Defect is one of the key factors in reducing the reliability of the insulated gate bipolar transistor (IGBT) module, so developing the diagnostic method for defects inside the IGBT module is an important measure to avoid catastrophic failure and improves the reliability of power electronic converters. For this reason, a novel diagnostic method based on the approximate entropy (ApEn) theory is presented in this paper, which can provide statistical diagnosis and allow the operator to replace defective IGBT modules timely. The proposed method is achieved by analyzing the cross ApEn of the gate voltages before and after the occurring of defects. Due to the local damage caused by aging, the intrinsic parasitic parameters of packaging materials or silicon chips inside the IGBT module such as parasitic inductances and capacitances may change over time, which will make remarkable variation in the gate voltage. That is to say the gate voltage is close coupled with the defects. Therefore, the variation is quantified and used as a precursor parameter to evaluate the health status of the IGBT module. Experimental results validate the correctness of the proposed method. 1. Introduction The survey carried out in [1] shows that the reliability of power electronic converters deserves increasing interest from industry in recent years, but the satisfaction level with reliability monitoring is low at 50%. This suggests more research effort is needed. One of the major challenges is the health management of power electronic devices due to their significant impacts on the degradation of power electronic converters. At present, the IGBTs are the most used power electronic devices in many industrial applications as well as some safe-critical fields such as traction and renewable energy [2, 3], where stringent reliability is required. Though the reliability of IGBTs has been substantial developed recently, the failure rate of IGBTs dropped from 1,000 FITs in 1995 to 20 FITs in 2000, and to only a few FITs currently where 1 FIT is equal 1 × 10？9 failures per device-hour [4], the IGBTs used in those safe-critical fields mentioned above may undergo severe electrical and thermal stress. Such as wind power generation, the IGBTs are subject to large-junction temperature swings during normal operation due to the inherent intermittent nature of the wind speed and low-converter-modulation frequencies [5]. Therefore, monitoring reliability degradation of IGBTs becomes an important issue and still remains as an open topic for research [6]. Reliability is the ability of a product or system
References
[1]
S. Yang, A. Bryant, P. Mawby, D. Xiang, L. Ran, and P. Tavner, “An industry-based survey of reliability in power electronic converters,” IEEE Transactions on Industry Applications, vol. 47, no. 3, pp. 1441–1451, 2011.
[2]
S. Bernet, “Recent developments of high power converters for industry and traction applications,” IEEE Transactions on Power Electronics, vol. 15, no. 6, pp. 1102–1117, 2000.
[3]
Z. Chen, J. M. Guerrero, and F. Blaabjerg, “A review of the state of the art of power electronics for wind turbines,” IEEE Transactions on Power Electronics, vol. 24, no. 8, pp. 1859–1875, 2009.
[4]
S. Yang, D. Xiang, A. Bryant, P. Mawby, L. Ran, and P. Tavner, “Condition Monitoring for Device Reliability in Power Electronic Converters: A Review,” IEEE Transactions on Power Electronics, vol. 25, pp. 2734–2752, 2011.
[5]
A. Bryant, S. Y. Yang, P. Mawby et al., “Investigation into IGBT dV/dt during turn-off and its temperature dependence,” IEEE Transactions on Power Electronics, vol. 26, pp. 3019–3031, 2011.
[6]
D. Xiang, L. Ran, P. Tavner, A. Bryant, S. Yang, and P. Mawby, “Monitoring solder fatigue in a power module using case-above-ambient temperature rise,” IEEE Transactions on Industry Applications, vol. 47, pp. 2578–2259, 2011.
[7]
M. G. Pecht, Prognostics and Health Management of Electronics, John Wiley & Sons, Hoboken, NJ, USA, 2008.
[8]
N. Patil, D. Das, and M. Pecht, “A prognostic approach for non-punch through and field stop IGBTs,” Microelectronics Reliability, vol. 52, pp. 482–488, 2011.
[9]
Y. Xiong, X. Cheng, Z. J. Shen, C. Mi, H. Wu, and V. K. Garg, “Prognostic and warning system for power-electronic modules in electric, hybrid electric, and fuel-cell vehicles,” IEEE Transactions on Industrial Electronics, vol. 55, no. 6, pp. 2268–2276, 2008.
