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Cost-Effective Prognostics of IGBT Bond Wires with Consideration of Temperature Swing
IEEE Transactions on Power Electronics ( IF 6.7 ) Pub Date : 2020-07-01 , DOI: 10.1109/tpel.2019.2959953
Keting Hu , Zhigang Liu , He Du , Lorenzo Ceccarelli , Francesco Iannuzzo , Frede Blaabjerg , Ibrahim Adamu Tasiu

This article presents a cost-effective prognostic method for the bond wires in the insulated-gate bipolar transistor (IGBT). Consider that the crack propagation in the wire bond leads to the bond wire liftoff, the corresponding state equation is established from the fracture mechanics theory, with the consideration of the uneven distribution of the temperature swings. Hence, the proposed model can work under different loading conditions. With the fact that the on-state voltage $(v_{{\rm{ce,on}}})$ of the IGBT shifts with the crack propagation, the history $v_{{\rm{ce,on}}}$ is used to predict the remaining useful lifetime (RUL), through which numerous power cycling tests are avoided, and low economical cost for doing prognosis is fulfilled. In this article, the functional relationship between the increase of $v_{{\rm{ce,on}}}$ and the crack length of each bond wire is obtained through finite-element simulation, while the effects of the temperature variation and metallization degradation to the $v_{{\rm{ce,on}}}$ are compensated. Thus, the output equation can be obtained. Then, the unknown parameters of the aforementioned equations and the current crack length can be estimated by the particle-based marginalized resample-move algorithm. Finally, the RUL can be predicted effectively by evolving the particles obtained in the algorithm. The proposed method has been validated by the power cycling test.

中文翻译:

考虑温度波动的 IGBT 键合线的成本效益预测

本文介绍了一种经济高效的绝缘栅双极晶体管 (IGBT) 键合线预测方法。考虑到焊线裂纹扩展导致焊线剥离,从断裂力学理论建立相应的状态方程,并考虑温度波动分布不均匀。因此,所提出的模型可以在不同的负载条件下工作。事实上,-状态电压 $(v_{{\rm{ce,on}}})$ IGBT 随裂纹扩展而变化的历史 $v_{{\rm{ce,on}}}$用于预测剩余使用寿命(RUL),通过它避免了大量的功率循环测试,并实现了预测的低经济成本。在本文中,增加之间的函数关系$v_{{\rm{ce,on}}}$ 通过有限元模拟得到每条焊线的裂纹长度,而温度变化和金属化退化对焊线的影响 $v_{{\rm{ce,on}}}$得到补偿。因此,可以得到输出方程。然后,上述方程的未知参数和当前裂纹长度可以通过基于粒子的边缘化重采样移动算法进行估计。最后,通过对算法中得到的粒子进行进化,可以有效地预测 RUL。所提出的方法已通过功率循环测试验证。
更新日期:2020-07-01
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