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In the power supply of urban rail transit system, electrolytic capacitors are used in large numbers. They suffer from inevitable ripple currents; such ripple currents generate heat dissipation, which shortens their service life seriously. To increase the reliability of the whole power supply system, the aging process of electrolytic capacitors must be evaluated, so that their service life could be predicted and measures could be taken in advance before their failures. When they are applied into the power supply system, the accuracy of conventional approaches is somewhat lowered, owing to the existence of unpredictable ripple current and ambient temperature variations. In this paper, we build an analytical ripple model to offer online aging monitoring of electrolytic capacitors. After that, a GM(2,1) model is adopted to predict service life with higher accuracy than conventional approaches.

Service Life Prediction of Electrolytic Capacitors in Urban Rail Transit Based on Analytical Iteration and GM(2,1) Model