| Title |
A Study on the Diagnostics of Capacitor Degradation in Switching DC-DC Converters |
| DOI |
http://doi.org/10.5207/JIEIE.2023.37.3.077 |
| Keywords |
Capacitor; DC-DC converter; Degradation; Estimation of capacitance; Neural-Network fitting |
| Abstract |
As the DC grid continues to expand, the significance of switching type DC-DC power converters is growing. These power converters commonly employ aluminum electrolytic capacitors for DC output, which are prone to failure and deterioration. Therefore, this paper introduces a novel capacitance estimation method designed to diagnose the degradation of aluminum electrolytic capacitors used for voltage regulation in switching DC-DC converters. The proposed method utilizes the measured inductor current and output voltage, employing a Discrete Fourier Transformation (DFT) based on the PWM switching frequency. The harmonic data obtained is then employed to estimate the capacitance change of the capacitor using an artificial neural network fitting algorithm. To validate the performance of the proposed method, it was implemented in Buck converter, and the capacitance estimation accuracy was assessed using Matlab. |