summarized. According to the model structure, they are divided into three categories: one dimensional, two dimensional and three dimensional. Then, the research situation of parameter identification methods for thermal network model in recent years is discussed, and each method is compared and evaluated. On this basis, the future research directions of new thermal network models and model parameter identification methods are prospected.
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