为了实现对IGBT期间在全生命周期内的健康状态进行有效评估，基于半导体物理理论，研究了IGBT芯片疲劳失效机理，分析了IGBT栅极界面电荷密度对阈值电压的影响。以阈值电压作为IGBT的失效特征量，在研究阈值电压随疲劳失效时间变化规律的基础上，建立IGBT芯片疲劳失效失效模型。搭建了IGBT阈值电压测试测试平台，通过IGBT老化实验验证本文所提出的模型可以较为准确地表征和估算IGBT中的芯片老化程度，验证了失效模型的正确性和合理性。
In order to effectively evaluate the health status of IGBT during its whole life cycle, the fatigue failure mechanism of IGBT chip was studied based on the theory of semiconductor physics, and the effect of charge density at gate interface on threshold voltage was analyzed. Taking the threshold voltage as the failure characteristic quantity of IGBT, the fatigue failure model of IGBT chip was established on the basis of studying the change rule of threshold voltage with fatigue failure time. An IGBT threshold voltage test platform was built, and IGBT aging experiments were performed to verify that the model proposed in this paper can accurately characterize and estimate the aging degree of IGBT chips, and the correctness and rationality of the failure model were verified.
[1] 魏伟伟, 张杨, 徐国卿. IGBT模块栅氧老化机理分析与表征方法研究[J]. 电源学报, 2021, 19(6):171-178. Wei W W, Zhang Y, Xu G Q. Research on mechanism analysis and characterization method for gate oxygen degradation of IGBT module[J]. Journal of Power Supply, 2021, 19(6):171-178. (in Chinese)
[2] 谷明月, 刘金璐. 大功率IGBT模块结温提取研究[J]. 电源学报, 2020, 18(6):192-198. Gu M Y, Liu J L. Study on junction temperature extraction of high-power IGBT module[J]. Journal of Power Supply, 2020, 18(6):192-198. (in Chinese)
[3] 张军, 张犁, 成瑜. IGBT模块寿命评估研究综述[J]. 电工技术学报, 2021, 36(12):2560-2575. Zhang J, Zhang L, Cheng Y. A review of IGBT module life assessment[J]. Transactions of China Electrotechnical Society, 2021, 36(12):2560-2575. (in Chinese)
[4] 王新春, 李锦涛. 基于MEA-BP算法的IGBT的寿命预测[J]. 电工技术, 2021, 18(41):116-119. Wang X C, Li J T. Life Prediction of IGBT based on MEA-BP algorithm[J]. Transactions of China Electrotechnical Society, 2021, 18(41):116-119. (in Chinese)
[5] 黄柯勋, 吴松荣, 向碧楠, 等. 基于改进小波神经网络的IGBT时间序列预测算法研究[J]. 机车电传动, 2021, 6(5):161-166. Huang K X, Wu R S, Xiang B N, et al. Research on IGBT time series prediction algorithm based on improved wavelet neural network[J]. Electric Drive for Locomotives, 2021, 6(5):161-166. (in Chinese)
[6] 赖伟, 陈民铀, 冉立, 等. 老化实验条件下的IGBT寿命预测模型[J]. 电工技术学报, 2016, 31(24):1-8. Lai W, Chen M Y, Rang L, et al. IGBT Lifetime model based on aging experiment[J]. Transactions of China Electrotechnical Society, 2016, 31(24):1-8. (in Chinese)
[7] 曾东, 孙林, 周雒维, 等. 基于加速老化试验IGBT性能退化特征参量的可靠性评估[J]. 电工电能新技术, 2019, 38(7):20-28. Zeng D, Sun L, Zhou L W, et al. Reliability evaluation of IGBT performance degradation characteristic parameters based on accelerated aging test[J]. Advanced Technology of Electrical Engineering and Energy, 2019, 38(7):20-28. (in Chinese)
[8] 陈民铀, 陈一高, 高兵, 等. 考虑老化进程对热参数影响的IGBT模块寿命评估[J]. 中国电机工程学报, 2017, 37(18):1-10. Chen M Y, Chen Y G, Gao B, et al. Life evaluation of IGBT module considering the effect of aging process on thermal parameters[J]. Proceedings of the CSEE, 2017, 37(18):1-10. (in Chinese)
[9] 王传坤, 何怡刚, 王晨苑, 等. 计及疲劳损伤的多时间尺度风电变流器IGBT可靠性评估[J]. 电力自动化设备, 2021, 41(3):173-178. Wang C K, He Y G, Wang C Y, et al. Multi-time scale reliability evaluation of wind power converter IGBT considering fatigue damage[J]. Electric Power Automation Equipment, 2021, 41(3):173-178. (in Chinese)
[10] 李善鹏. IGBT模块寿命分析[J]. 科学与信息化, 2019(23):1-2. Li S P. Life analysis of IGBT module[J]. Science and Information Technology, 2019(23):1-2. (in Chinese)
[11] 王宇琦. IGBT疲劳老化失效剩余使用寿命预测的研究[D]. 西安:西安电子科技大学, 2017.
[12] 白梁军, 黄萌, 饶臻, 等. 基于GARCH模型的IGBT寿命预测[J]. 中国电机工程学报, 2020, 40(18):5787-5796. Bai L J, Huang M, Rao Z, et al. Life prediction of IGBT based on GARCH model[J]. Proceedings of the CSEE, 2020, 40(18):5787-5796. (in Chinese)
[13] 高兵. 基于温度梯度及统计特性的IGBT模块失效评估方法研究[D]. 重庆:重庆大学, 2016.
[14] 边少聪, 王宇. 基于PSO-BP神经网络模型的IGBT老化预测[J]. 浙江电力, 2019, 38(11):58-64. Bian S C, Wang Y. Aging prediction of IGBT based on PSO-BP neural network model[J]. Zhejiang Electric Power, 2019, 38(11):58-64. (in Chinese)
