Parameter identification of dc black‐box arc model using non‐linear least squares

Abstract

The black-box arc model is known to be a useful technique to simulate dynamic arc-circuit interaction by reflecting arc characteristics. Existing researches have shown that the black-box model has been widely used to analyse the ac arc characteristics of SF6 and air circuit breakers. Due to the enormous energy and steep rise rate (di/dt) during dc fault, it is important to consider dc arc characteristics. However, there are no examples of black-box models for dc circuit breakers utilised in railway systems and dc microgrid. In this study, the applicability of the black-box model, which was applied to the existing ac arc analysis, was verified for the dc arc analysis. Black-box modelling is applied to datasheet of industrial low-voltage circuit breakers and parametric sweep method was used to select Schwarz model parameters considering the tendency of dc arc current waveform for the dc pole-to-pole fault. The authors also applied the Levenberg–Marquardt algorithm, which is the most extensively used for the optimisation of functional parameters, to the Schwarz model for accurate and reliable arc modelling. As a result, the dc arc feasibility of the black-box model was analysed through simulation results, and a model optimisation technique was proposed.