Prognosis of wire bond lift-off fault of an IGBT based on multisensory approach

The safe and continuous operation of the power switches of the inverter units is vital in assisting the functioning of the inverter units. This paper proposes an algorithm for the condition monitoring and prognosis of wire-bond fault in an IGBT- extensively used power switch in inverter systems. The proposed algorithm employs both on-state collector emitter voltage and collector current in the estimation of IGBT junction temperature. These two signals complement each other as thermal sensitive electrical parameters and results in better estimation of junction temperature. This algorithm has integrated a stochastic method and Coffin Manson model to introduce criticality matrix which is used to determine the necessity for IGBT replacement. Both simulation result and experiment data verified the proposed. The proposed algorithm has the scope to be further modified for the condition monitoring of a more complex system in the future.

[1]  Tony Greenfield,et al.  Theory and Problems of Probability and Statistics , 1982 .

[2]  Frede Blaabjerg,et al.  Study and Handling Methods of Power IGBT Module Failures in Power Electronic Converter Systems , 2015, IEEE Transactions on Power Electronics.

[3]  Frede Blaabjerg,et al.  An overview of the reliability prediction related aspects of high power IGBTs in wind power applications , 2011, Microelectron. Reliab..

[4]  Jerry L. Hudgins,et al.  Monitoring IGBT's health condition via junction temperature variations , 2014, 2014 IEEE Applied Power Electronics Conference and Exposition - APEC 2014.

[5]  Fei Wang,et al.  Junction Temperature Measurement of IGBTs Using Short-Circuit Current as a Temperature-Sensitive Electrical Parameter for Converter Prototype Evaluation , 2015, IEEE Transactions on Industrial Electronics.

[6]  Bongtae Han,et al.  Physics-of-Failure, Condition Monitoring, and Prognostics of Insulated Gate Bipolar Transistor Modules: A Review , 2015, IEEE Transactions on Power Electronics.

[7]  O. Apeldoorn,et al.  New IGBT model for PSPICE , 2002 .

[8]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[9]  M. Ciappa,et al.  Reliability of High-Power IGBT Modules for Traction Applications , 2007, 2007 IEEE International Reliability Physics Symposium Proceedings. 45th Annual.

[10]  L. Dupont,et al.  Temperature Measurement of Power Semiconductor Devices by Thermo-Sensitive Electrical Parameters—A Review , 2012, IEEE Transactions on Power Electronics.

[11]  Gehan A. J. Amaratunga,et al.  Long-Lifetime Power Inverter for Photovoltaic AC Modules , 2008, IEEE Transactions on Industrial Electronics.

[12]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1967 .

[13]  Frédéric Richardeau,et al.  Evaluation of $V_{\rm ce}$ Monitoring as a Real-Time Method to Estimate Aging of Bond Wire-IGBT Modules Stressed by Power Cycling , 2013, IEEE Transactions on Industrial Electronics.

[14]  John Harris,et al.  Handbook of mathematics and computational science , 1998 .

[15]  Annette Muetze,et al.  Condition monitoring and failure prognosis of IGBT inverters based on on-line characterization , 2014, 2014 IEEE Energy Conversion Congress and Exposition (ECCE).

[16]  M. Pecht,et al.  Identification of failure precursor parameters for Insulated Gate Bipolar Transistors (IGBTs) , 2008, 2008 International Conference on Prognostics and Health Management.