Objective. Event-related potentials (ERPs) evoked by visual stimulations comprise several components, with different amplitudes and latencies. Among them, the N2 and N2pc components have been demonstrated to be a measure of subjects’ allocation of visual attention to possible targets and to be involved in the suppression of irrelevant items. Unfortunately, the N2 and N2pc components have smaller amplitudes compared with those of the background electroencephalogram (EEG), and their measurement requires employing techniques such as conventional averaging, which in turn necessitates several sweeps to provide acceptable estimates. In visual search studies, the number of sweeps (Nswp) used to extrapolate reliable estimates of N2/N2pc components has always been somehow arbitrary, with studies using 50–500 sweeps. In-silico studies relying on synthetic data providing a close-to-realistic fit to the variability of the visual N2 component and background EEG signals are therefore needed to go beyond arbitrary choices in this context. Approach. In the present work, we sought to take a step in this direction by developing a simulator of ERP variations in the N2 time range based on real experimental data while monitoring variations in the estimation accuracy of N2/N2pc components as a function of two factors, i.e. signal-to-noise ratio (SNR) and number of averaged sweeps. Main results. The results revealed that both Nswp and SNR had a strong impact on the accuracy of N2/N2pc estimates. Critically, the present simulation showed that, for a given level of SNR, a non-arbitrary Nswp could be parametrically determined, after which no additional significant improvements in noise suppression and N2/N2pc accuracy estimation were observed. Significance. The present simulator is thought to provide investigators with quantitative guidelines for designing experimental protocols aimed at improving the detection accuracy of N2/N2pc components. The parameters of the simulator can be tuned, adapted, or integrated to fit other ERP modulations.