Armature Velocity Control Strategy and System Efficiency Optimization of Railguns

作者：Chang, Xinyue; Yu, Xinjie^*; Liu, Xukun; Li, Zhen

来源：IEEE Transactions on Plasma Science, 2018, 46(10): 3634-3639.

DOI：10.1109/TPS.2018.2844292

• Capacitive pulsed power supply
• genetic algorithm (GA) optimization
• railguns
• system efficiency
• trigger
• strategy
• velocity control

This paper at first proposes a method to calculate a trigger strategy before launching in order to control the muzzle velocity of railguns. Five triggering points are set equidistantly and six pulsed forming unit (PFU) groups are triggered in total. First, given a desired muzzle velocity, the expected uniformly accelerated rectilinear motion of the armature is calculated. Second, the module number of each PFU group is obtained according to the principle of minimizing the absolute relative error between the actual and the expected velocity at each triggering point. The results show that, when the desired muzzle velocity is within [1500, 2000] m/s, the absolute muzzle velocity relative error delta is less than 0.5%. In order to achieve a better control performance, the places of the five triggering points are then optimized by a genetic algorithm (GA). The objective function is the sum of absolute delta, when the desired muzzle velocities are 1500, 1600, ..., 2000 m/s. After the optimization, delta is reduced to less than 0.05%. At last, based on this velocity control method, the railgun system is optimized to pursue the highest system efficiency eta by GA. The independent variables are the armature mass, the precharged voltage, and the places of the five triggering points. The constraints are that the desired muzzle velocity is 1800 m/s and the absolute delta is within 1%. The results show that eta increases from 6.57% to 25.37%.

• 出版日期2018-10
• 单位清华大学