Data driven solder layer state evaluation of IGBT module chip for converter valve

doi:10.3969/j.issn.1000-1565.2025.01.002

Abstract

Abstract: Insulated gate bipolar transistor(IGBT)modules for converter valves are widely used in fields such as wind power transmission and grid interconnection. IGBT modules for converter valves have been widely used in wind power transmission and grid interconnection. As the operating time increases, the IGBT chip solder layer is prone to thermal fatigue damage, leading to a decrease in module reliability. Therefore, it is particularly critical to evaluate the state of the IGBT module chip solder layer. To this end, this paper proposes a data-driven method for evaluating the state of the IGBT module chip solder layer for converter valves. Firstly, the fatigue mechanism of the solder layer is analyzed, and evaluation parameters that can reflect the fatigue state of the chip solder layer are selected based on their ability to represent data and the ease of acquisition. Secondly, an electro-thermal coupling model of the IGBT module- DOI:10.3969/j.issn.1000-1565.2025.01.002基于数据驱动的换流阀用IGBT模块芯片焊料层状态评估黄雄峰¹,段熙尧¹,黄明¹,陈忠²,祝琳²,张宇娇¹(1.合肥工业大学电气与自动化工程学院,功率半导体封装与可靠性安徽省重点实验室,安徽合肥 230009;2.国网安徽省电力有限公司电力科学研究院,安徽合肥 230601)摘要:换流阀用绝缘栅双极型晶体管(IGBT)模块在风电输送与电网互联等领域得到广泛应用,随着运行时间的增长,IGBT芯片焊料层易发生热疲劳损伤,导致模块可靠性降低,因此实现IGBT模块芯片焊料层状态评估尤为关键.为此,提出一种基于数据驱动的换流阀用IGBT模块芯片焊料层状态评估方法.首先,分析焊料层的疲劳机理,并从数据的表征能力和获取难易程度出发,选取能够反映芯片焊料层疲劳状态的评估参数;其次,建立不同焊料层疲劳损伤状态的IGBT模块电热耦合模型,并通过有限元计算获得“疲劳状态-评估参数”数据;最后,考虑芯片焊料层疲劳状态与评估参数之间的非线性、相互交叉等问题,选取多种算法共同实现由评估参数到芯片焊料层的疲劳状态的映射,并对评估参数发展趋势进行预测.结果表明本评估方法准确性、实时性均满足工程需要,可为IGBT模块运维提供可靠依据.关键词:芯片焊料层;状态评估;数据驱动;评估参数;电热耦合模型中图分类号:TP181 文献标志码:A 文章编号:1000-1565(2025)01-0010-10Data driven solder layer state evaluation of IGBT module chip for converter valveHUANG Xiongfeng¹, DUAN Xiyao¹, HUANG Ming¹, CHEN Zhong², ZHU Lin², ZHANG Yujiao¹(1.Anhui Province Key Laboratory of Semiconductor Packaging and Reliability, School of Electrical and Automation Engineering, Hefei University of Technology,Hefei 230009,China;2.Electric Power Research Institute,State Grid Anhui Electric Power Co., Ltd., Hefei 230601,China)Abstract: Insulated gate bipolar transistor(IGBT)modules for converter valves are widely used in fields such as wind power transmission and grid interconnection. IGBT modules for converter valves have been widely used in wind power transmission and grid interconnection. As the operating time increases, the IGBT chip solder layer is prone to thermal fatigue damage, leading to a decrease in module reliability. Therefore, it is particularly critical to evaluate the state of the IGBT module chip solder layer. To this end, this paper proposes a data-driven method for evaluating the state of the IGBT module chip solder layer for converter valves. Firstly, the fatigue mechanism of the solder layer is analyzed, and evaluation parameters that can reflect the fatigue state of the chip solder layer are selected based on their ability to represent data and the ease of acquisition. Secondly, an electro-thermal coupling model of the IGBT module- 收稿日期:2024-06-14;修回日期:2024-09-12 基金项目:安徽省自然科学基金资助项目(JZ2023GJDQ0018) 第一作者:黄雄峰(1980—),男,合肥工业大学副教授,博士,主要从事检测技术与自动化装置应用方向研究.E-mail: hfut_huangxf@hfut.edu.cn 通信作者:张宇娇(1978—),女,合肥工业大学教授,博士生导师,主要从事电气设备多物理场建模与仿真、基于数字孪生技术的电气设备故障诊断与健康寿命管理方向研究.E-mail: zhangyujiao@hfut.edu.cn 第1期黄雄峰等:基于数据驱动的换流阀用IGBT模块芯片焊料层状态评估河北大学学报(自然科学版) 第45卷with different fatigue damage states of the solder layer is established, and finite element calculations are performed to obtain ‘fatigue state-evaluation parameter data. Finally, considering the non-linearity and cross-correlation issues between the fatigue state of the chip solder layer and the evaluation parameters, multiple algorithms are selected to jointly achieve the mapping from the evaluation parameters to the fatigue state of the chip solder layer and predict the development trend of the evaluation parameters. The results show that the accuracy and real-time performance of this evaluation method can meet the engineering needs, providing a reliable basis for the operation and maintenance of IGBT modules.

