Fractional order equivalent series resistance modelling of electrolytic capacitor and fractional order failure prediction with application to predictive maintenance

• Published in: IET power electronics Vol. 9; no. 8; pp. 1608 - 1613
• Main Authors: Malek, Hadi, Dadras, Sara, Chen, Yangquan
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 29.06.2016
• Subjects: Algorithms; Capacitors; electrolytic capacitor; Electrolytic capacitors; Electronics; Equivalence; Failure; fractional order element; fractional order equivalent series resistance modelling; fractional order failure prediction; Maintenance; Mathematical models; Mittag‐Leffler function; power electronics; Predictive maintenance; fractional order equivalent series resistance modelling; electrolytic capacitor; predictive maintenance; Mittag-Leffler function; fractional order failure prediction; electrolytic capacitors; power electronics; fractional order element
• ISSN: 1755-4535; 1755-4543; 1755-4543
• DOI: 10.1049/iet-pel.2015.0636

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 vaporisation 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. To set the maintenance schedule, various ESR monitoring algorithms have been investigated in literature. These classical real-time algorithms lead the maintenance program to be either risky if the prediction is longer than the actual life-time or more expensive if it is shorter than the actual life span. This study presents a generalised equivalent model using fractional order (FO) element for electrolytic capacitor to estimate the ESR and impedance of faultless running capacitor. Furthermore, a novel failure predictive model using Mittag-Leffler function is proposed to track the ESR increment and estimate the failure time. Hence, the predictive maintenance of the system with capacitors nearing their failure time can be set more precisely. These two FO models are compared against classical ESR and life-time prediction models to illustrate the enhanced performances of the proposed models.