Abstract: Due to the complexity of the modular multilevel converter based high voltage direct current (MMC-HVDC) grids, it is difficult to build an accurate analytical model for analysis of direct fault currents. In this paper, an analytical method based on central composite design(CCD) is proposed to quantitatively analyze and evaluate the comprehensive influence of main circuit parameters on DC short-circuit fault current (DSCFC). By the proposed method, the multi-factor regression equation is obtained with as few simulations experimental data as possible to realize quantitative analysis and evaluation of the comprehensive influence of multi-factors on DSCFC. Taking the four-terminal DC grid as an example, multi-factor simulation experiments are designed to analyze the influence of the four main circuit parameters including DC inductance, bridge arm inductance, neutral line inductance, and ground resistance on DSCFC. The statistical method is used to analyze and evaluate the main effects and interaction effects of each factor on the peak value of the DSCFC. The analysis results show that among the four main circuit parameters, the DC inductance has the strongest influence on the peak value of fault current within 6 ms after the faults, the neutral inductance has the strongest influence on the peak value of bridge arm fault current within 6 ms after faults, and the interactions between main circuit parameters are weak and can be ignored. The analysis results can provide a theoretical basis for the research of fault current suppression and the comprehensive optimization of multi-component parameters in the case of short-circuit fault in DC grid.