Key words: chip solder layer, state assessment, data-driven, evaluation parameter, electrothermal coupling model

CLC Number:

TP181

HUANG Xiongfeng, DUAN Xiyao, HUANG Ming, CHEN Zhong, ZHU Lin, ZHANG Yujiao. Data driven solder layer state evaluation of IGBT module chip for converter valve[J]. Journal of Hebei University(Natural Science Edition), 2025, 45(1): 10-19.

References

[1] 赵智强, 帕孜来·马合木提,刘行行,等.光伏逆变器IGBT器件接线故障诊断方法[J].河北大学学报(自然科学版), 2024,44(1): 17-26. DOI: 10.3969/j.issn.1000-1565.2024.01.003.
[2] 张艳梅,雒雯霞,孙小平,等.基于压接型IGBT器件的柔直换流阀功率模块多物理场耦合仿真分析[J].高压电器, 2021,57(11): 84-92. DOI: 10.13296/j.1001-1609.hva.2021.11.011.
[3] 王争东,罗盟,成永红.高压大功率IGBT失效机理和耐高温改性有机硅灌封材料研究综述[J].高电压技术, 2023,49(4): 1632-1644. DOI: 10.13336/j.1003-6520.hve.20221925.
[4] 张宇娇,范虹兴,张炫焜,等.柔性直流输电换流阀用IGBT模块焊料层疲劳寿命研究[J].高电压技术, 2020,46(10): 3381-3389. DOI: 10.13336/j.1003-6520.hve.20200596.
[5] 陈民铀,陈一高,高兵,等.计及焊料层疲劳累积效应的IGBT模块寿命评估[J].中国电机工程学报, 2018,38(20): 6053-6061. DOI: 10.13334/j.0258-8013.pcsee.172213.
[6] 唐圣学,马强,陈冬,等.IGBT模块焊料层空洞生长分析与评估方法[J].仪器仪表学报, 2020,41(8): 244-254. DOI: 10.19650/j.cnki.cjsi.J2006505.
[7] DUM X, GUOQ Y, WANGH B, et al. An improved cauer model of IGBT module: inclusive void fraction in solder layer[J]. IEEE Trans Compon, Packag Manufa Technol, 2020, 10(8): 1401-1410. DOI: 10.1109/tcpmt.2020.3010064.
[8] 丁雪妮,陈民铀,赖伟,等.多芯片并联IGBT模块老化特征参量甄选研究[J].电工技术学报, 2022,37(13): 3304-3316. DOI: 10.19595/j.cnki.1000-6753.tces.210792.
[9] 祝令瑜,占草,刘琛硕,等.高压IGBT劣化机理分析及状态监测技术研究综述[J].高电压技术, 2021,47(3): 903-916. DOI: 10.13336/j.1003-6520.hve.20191819.
[10] 赵泽宇,杜明星.多数据驱动人工神经网络的IGBT结温在线估计方法[J].电子测量与仪器学报, 2022,36(7): 223-229. DOI: 10.13382/j.jemi.B2104628.
[11] HUY G, SHIP P, LIH, et al. Health condition assessment of base-plate solder for multi-chip IGBT module in wind power converter[J]. IEEE Access, 2019, 7: 72134-72142. DOI: 10.1109/ACCESS.2019.2918029.
[12] HUANGY L, DENGH F, LUOY F, et al. Fatigue mechanism of die-attach joints in IGBTs under low-amplitude temperatureswings based on 3D electro-thermal-mechanical FE simulations[J]. IEEE Trans Ind Electron, 2021, 68(4): 3033-3043. DOI: 10.1109/TIE.2020.2977563.
[13] WEIK X, WANGW B, HUZ, et al. Condition monitoring of IGBT modules based on changes of thermal characteristics[J]. IEEE Access, 2019, 7: 47525-47534. DOI: 10.1109/ACCESS.2019.2909928.
