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| A Hybrid 3-D Reduced-Order Thermal Model for Temperature Observation of IGBT Modules |
| Tian Ye1, Bu Kaiyang1,2, Li Chushan1,2, Li Wuhua1, He Xiangning1 |
1. College of Electrical Engineering Zhejiang University Hangzhou 310027 China;
2. Zhejiang University-University of Illinois at Urbana-Champaign Institute Haining 314400 China |
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Abstract Online monitoring of IGBT module temperature is a key technology for enhancing the reliability of high-power converters. Among the various online temperature monitoring methods for IGBT modules, the thermal network method has garnered attention due to its ability to estimate the internal temperature distribution within the IGBT module. The temperature observer based on the thermal network model can correct the model by utilizing measurement information to reduce the impact of aging, temperature-dependent material parameters, and power loss calculation errors on temperature estimation accuracy. However, existing thermal models struggle to balance system observability and modeling accuracy, and their high model order complicates their application in temperature observers. Therefore, an observable reduced-order hybrid 3-D thermal model suitable for temperature observer for forced air-cooling multi-chip IGBT modules is proposed in this paper.
Firstly, a hybrid thermal network combining the strengths of the 3-D Cauer model and the Foster model is introduced for air-cooling multi-chip IGBT modules. This model ensures both thermal modeling accuracy and observability for air-cooled IGBT modules. Based on this model's structure, the corresponding state-space expression is also derived. Secondly, a nonlinear optimization algorithm is employed to refine and calibrate the thermal network model using experimental temperature measurements, reducing the deviation between thermal model parameters and actual parameters caused by uncertain material parameters in the computational fluid dynamics (CFD) model. Finally, the balanced truncation method is utilized to further reduce the order of the proposed thermal network model's state space while maintaining model accuracy.
In summary, the main contributions of this paper are:
(1) The proposed lumped parameter 3-D thermal network model addresses the challenge that existing reduced-order thermal models cannot accurately model air-cooling IGBT modules with system observability. The error between the proposed thermal network model and CFD simulation is less than 5%, whereas the existing 3-D Cauer model exhibits a maximum error exceeding 34%.
(2) The nonlinear optimization algorithm is applied to further correct model parameters. Experimental results demonstrate that this model parameter correction method can decrease the discrepancy between the model and the actual IGBT module by up to 78.69%.
(3) The order of the thermal model's state space is further reduced from 270 to 38 by the balanced truncation method, while the model accuracy is still guaranteed within 100 Hz, which further improves the computational efficiency compared to lumped parameter thermal network models.
In the future, based on the observable 3-D reduced-order thermal model proposed in this paper and incorporating sensor measurement information, the temperature observer will be further designed to reduce the impact of aging and loss calculation errors on temperature estimation, which can enhance the reliability of thermal monitoring for high-power IGBT modules.
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Received: 26 September 2023
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[1] 黄欣科, 王环, 周宇, 等. 兆瓦级光伏中压直流并网变换器研制及实证应用[J]. 电力系统自动化, 2022, 46(14): 150-157.
Huang Xinke, Wang Huan, Zhou Yu, et al.Development and empirical application of megawatt-level medium-voltage DC photovoltaic grid-connected converter[J]. Automation of Electric Power Systems, 2022, 46(14): 150-157.
[2] Feng Jianghua, Chu W Q, Zhang Zhixue, et al.Power electronic transformer-based railway traction systems: challenges and opportunities[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2017, 5(3): 1237-1253.
[3] Yang Shaoyong, Xiang Dawei, Bryant A, et al.Condition monitoring for device reliability in power electronic converters: a review[J]. IEEE Transactions on Power Electronics, 2010, 25(11): 2734-2752.
[4] Yang Shaoyong, Bryant A, Mawby P, et al.An industry-based survey of reliability in power electronic converters[C]//2009 IEEE Energy Conversion Congress and Exposition, San Jose, CA, USA, 2009: 3151-3157.
[5] 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 Jun, Zhang Li, Cheng Yu.Review of the lifetime evaluation for the IGBT module[J]. Transactions of China Electrotechnical Society, 2021, 36(12): 2560-2575.
[6] Blackburn D L.Temperature measurements of semiconductor devices-a review[C]//Twentieth Annual IEEE Semiconductor Thermal Measurement and Management Symposium, San Jose, CA, USA, 2004: 70-80.
[7] Chen Shiying, Vilchis-Rodriguez D, Djurović S, et al.Direct on chip thermal measurement in IGBT modules using FBG technology—sensing head interfacing[J]. IEEE Sensors Journal, 2022, 22(2): 1309-1320.
