Early Detection of SMPS Electromagnetic Interference Failures Using Fuzzy Multi-Task Functional Fusion Prediction
Volume 9, Issue 4, Page No 35-50, 2024
Author’s Name: Declan Mallamo*, Michael Azarian, Michael Pecht
View Affiliations
Center for Advanced Life Cycle Engineering, University of Maryland, College Park, MD 20742, USA
a)whom correspondence should be addressed. E-mail: dmallamo@umd.edu
Adv. Sci. Technol. Eng. Syst. J. 9(4), 35-50 (2024); 
DOI: 10.25046/aj090405
Keywords: Prognostics Health Management, Functional Data Analysis, Electromagnetic Interference, Multitask Lasso Regression, Aluminum Electrolytic Capacitors
Export Citations
This study addresses the need for improved prognostics in switch-mode power supplies (SMPS) that incorporate electromagnetic interference (EMI) filters, with a focus on aluminum electrolytic capacitors, which are critical for the reliability of these systems. The primary aim is to develop a robust model-based approach that can accurately predict the degradation and operational lifetime of these capacitors under varying environmental conditions. To achieve this, the research employs a generalized state space averaging technique to simulate a population of impending degradation trajectories for the capacitors. Environmental and degradation effects are modeled comprehensively. Frequency-based test features are derived from the gain, control, and impedance transfer functions of the filter and SMPS. These features are fitted with b-spline functionals for resampling and subsequently analyzed using functional principal component analysis to project the data onto the principal modes of variation. The extracted features serve as inputs to a fuzzy multi-task functional fusion predictor, which estimates the state of health at critical frequencies. The effectiveness of this model-based approach is validated through extensive experimentation, demonstrating its potential to significantly enhance the predictive maintenance strategies for SMPS with EMI filters.
Received: 01 May 2024, Revised: 04 July 2024, Accepted: 05 July 2024, Published Online: 26 July 2024
- S. Douzi, M. Tlig, J.B.H. Slama, 2015. “Experimental investigation on the evolution of a conducted-EMI buck converter after thermal aging tests of the MOSFET,” Microelectronics Reliability, 55(9-10), 1391-1394, 2015, doi:10.1016/j.microrel.2015.07.009.
- J. I. Corcau, L. Dinca, “Stability Studies of Power Systems for More Electric Aircraft,” in 2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), Sorrento, Italy, 861-864, 2022, 10.1109/SPEEDAM53979.2022.9842040.
- D. Nemashkalo, N. Moonen, F. Leferink, “Practical consideration on power line filter design and implementation,” 2020 International Symposium on Electromagnetic Compatibility – EMC EUROPE, Rome, Italy, 1-6, 2020, doi: 10.1109/EMCEUROPE48519.2020.9245777.
- R. Trois, G. Viscillo, G. F. Volpi, S.A. Pignari, “Accurate prediction of conducted emissions in switch-mode power supplies for space applications,” in 2020 International Symposium on Electromagnetic Compatibility – EMC EUROPE, Rome, Italy, 1-6, 2020, doi: 10.1109/EMCEUROPE48519.2020.9245814.
- L. Eliasson, “Aluminium electrolytic capacitor’s performance in Very High Ripple Current and Temperature Applications,” in CARTS Europe, 2007.
- D. Goodman, J. Hofmeister, J. Judkins, “Electronic prognostics for switched mode power supplies,” Microelectronics Reliability, 47(12), 1902-1906, 2007.
- R. F. Orsagh, D. W. Brown, P. W. Kalgren, C. S. Byington, A. J. Hess and T. Dabney, “Prognostic health management for avionic systems,” in 2006 IEEE Aerospace Conference, Big Sky, MT, USA, p. 7, 2006, doi: 10.1109/AERO.2006.1656086.
- C.S. Kulkarni, J.R. Celaya, K. Goebel, G. Biswas, “Physics based electrolytic capacitor degradation models for prognostic studies under thermal overstress.” in PHM Society European Conference, Vol.1, No. 1, 2012, doi:10.36001/phme.2012.v1i1.1423
- B. Sun, X. Fan, C.A. Yuan, C. Qian, G. Zhang, “A degradation model of aluminum electrolytic capacitors for LED drivers,” in 2015 16th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems, Budapest, Hungary, 1-4, 2015, doi:10.1109/EuroSimE.2015.7103124.
- M.M. Jovanović, “Power supply technology–past, present, and future,” in Power Conversion and Intelligent Motion China Conf. for Power Electronics (PCIM China) Shanghai, China, 3-15, 2007.
- Z. Wang, Conducted EMI Noise Prediction and Filter Design Optimization, Ph.D Dissertation, Virginia Tech, 2016.
- Z. Li, K.W. E. Cheng, J. Hu, “Modeling of basic DC-DC converters,” in 2017 7th International Conference on Power Electronics Systems and Applications – Smart Mobility, Power Transfer & Security (PESA), Hong Kong, China, 1-8, 2017, doi: 10.1109/PESA.2017.8277782.
- A. Ghosh, K. Mayank, State-space average modeling of dc-dc converters with parasitic in discontinuous conduction mode (dcm), Bachelor’s Thesis, National Institute of Technology, Rourkela, 2010.
- L. Sandrolini, A. Mariscotti, “Waveform and spectral characteristics of supraharmonic unsymmetrical conducted EMI of switched-mode power supplies,” Electronics, 11(4), p. 591, 2022, doi:10.3390/electronics11040591.
- A. Ismail, L. Saidi, M. Sayadi, M. Benbouzid, “A new data-driven approach for power IGBT remaining useful life estimation based on feature reduction technique and neural network,” Electronics, 9(10), p.1571, 2020, doi:10.3390/electronics9101571.
- A.G. EPCOS, “Aluminum electrolytic capacitors – general technical information’. White Paper, 2014.
- J. Gu, M. Pecht, “Prognostics and health management using physics-of-failure,” in 2008 Annual Reliability and Maintainability Symposium, Las Vegas, NV, USA, 481-487, 2008, doi: 10.1109/RAMS.2008.4925843.
- A.B. Kareem, J.W. Hur, “A feature engineering-assisted CM technology for SMPS output aluminium electrolytic capacitors (AEC) considering D-ESR-QZ parameters,” Processes, 10(6), p. 1091, 2022, doi: 10.3390/pr10061091.
- T. McGrew, V. Sysoeva, C.H. Cheng, C. Miller, J. Scofield, M. J. Scott, “Condition Monitoring of DC-Link Capacitors Using Time–Frequency Analysis and Machine Learning Classification of Conducted EMI,” IEEE Transactions on Power Electronics, 37(10), 12606-12618, 2022, doi: 10.1109/TPEL.2021.3135873.
- A. Altmann, B. Ng, “Joint Feature Extraction from Functional Connectivity Graphs with Multi-task Feature Learning,” in 2015 International Workshop on Pattern Recognition in NeuroImaging, Stanford, CA, USA, 29-32, 2015, doi: 10.1109/PRNI.2015.17
Citations by Dimensions
Citations by PlumX
Crossref Citations
- Tinofirei Museba Museba, Koenraad Vanhoof Vanhoof, "An Adaptive Heterogeneous Ensemble Learning Model for Credit Card Fraud Detection." Advances in Science, Technology and Engineering Systems Journal, vol. 9, no. 3, pp. 1, 2024.
No. of Downloads Per Month