[14] DANGL Z, YANGK, ZHANGQ P, et al. Research on failure mechanism and health evaluation index system of welding IGBT module[C] //2022 3rd International Conference on Advanced Electrical and Energy Systems(AEES). IEEE, Lanzhou, 2022: 186-190. DOI: 10.1109/AEES56284.2022.10079292.
[15] HU R, XIAD H, HEZ G, et al. Experiment and simulation study of IGBT failure in IH heater[C] //2022 IEEE 17th Conference on Industrial Electronics and Applications(ICIEA). IEEE, Chengdu, 2022: 434-438. DOI: 10.1109/ICIEA54703.2022.10006145.
[16] 柯灿.考虑多特征参数的IGBT服役性能评估研究[D].北京: 北京交通大学, 2022.
[17] XIANGD W, ZHAON, LIH, et al. Noncontact monitoring of IGBT turn-OFF time using PWM switching ringing for inverter-fed machine systems[J]. IEEE Trans Power Electron, 2021, 36(10): 11055-11067. DOI: 10.1109/TPEL.2021.3070354.
[18] HAQUEMS, CHOI S, BAEKJ. Auxiliary particle filtering-based estimation of remaining useful life of IGBT[J]. IEEE Trans Ind Electron, 2018, 65(3): 2693-2703. DOI: 10.1109/TIE.2017.2740856.
[19] CHENJ B, LIUB W, HUM H, et al. Study of the solder characteristics of IGBT modules based on thermal-mechanical coupling simulation[J]. Materials(Basel), 2023, 16(9): 3504. DOI: 10.3390/ma16093504.
[20] JIANGM G, FUGC, CECCARELLI L, et al. Finite element modeling of IGBT modules to explore the correlation between electric parameters and damage in bond wires[C].2019 IEEE Energy Conversion Congress and Exposition(ECCE). 2019: 839-844. DOI: 10.1109/ECCE.2019.8912236.
[21] 江南,陈民铀,徐盛友,等.计及裂纹损伤的IGBT模块热疲劳失效分析[J].浙江大学学报(工学版), 2017,51(4): 825-833. DOI: 10.3785/j.issn.1008-973X.2017.04.025.
[22] 周健波.基于IGBT动态模型的电-热-力多物理场耦合失效分析[D].合肥: 合肥工业大学,2020. DOI: 10.27101/d.cnki.ghfgu.2020.000521.
[23] 杨剑锋,乔佩蕊,李永梅,等.机器学习分类问题及算法研究综述[J].统计与决策, 2019,35(6): 36-40. DOI: 10.13546/j.cnki.tjyjc.2019.06.008.
[24] 戚元星,崔双喜.集成学习在电网假数据入侵检测中的应用[J].河北大学学报(自然科学版), 2022, 42(1):105-112. DOI:10.3969/j.issn.1000-1565.2022.01.015.
[25] 崔丽娟,李凯,倪志宏.基于分类的集成学习算法研究[J].河北大学学报(自然科学版), 2007,27(4): 423-427. DOI: 10.3969/j.issn.1000-1565.2007.04.020.
[26] 李佳,郭剑毅,刘艳超,等.基于多分类器加权投票法的越南语组合歧义消歧[J].计算机科学, 2018,45(1): 167-172. DOI: 10.11896/j.issn.1002-137X.2018.01.029.
[27] 柴变芳,杨蕾,王建岭,等.集成局部和全局关键特征的文本情感分类方法[J].河北大学学报(自然科学版), 2021,41(2): 201-211. DOI: 10.3969/j.issn.1000-1565.2021.02.014.
[28] 唐圣学,马强,陈冬等.IGBT模块焊料层空洞生长分析与评估方法[J].仪器仪表学报,2020,41(8):244-254.DOI:10.19650/j.cnki.J2006505. (