基于遗传算法的电磁轨道炮能量效率优化研究  

Research on Optimization for Energy Efficiency of Electromagnetic Gun Based on Genetic Algorithm

作　　者：李天亮 李秋生 刘真[1] 刘雨满 LI Tianliang;LI Qiusheng;LIU Zhen;LIU Yuman(PLA 93221 Troops,Beijing 100085,China)

机构地区：[1]中国人民解放军93221部队,北京100085

出　　处：《现代防御技术》2024年第4期146-153,共8页Modern Defence Technology

摘　　要：针对易损性不同的空袭目标“订制”不同能量的拦截弹丸是电磁轨道炮的重要技术优势,针对弹丸特定预期炮口速度,轨道炮电源端不同的电压、激励电流、轨道不同尺寸等参数构成了存在较多可行解的解空间,自然存在最优解问题。以弹丸炮口速度、系统能量效率最优为目标,设计了4个逐次递进的多目标优化问题,采用非支配排序遗传算法(NSGA-Ⅱ),将求解空间逐步拓展至弹丸质量、轨道尺寸、电源电容、电压,特别是放电时序等参数,通过对轨道端、电源端的参数空间寻优,求出系统帕累托最优解,基于最优解对轨道炮的系统效率和各影响因素进行了研究,并给出了分析结论。Electromagnetic gun can customize appropriate projectile according to the vulnerability of individual target.For an aim velocity of projectile,different voltage,current,and dimension of rails,which formed solution space with multiple feasible ones,and the optimal solution should be found.Based on non-dominated sorting genetic algorithm-II(NSGA-Ⅱ),taking the muzzle velocity and energy efficiency as the goal,four multi objective optimization problems are proposed,in which projectile mass,dimension of rails,capacitance,voltage and current of electric power,are involved progressively.Based on Pareto optimal solution that solved with NSGA-Ⅱ,the main influence factors were analyzed,and some useful conclusions were drawn.

关 键 词：电磁轨道炮 能量效率 解空间 帕累托优化 遗传算法 

分 类 号：TJ301[兵器科学与技术—火炮、自动武器与弹药工程] TP391.9[自动化与计算机技术—计算机应用技术]