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Failure Prediction Model and ESR Modeling of Electrolytic Capacitor With Application to Predictive Maintenance

[+] Author Affiliations
Hadi Malek, Sara Dadras

Utah State University, Logan, UT

YangQuan Chen

University of California - Merced, Merced, CA

Paper No. DETC2015-46175, pp. V009T07A016; 6 pages
doi:10.1115/DETC2015-46175
From:
  • ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 9: 2015 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications
  • Boston, Massachusetts, USA, August 2–5, 2015
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5719-9
  • Copyright © 2015 by ASME

abstract

Being one of the most used passive components in power electronics, electrolytic capacitors have the shortest life span due to their wear-out failure which is mainly caused by vaporization and deterioration of capacitor electrolyte. Knowing these two phenomena increase Equivalent Series Resistance (ESR) of the capacitor, tracking ESR value over the system operating time can be a good indicator for state of health of an electrolytic capacitor. In order to set the maintenance schedule, various ESR monitoring algorithms computing remaining time before failure have been investigated in literature. These real-time algorithms use classical models for ESR and life-time estimation which are not precise enough and leads the maintenance program to be either risky if the prediction is more than the actual life-time or more expensive if it is much less than the actual life span.

This paper presents a generalized equivalent model using fractional order element for electrolytic capacitor to estimate the ESR and impedance of faultless running capacitor. Unlike other existing fractional order models, proposed model considers a fractional order dynamic only in the dielectric losses and the terminal capacitor remains integer order as observed in actual capacitor’s behavior.

Furthermore, a novel failure predictive model using Mittage-Leffler function is proposed to track the ESR increment due to aging of the capacitor and estimate the failure time based on the information which are provided through ESR monitoring system. Using this model increase the life-time prediction accuracy. Hence the predictive maintenance of the system with capacitors nearing their failure time can be set more precisely. These two fractional order models are compared against classical ESR and life-time prediction models to illustrate the enhanced performances of the proposed models.

Copyright © 2015 by ASME

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