Due to the complexity and randomness of a series fault arc in a low-voltage distribution system, it would be a great challenge to accurately describe the full-wave arcing process through a concise mathematical form. To address this issue, a circuit characteristic arc model of based on the asymmetric arcing (AA-CCAM) of low-voltage series arc fault is proposed. Firstly, the asymmetric arcing process is exactly depicted using field characteristic description, and then the AA-CCAM is constructed based on reasonable assumptions and field-path evolution. Afterwards, a time-domain difference method is adopted to implement the partitioned iterative computation of the model. More specially, the problem of solving model parameters is transformed into a single objective optimization problem, which applies the competitive particle swarm algorithm. Finally, a low-voltage series arc fault experimental platform is established for model validation. Based on the training set, reference parameter values are determined through stable distribution fitting. Test results demonstrate that the simulated fault waveforms achieve an overall fitting accuracy of 97.26%, thereby validating the model’s effectiveness under resistive load conditions.