Insulated Gate Bipolar Transistors (IGBTs) are one of the most used power semiconductor devices for energy conversion applications, due to their high performance. In this work we have developed a monitoring system for IGBTs installed in Fully Electric Vehicles (FEVs), which are operating under very variable working conditions. The monitoring system is based on a Self-Organizing Map (SOM), trained considering data collected from healthy IGBTs. An indicator of the IGBT degradation is defined as the distance between the measured SOM input vector, i.e., the signal measured on the monitored IGBT, and its SOM Best Matching Unit (BMU) representative of an healthy IGBT in similar working conditions. Then, a method based on the definition of a utility function for the identification of the threshold value to be used for the classification of the IGBT degradation state is proposed. The approach is verified with respect to experimental data collected from an inverter connected to an electric motor, and is shown able to identify the IGBTs degradation state regardless of the actual operating condition.
How to Cite
fault diagnosis, IGBT, electric vehicle, Self-organizing maps
Chokhawala, R. S., Catt, J., & Kiraly, L., (1995). Discussion on IGBT short-circuit behavior and fault protection schemes, IEEE Transactions on Industry Applications, 31 (2), pp. 256-263.
Fuchs, F. W., (2003). Some diagnosis methods for voltage source inverters in variable speed drives with induction machines - A survey, Proceedings 29th Annual Conf. IEEE Ind. Electron. Soc., vol. 2, , pp. 1378–1385.
Gonçalves, L.F., Schneider, E.L., Henriques, R.V.B., Lubaszewski, M., Bosa, J.L., & Engel, P.M., (2010). Fault prediction in electrical valves using temporal
kohonen maps, LATW2010 - 11th Latin-American Test Workshop, art. no. 5550338.
Hudgins, J., (2013). Power electronic devices in the future, IEEE J. Emerg. Sel. Topics Power Electron., vol. 1, no.1, pp. 11–17.
Huang, R., Xi, L., Li, X., Liu, C., Qiu, H., & Lee, J., (2007).Residual life predictions for ball bearings based on self- organizing map and back propagation neural network methods, Mechanical Systems and Signal Processing, 21 (1), pp. 193-207.
Shaoyong, Y., Bryant, A., Mawby, P., Dawei, X., Li, R., & Tavner, P., (2011). An industry-based survey of reliability in power electronic converters, IEEE Trans. Ind. Appl., vol. 47, no. 3, pp. 1441–1451, May/Jun.
Ji, B., Pickert, V., Cao, W., & Zahawi, B., (2013). In situ diagnostics and prognostics of wire bonding faults in IGBT modules for electric vehicle drives, IEEE Transactions on Power Electronics, 28 (12), art. no. 6479354, pp. 5568-5577.
Kohonen, T., (2005). Self-Organizing Maps. Series in Information Sciences, Vol. 30. Springer, Heidelberg. Second ed. 1997.
Lu, B., & Sharma, S. K., (2009). A literature review of IGBT fault diagnostic and protection methods for power inverters, IEEE Trans. Ind. Appl., vol. 45, no. 5, pp. 1770–1777.
Oh, H., Han, B., McCluskey, P., Han, C., & Youn, B.D., (2015). Physics-of-failure, condition monitoring, and prognostics of insulated gate bipolar transistor modules: A review, IEEE Transactions on Power Electronics, 30 (5), art. no. 6874580, pp. 2413-2426.
Patil, N., Das, D., Goebel, K., & Pecht, M., (2008). Identification of failure precursor parameters for Insulated Gate Bipolar Transistors (IGBTs), 2008 International Conference on Prognostics and Health Management, PHM 2008, art. no. 4711417.
Qiu, H., & Lee, J., (2004). Feature fusion and degradation detection using self-organizing map, Proceedings of the 2004 International Conference on Machine Learning and Applications, ICMLA '04, pp. 107-114.
Smet, V., Forest, F., Huselstein, J.J., Rashed, A., & Richardeau, F., (2013). Evaluation of Vce monitoring as a real-time method to estimate aging of bond wire- IGBT modules stressed by power cycling, IEEE Transactions on Industrial Electronics, 60 (7), art. no. 6191320, pp. 2760-2770.
Thébaud, J.M., Woirgard, E., Zardini, C., Azzopardi, S., Briat, O., & Vinassa, J.M., (2000). Strategy for Designing Accelerated Aging Tests to Evaluate IGBT Power Modules Lifetime in Real Operation Mode, IEEE Transactions on components and packaging technologies, Vol. 26, No. 2.
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