A technique for conducting online estimation of the intrinsic parameters of encapsulated three-phase harmonic filter capacitors is presented. The concept is based on firstly sampling the line voltage and current associated with the encapsulated capacitor, then formulating a capacitor current estimator to estimate the line currents with the sampled line voltages, and finally using the errors of the estimated and actual line currents to estimate the intrinsic parameters with a modified particle swarm optimization algorithm. A decoupled technique is formulated to estimate the unmeasurable circulating current in the encapsulated capacitor with the measured line voltages. A prototype for estimating the intrinsic parameters of an encapsulated three-phase capacitor in the harmonic filter for an adjustable speed drive for a 1.1kW motor-generator set has been built and evaluated. To facilitate the application of the proposed technology for Internet-of-Things (IoT) devices, the impact of different durations, sampling frequencies, and data lengths on the estimation accuracy is evaluated. The results are favorably compared with the theoretical predictions and the measurement results obtained on a calibrated network analyzer. In addition, the performance of the proposed technique is favorably compared with the Trust-Region-Reflective Least Squares Method.
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