[8] Yang Yanyong, Zhang Pinjia.A novel converter-level IGBT junction temperature estimation method based on the bus voltage ringing[J]. IEEE Transactions on Power Electronics, 2022, 37(4): 4553-4563.
[9] 郑丹, 宁圃奇, 仇志杰, 等. 基于老化补偿的功率模块全生命周期在线结温监测方法[J]. 电工技术学报, 2024, 39(12): 3705-3717.
Zheng Dan, Ning Puqi, Qiu Zhijie, et al.Full life-cycle online junction temperature monitoring of power module based on aging compensation[J]. Transactions of China Electrotechnical Society, 2024, 39(12): 3705-3717.
[10] 杨舒萌, 孙鹏菊, 王凯宏, 等. 恒流驱动下基于VeE_max的IGBT模块解耦老化影响的结温测量方法[J]. 电工技术学报, 2022, 37(12): 3038-3047, 3072.
Yang Shumeng, Sun Pengju, Wang Kaihong, et al.Junction temperature measurement method of IGBT modules based on VeE-max under constant-current source drive which decouples fatigue effect[J]. Transactions of China Electrotechnical Society, 2022, 37(12): 3038-3047, 3072.
[11] Wang Haoran, Zhu Rongwu, Wang Huai, et al.A thermal modeling method considering ambient temperature dynamics[J]. IEEE Transactions on Power Electronics, 2020, 35(1): 6-9.
[12] Wang Ze, Qiao Wei.A physics-based improved Cauer-type thermal equivalent circuit for IGBT modules[J]. IEEE Transactions on Power Electronics, 2016, 31(10): 6781-6786.
[13] Iachello M, De Luca V, Petrone G, et al.Lumped parameter modeling for thermal characterization of high-power modules[J]. IEEE Transactions on Components, Packaging and Manufacturing Technology, 2014, 4(10): 1613-1623.
[14] 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, 3340.
Ding Xueni, Chen Minyou, Lai Wei, et al.Selection of aging characteristic parameter for multi-chips parallel IGBT module[J]. Transactions of China Electrotechnical Society, 2022, 37(13): 3304-3316, 3340.
[15] Ma Mingyao, Guo Weisheng, Yan Xuesong, et al.A three-dimensional boundary-dependent compact thermal network model for IGBT modules in new energy vehicles[J]. IEEE Transactions on Industrial Electronics, 2021, 68(6): 5248-5258.
[16] Zhan Cao, Zhu Lingyu, Wang Weicheng, et al.A large-scale identification approach for thermal parameters of multichips IGBT modules based on LLSO-SQP algorithm[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2023, 11(3): 2554-2564.
[17] Batard C, Ginot N, Antonios J.Lumped dynamic electrothermal model of IGBT module of inverters[J]. IEEE Transactions on Components, Packaging and Manufacturing Technology, 2015, 5(3): 355-364.
[18] Bahman A S, Ma Ke, Blaabjerg F.A lumped thermal model including thermal coupling and thermal boundary conditions for high-power IGBT modules[J]. IEEE Transactions on Power Electronics, 2018, 33(3): 2518-2530.
[19] Shi Yunming, Liu Jianqiang, Ai Yu, et al.Dynamic IGBT three-dimensional thermal network model considering base solder degradation and thermal coupling between IGBT chips[J]. IEEE Transactions on Transportation Electrification, 2023, 9(2): 2994-3011.
[20] 龙柳, 肖凡, 涂春鸣, 等. 基于热网络分区等效策略的Si/SiC混合器件耦合热参数辨识方法[J]. 电工技术学报, 2024, 39(12): 3718-3731.
Long Liu, Xiao Fan, Tu Chunming, et al.Enhanced identification approach for RC parameters of Si/SiC hybrid switches based on thermal network partition scheme[J]. Transactions of China Electrotechnical Society, 2024, 39(12): 3718-3731.
[21] Xu Mengqi, Ma Ke, Qi Yuhao, et al.Frequency-domain thermal coupling model of multi-chip power module[J]. IEEE Transactions on Power Electronics, 2023, 38(5): 6522-6532.
[22] Wang Ze, Qiao Wei.An online frequency-domain junction temperature estimation method for IGBT modules[J]. IEEE Transactions on Power Electronics, 2015, 30(9): 4633-4637.
[23] Chen Yu, Wu Qiang, Zhou Yu, et al.Physics-based thermal impedance model for power module by analytic fourier series based heat spreading angle[J]. Chinese Society for Electrical Engineering, 2022, 2(42): 715-728.
[24] Zhang Yi, Wang Zhongxu, Wang Huai, et al.Artificial intelligence-aided thermal model considering cross-coupling effects[J]. IEEE Transactions on Power Electronics, 2020, 35(10): 9998-10002.