[10]
D. W. Xiang, L. Ran, P. Tavner, S. Y. Yang, A. Bryant, and P. Mawby, “Condition monitoring power module solder fatigue using inverter harmonic identification,” IEEE Transactions on Power Electronics, vol. 27, pp. 235–247, 2012.
[11]
M. Musallam, C. Buttay, M. Whitehead, and C. M. Johnson, “Real-time compact electronic thermal modelling for health monitoring,” in Proceedings of the European Conference on Power Electronics and Applications (EPE '07), September 2007.
[12]
N. Patil, S. Menon, D. Das, and M. Pecht, “Anomaly detection of non punch through insulated gate bipolar transistors (IGBT) by robust covariance estimation techniques,” in Proceedings of the 2nd International Conference on Reliability, Safety and Hazard: Risk-Based Technology and Physics-of-Failure Methods (ICRESH '10), pp. 68–72, December 2010.
[13]
E. Sutrisno, Q. Fan, D. Das, and M. Pecht, “Anomaly Detection for Insulated Gate Bipolar Transistor (IGBT) under power cycling using a K‐Nearest neighbor technique,” in Proceedings of the Prognostics and Health Management Solutions Conference (MFPT '12), Dayton, Ohio, USA, 2012.
[14]
N. Patil, D. Das, C. Yin, H. Lub, C. Bailey, and M. Pecht, “A fusion approach to IGBT power module prognostics,” in Proceedings of the 10th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE '09), pp. 1–5, Delft, The Netherlands, April 2009.
[15]
M. Musallam, C. M. Johnson, C. Yin, H. Lu, and C. Bailey, “In-service life consumption estimation in power modules,” in Proceedings of the 13th International Power Electronics and Motion Control Conference (EPE-PEMC '08), pp. 76–83, New York, NY, USA, September 2008.
[16]
M. Ciappa, “Selected failure mechanisms of modern power modules,” Microelectronics Reliability, vol. 42, no. 4-5, pp. 653–667, 2002.
[17]
B. Lu and S. K. Sharma, “A literature review of IGBT fault diagnostic and protection methods for power inverters,” IEEE Transactions on Industry Applications, vol. 45, no. 5, pp. 1770–1777, 2009.
[18]
A. Qun-Tao, S. Li-Zhi, Z. Ke, and S. Li, “Switching function model-based fast-diagnostic method of open-switch faults in inverters without sensors,” IEEE Transactions on Power Electronics, vol. 26, no. 1, pp. 119–126, 2011.
[19]
D. Pan, X. Kai-gui, Z. Li, and R. Xianliang, “Open-switch fault diagnosis and system reconfiguration of doubly fed wind power converter used in a microgrid,” IEEE Transactions on Power Electronics, vol. 26, no. 3, pp. 816–821, 2011.
[20]
S. M. Pincus, “Approximate entropy as a measure of system complexity,” Proceedings of the National Academy of Sciences of the United States of America, vol. 88, no. 6, pp. 2297–2301, 1991.
[21]
W. W. Sheng and R. P. Colino, Power Electronic Modules: Design and Manufacture, CRC Press, Boca Raton, Fla, USA, 2005.
[22]
N. Patil, J. Celaya, D. Das, K. Goebel, and M. Pecht, “Precursor parameter identification for insulated gate bipolar transistor (IGBT) prognostics,” IEEE Transactions on Reliability, vol. 58, no. 2, pp. 271–276, 2009.
[23]
V. K. Khanna, The Insulated Gate Bipolar Transistor: IGBT Theory and Design, IEEE Press, Piscataway, NJ, USA, 2003.
[24]
K. Xing, F. C. Lee, and D. Boroyevich, “Extraction of parasitics within wire-bond IGBT modules,” in Proceedings of the 13th Annual Applied Power Electronics Conference and Exposition (APEC '98), pp. 497–503, Anaheim, Calif, USA, February 1998.
[25]
N. Mohan, T. M. Undeland, and W. P. Robbins, Power Electronics: Converters, Applications, and Design, John Wiley & Sons, New York, NY, USA, 3rd edition, 2003.
[26]
A. R. Hefner and D. M. Diebolt, “Experimentally verified IGBT model implemented in the Saber circuit simulator,” IEEE Transactions on Power Electronics, vol. 9, no. 5, pp. 532–542, 1994.
