A Simple Hybrid Model for Estimating Remaining Useful Life of SiC MOSFETs in Power Cycling Experiments

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Published Sep 4, 2023
Mattias P. Eng Andreas Lövberg Maciej Misiorny Wilhelm Söderkvist Vermelin Klas Brinkfeldt Madhav Mishra

Abstract

Recording and prediction of the accumulated damage, which will eventually lead to the failure of power electronic modules, is an aspect of high importance for power electronic systems design and, in particular, for development of Prognostic and Health Management (PHM) schemes for in-field applications. To this end, this paper presents a simple and cost-effective prognostic method for predicting the remaining useful life (RUL) of TO-247 packaged silicon carbide (SiC) metal-oxide semiconductor field-effect transistors (MOSFETs) subjected to power cycling experiments. The model assumes that the major failure mode is bond-wire lift-off and uses a damage accumulation scheme based on Paris’ crack law. The only inputs to the model are historical data on the average junction temperature swing and the temperature-compensated drain-source ON-state resistance at the peak temperature of the current cycle. Using only these two input values, the model is shown to predict RUL with surprising accuracy for the range of constant current loads determining cycling conditions under which the test data series have been acquired. This work is a first step in an ongoing project towards building more elaborate prognostic schemes for RUL-determination of SiC power MOSFETs in actual working conditions, using physics-informed neural networks (PINNs).  

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Keywords

SiC, MOSFET, RUL, Paris’ law, Power cycling, Damage accumulation, Wire bond

References
Bayerer, R., Herrmann, T., Licht, T., Lutz, J., & Feller, M. (2008). Model for Power Cycling lifetime of IGBT Modules—Various factors influencing lifetime. 5th International Conference on Integrated Power Electronics Systems, 1–6.

Benguediab, M., Bouchouicha, B., Mokhtar, Z., & Mazari, M. (2012). Crack propagation under constant amplitude loading based on an energetic parameters and fractographic analysis. Materials Research, 15, 544–548. https://doi.org/10.1590/S151614392012005000072

Degrenne, N., & Mollov, S. (2018). Diagnostics and Prognostics of Wire-Bonded Power SemiConductor Modules subject to DC Power Cycling with Physically-Inspired Models and Particle Filter. PHM Society European Conference, 4(1), Article 1. https://doi.org/10.36001/phme.2018.v4i1.167

Dornic, N., Ibrahim, A., Khatir, Z., Degrenne, N., Mollov, S., & Ingrosso, D. (2020). Analysis of the aging mechanism occurring at the bond-wire contact of IGBT power devices during power cycling. Microelectronics Reliability, 114, 113873. https://doi.org/10.1016/j.microrel.2020.113873

Dornic, N., Ibrahim, A., Khatir, Z., Tran, S. H., Ousten, J.P., Ewanchuk, J., & Mollov, S. (2018). Analysis of the degradation mechanisms occurring in the topside interconnections of IGBT power devices during power cycling. Microelectronics Reliability, 88–90, 462–469. https://doi.org/10.1016/j.microrel.2018.07.041

Hanif, A., Yu, Y., DeVoto, D., & Khan, F. (2019). A Comprehensive Review Toward the State-of-theArt in Failure and Lifetime Predictions of Power Electronic Devices. IEEE Transactions on Power Electronics, 34(5), 4729–4746. https://doi.org/10.1109/TPEL.2018.2860587

Held, M., Jacob, P., Nicoletti, G., Scacco, P., & Poech, M.H. (1997). Fast power cycling test of IGBT modules in traction application. Proceedings of Second International Conference on Power Electronics and Drive Systems, 1, 425–430 vol.1. https://doi.org/10.1109/PEDS.1997.618742

Hendrycks, D., Basart, S., Mu, N., Kadavath, S., Wang, F., Dorundo, E., Desai, R., Zhu, T., Parajuli, S., Guo, M., Song, D., Steinhardt, J., & Gilmer, J. (2021). The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 8320–8329. https://doi.org/10.1109/ICCV48922.2021.00823

Hu, K., Liu, Z., Du, H., Ceccarelli, L., Iannuzzo, F., Blaabjerg, F., & Tasiu, I. A. (2020). Cost-Effective Prognostics of IGBT Bond Wires With Consideration of Temperature Swing. IEEE Transactions on Power Electronics, 35(7), 6773– 6784. https://doi.org/10.1109/TPEL.2019.2959953

Lakshminarayanan, B., Pritzel, A., & Blundell, C. (2017). Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles (arXiv:1612.01474). arXiv. https://doi.org/10.48550/arXiv.1612.01474

Lu, Y., & Christou, A. (2019). Prognostics of IGBT modules based on the approach of particle filtering. Microelectronics Reliability, 92, 96–105. https://doi.org/10.1016/j.microrel.2018.11.012

Paris, P., & Erdogan, F. (1963). A Critical Analysis of Crack Propagation Laws. Journal of Basic Engineering, 85(4), 528–533. https://doi.org/10.1115/1.3656900

Sasaki, K., Iwasa, N., Kurosu, T., Saito, K., Koike, Y., Kamita, Y., & Toyoda, Y. (2008). Thermal and Structural Simulation Techniques for Estimating Fatigue Life of an IGBT Module. 2008 20th International Symposium on Power Semiconductor Devices and IC’s, 181–184. https://doi.org/10.1109/ISPSD.2008.4538928

Söderkvist Vermelin, W., Lövberg, A., Misiorny, M., Eng, M. P., & Brinkfeldt, K. (2023). Data-Driven Remaining Useful Life Estimation of Discrete Power Electronic Devices. European Safety and Reliability Conference, In press.

Song, Y., & Wang, B. (2013). Survey on Reliability of Power Electronic Systems. IEEE Transactions on Power Electronics, 28(1), 591–604. https://doi.org/10.1109/TPEL.2012.2192503

Tada, H., Paris, P. C., & Irwin, G. R. (2000). The Stress Analysis of Cracks Handbook, Third Edition. https://doi.org/10.1115/1.801535

Van Rossum, G., & Drake, F. L. (2009). Python 3 Reference Manual. CreateSpace.

Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., ... van Mulbregt, P. (2020). SciPy 1.0: Fundamental algorithms for scientific computing in Python. Nature Methods, 17(3), Article 3. https://doi.org/10.1038/s41592-019-0686-2
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Special Session Papers