[25] Li Hui, Zhou Bailing, Yao Ran, et al.A thermal twin modeling method of press pack IGBT based on power loss[J]. IEEE Transactions on Electron Devices, 2022, 69(12): 6922-6928.
[26] Dong Xiaojun, Griffo A, Wang Jiabin.Multiparameter model order reduction for thermal modeling of power electronics[J]. IEEE Transactions on Power Electronics, 2020, 35(8): 8550-8558.
[27] Cai Jie, Zhou Luowei, Sun Pengju, et al.Effect of TIM deterioration on monitoring of IGBT module thermal resistance and its compensation strategy[J]. IEEE Transactions on Components, Packaging and Manufacturing Technology, 2022, 12(5): 789-797.
[28] Akbari M, Tavakoli Bina M, Bahman A S, et al.An extended multilayer thermal model for multichip IGBT modules considering thermal aging[J]. IEEE Access, 2021, 9: 84217-84230.
[29] 崔曼, 胡震, 张腾飞, 等. 基于壳温信息的功率器件可靠性分析[J]. 电工技术学报, 2023, 38(24): 6760-6767.
Cui Man, Hu Zhen, Zhang Tengfei, et al.Reliability analysis of power device based on the case temperatures[J]. Transactions of China Electrotechnical Society, 2023, 38(24): 6760-6767.
[30] Wang Xiang, Castellazzi A, Zanchetta P.Observer based dynamic adaptive cooling system for power modules[J]. Microelectronics Reliability, 2016, 58: 113-118.
[31] van der Broeck C H, Lorenz R D, De Doncker R W. Monitoring 3-D temperature distributions and device losses in power electronic modules[J]. IEEE Transactions on Power Electronics, 2019, 34(8): 7983-7995.
[32] van der Broeck C H, De Doncker R W. Thermal monitoring of power electronic modules with minimal sensing effort[C]//2019 IEEE Energy Conversion Congress and Exposition (ECCE), Baltimore, MD, USA, 2019: 5989-5996.
[33] Xiao Xiuchen, Ge Xinglai, Ke Qianxia, et al.An adaptive temperature observer for electrothermal analysis of IGBT based on temperature characteristics[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2023, 11(2): 2246-2258.
[34] Dong Xiaojun, Griffo A, Hewitt D, et al.Reduced-order thermal observer for power modules temperature estimation[J]. IEEE Transactions on Industrial Electronics, 2020, 67(12): 10085-10094.
[35] Yu Yaoyi, Du Xiong, Zhou Junjie, et al.Condition monitoring of thermal fatigue of IGBT module using turning point of preheating stage of case temperature[J]. IEEE Transactions on Power Electronics, 2023, 38(3): 2866-2871.
[36] Wang Jianpeng, Chen Wenjie, Wang Laili, et al.A transient 3-D thermal modeling method for IGBT modules considering uneven power losses and cooling conditions[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2021, 9(4): 3959-3970.
[37] 许智亮, 葛兴来, 李金, 等. 计及流-热耦合热网络模型的IGBT结温计算[J]. 电气工程学报, 2022, 17(2): 19-26.
Xu Zhiliang, Ge Xinglai, Li Jin, et al.Calculation of IGBT junction temperature with thermal network model considering flow-thermal coupling[J]. Journal of Electrical Engineering, 2022, 17(2): 19-26.
[38] Xie Lihong, Yuan Xibo, Wang Wenbo.Thermal modeling of fan-cooled plate-fin heatsink considering air temperature rise for virtual prototyping of power electronics[J]. IEEE Transactions on Components, Packaging and Manufacturing Technology, 2020, 10(11): 1829-1839.
[39] Bonnans J F, Gilbert J C, Lemaréchal C, et al.Numerical Optimazation: Theoretical and Practical Aspects[M]. 2nd ed. Berlin: Springer-Verlag, 2006.
[40] Benner P, Schneider A.Balanced truncation model order reduction for LTI systems with many inputs or outputs[C]//19th International Symposium on Mathematical Theory of Networks and System (MTNS 2010), Budapest, Hungary, 2010: 5.
[41] Xu Zhiliang, Zhang Yichi, Wang Huimin, et al.A novel calculation method for IGBT junction temperature based on Fourier transform[J]. CPSS Transactions on Power Electronics and Applications, 2023, 8(1): 54-64.
[42] Ebersberger J, Hagedorn M, Lorenz M, et al.Potentials and comparison of inverter topologies for future all-electric aircraft propulsion[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2022, 10(5): 5264-5279. |
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2024, Vol. 39 
