Optimal rail parameter design of series-connected augmented railgun based on genetic algorithm

Rail size parameters are important factors affecting the muzzle velocity and energy utilization efficiency of the series-connected augmented railgun (SAR). In order to find the optimal configuration under certain constraints and get the maximum velocity and maximum energy efficiency, based on the basic theory of circuit, the circuit model and the dynamics model which considered circuit switching and varying load were established. By using Simulink software, the process of circuit discharging and armature launch were simulated. To get the goal of maximum velocity and maximum energy efficiency, multi-objective genetic algorithm was used to optimize the size parameters of the rail. The results show the optimized muzzle velocity and energy efficiency were significantly increased. The research can provide a reference for the design of series-connected augmented railgun.