Degredation Modeling and Remaining Useful Life Prediction of Electrolytic Capacitors under Thermal Overstress Condition Using Particle Filters
Prognostic and remaining useful life (RUL) predictions for electrolytic capacitors under thermal overstress condition are investigated in this paper. In the first step, the degradation process is modeled as a physics of failure process. All of the relevant parameters and states of the capacitor are considered during the degradation process. A particle filter approach is utilized to derive the dynamic form of the degradation model and estimate the current state of capacitor health. This model is then used to get more accurate estimation of the Remaining Useful Life (RUL) of the capacitors as they are subjected to the thermal stress conditions. The paper includes an experimental study, where the degradation of a set of identical capacitors under thermal overstress conditions is studied to demonstrate and validate the performance of the degradation modeling approach.
How to Cite
Celaya, J. R., Wysocki, P., Vashchenko, V., Saha, S., Goebel, K. (2010, September). Accelerated aging system for prognostics of power semiconductor devices. In AU- TOTESTCON, 2010 IEEE (pp. 1-6). IEEE.
Celaya, J. R., Kulkarni, C. S., Biswas, G., Goebel, K. (2012). Towards A Model-based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging. International Journal of Prognostics and Health Management.
Gmez-Aleixandre, C., Albella, J. M., Martnez-Duart, J. M. (1986). Pressure build-up in aluminium electrolytic capacitors under stressed voltage conditions. Journal of applied electrochemistry, 16(1), 109-115.
Goebel, K., Saha, B., Saxena, A., Celaya, J., Christophersen, J. (2008). Prognostics in battery health management. Instrumentation and Measurement Magazine, IEEE, 11(4), 33-40.
Goodman, D. L., Vermeire, B., Spuhler, P., Venka- tramani, H. (2005, March). Practical application of PHM/prognostics to COTS power converters. In Aerospace Conference, 2005 IEEE (pp. 3573-3578). IEEE.
Gordon, N. J., Salmond, D. J., Smith, A. F. (1993). Novel approach to nonlinear/non-Gaussian Bayesian state estimation. In IEE Proceedings F (Radar and Signal Processing) (Vol. 140, No. 2, pp. 107-113). IET Digital Library.
Julier, S. J., Uhlmann, J. K. (1997, July). New extension of the Kalman filter to nonlinear systems. In AeroSense’97 (pp. 182-193). International Society for Optics and Photonics.
Kulkarni, C., Biswas, G., Koutsoukos, X. (2009, October). A prognosis case study for electrolytic capacitor degradation in DC-DC converters. In PHM Conference.
Kulkarni, C. S., Celaya, J. R., Biswas, G., Goebel, K. (2012, June). Physics based Modeling and Prognostics of Electrolytic Capacitors. Aerospace 2012, 19-21 June, Garden Grove, California.
Kulkarni, C. S., Celaya, J. R., Goebel, K., Biswas, G. (2012, September). Bayesian Framework Approach for Prognostic Studies in Electrolytic Capacitor under Thermal Overstress Conditions.
Kulkarni, C. S. (2013). A Physics-based Degradation Modeling Framework for Diagnostic and Prognostic Studies in Electrolytic Capacitors (Doctoral dissertation, Vanderbilt University).
Rdner, S. C., Wedin, P., Bergstrm, L. (2002). Effect of electrolyte and evaporation rate on the structural features of dried silica monolayer films. Langmuir, 18(24), 9327- 9333.
Ristic, B., Arulampalm, S., Gordon, N. J. (2004). Beyond the Kalman filter: Particle filters for tracking applications. Artech House Publishers.
Tasca, D. M. (1981, September). Pulse power response and damage characteristics of capacitors. In EOS/ESD Symposium Proceedings. Las Vegas: ESD Assn, Rome, NY (pp. 174-91).
Wan, E. A., Van Der Merwe, R. (2000). The unscented Kalman filter for nonlinear estimation. In Adaptive Systems for Signal Processing, Communications, and Control Symposium 2000. AS-SPCC. The IEEE 2000 (pp. 153-158). IEEE.
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