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.