基于遗传算法的分段多参气动阻力研究  

Research on piecewise multi-parameter aerodynamic resistance based on genetic algorithm

作　　者：温瑞英[1] 李璐 魏志强[1] WENRuiying;LI Lu;WEI Zhiqiang(College of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China)

机构地区：[1]中国民航大学空中交通管理学院,天津300300

出　　处：《飞行力学》2021年第2期27-32,44,共7页Flight Dynamics

基　　金：民航联合研究基金资助(U1833103)。

摘　　要：针对BADA模型未考虑马赫数、仅基于升力系数求得的阻力系数与真实值存在较大误差的问题,考虑到飞机以较大马赫数飞行时气流压缩效应会改变阻力特性,提出了一种基于遗传算法的临界马赫数分段多参数数据拟合方法,建立了更为精确的阻力系数数学模型。以B737-800民机为算例的计算结果表明:该模型计算的阻力系数与真实值的平均相对误差小于5%,与经典BADA模型相比,平均相对误差下降了15.63%,均方根误差下降了0.384%,拟合优度提升了0.344;所提优化方法提高了阻力计算的精确度,可提高ATM飞行仿真的准确性。BADA obtained the drag coefficient based on the lift coefficient without considering Mach number. It does have large error between real values. For this problem, considering air compression effect will change resistance polarity if the plane flies at higher Mach number, this paper proposed a method of critical Mach number piecewise multi-parameter data fitting based on genetic algorithm. A more accurate mathematical model of the drag coefficient was established. Taking B737-800 civil aircraft as an example, the calculation results show that the average relative error between the calculated drag coefficient and the real value is less than 5%. Compared with the traditional BADA model, the average relative error decreases by 15.63%, the root mean square error decreases by 0.384% and the goodness of fit increases by 0.344. This optimization method improves the accuracy of drag calculation and ATM flight simulation.

关 键 词：极曲线 BADA模型 遗传算法 临界马赫数 

分 类 号：V212.1[航空宇航科学与技术—航空宇航推进理论与工程]