A digital twin based reliability assessment of Superbuck converters

Abstract Addressing the challenge of assessing the reliability of ‘long-life, high-reliability’ DC/DC analog converters in submarine observation networks and space power systems, which have limited internal observation points and insufficient valid information, and initial assessment rendered unreliable with the long-term operation of the converter. This paper proposes a novel method based on digital twin (DT) technology. The method eliminates the need for measuring internal variables, and only requires the measurement of the converter’s ripple peak-to-peak. A digital twin (DT) is constructed based on the underlying mechanism, and the parameters of the operating converter are identified through the collection of ripple peak-to-peak, which are then injected into the DT for dynamic tracking of the physical entity. By obtaining internal current and voltage of the DT and utilizing the Markov model, the reliability of the converter can be assessed. This method offers real-time reliability assessment without the need for additional measurement points. To validate the effectiveness of the proposed approach, a Superbuck converter is used as an example to demonstrate the high-fidelity of the DT through isomorphic single-sample repeatability and isomorphic multiple-sample consistency experiments.