Online ESR monitoring and parasitic inductance self-correction for DC-link capacitors via multi-frequency ripple in-situ identification

Purpose This study aims to achieve accurate online monitoring of a DC-link capacitor’s equivalent series resistance (ESR) by overcoming the undesired coupling between the ESR and the parasitic inductance in the measurement path, thereby eliminating the reliance on offline characterization. Design/methodology/approach A self-calibrating technique is proposed that decouples these parameters in situ by leveraging the intrinsic dual-frequency ripple (twice the line frequency and the switching frequency) present on the DC bus as a natural excitation source. An overdetermined system model incorporating both ESR and parasitic inductance as unknown variables is established and solved via a recursive least squares algorithm. A standardized temperature normalization is further implemented to provide a high-fidelity health indicator. Findings Experimental validation on a 1.5-kW SiC inverter demonstrates that the proposed method accurately identifies the parasitic inductance and maintains the final ESR estimation error within ±5% across a wide range of load and temperature conditions (−10°C to 85°C). The results confirm the superior accuracy and robustness of the in situ multi-parameter identification approach. Originality/value This paper presents a novel approach that shifts the monitoring paradigm from simple impedance calculation to an in situ multi-parameter identification framework. By providing a self-calibrating capability without auxiliary hardware, the method enhances the reliability and maintenance efficiency of power electronic converters.