A novel method for on-board propulsion system modelling under supersonic state
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摘要: 为了满足机载航空推进系统模型对精度、实时性及数据存储量的苛刻要求,提出了一种机载模型建模方法.对传统的机载稳态模型建立过程中使用的相似准则进行了充分讨论,得出了一种具备更高建模精度的相似准则.在新的相似准则基础上,建立了包含泰勒展开式中非线性2阶项的高精度稳态变量模型,有效解决了分段线性稳态变量模型在大包线、变状态条件下精度难以保证的问题;为了解决超声速状态下安装推力与发动机净推力差别较大的问题,建立了考虑外流特性的简化进气道模型,给出了一种计算安装推力的方法,即由简化发动机模型计算安装推力中符合相似准则的部分,由进气道模型计算溢流阻力、放气阻力及发动机推力中不符合相似准则的部分.仿真结果表明:基于新的相似准则所建立的机载模型具有大包线、变状态适应性,输出参数误差均在0.5%以内.Abstract: In order to meet the high requirements of precision, timeliness and data storage of on-board aero propulsion model, a new method of onboard modeling was proposed. The similarity criterions used in traditional on-board steady-state model were deeply discussed, and a similarity criterion with higher modeling accuracy was obtained. Based on the new similarity criterion, a high precision steady state variable model was established, which includes the nonlinear 2 order term in the Taylor expansion, and the inaccuracy problem of the traditional piece-wise linear method in the condition of large flight envelope and variable state was solved effectively. In order to solve the problem of the prominent difference between engine installed thrust and net thrust under supersonic state, the simplified inlet model considering the outflow characteristics is established, and a method is given to calculate the installed thrust, the part of the installed thrust compatible with the similarity criterion was computed by the above simplified engine model, while the spilled air fluid resistance, the deflation resistance and some part of engine net thrust incompatible with the similarity criterion were calculated by the simplified inlet model. The simulation results show that the error of the on-board propulsion system model based on the new similarity criterion has the advantages of large flight envelope and variable state adaptability, and the error of output parameters are within 0.5%.
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[1] Gilyard G B,Orme J S.Performance-seeking control:program overview and future directions[R].AIAA 93-3765-CP,1993. [2] Gilyard G B,Orme J S.Subsonic flight test evaluation of a performance seeking control algorithm on an F-15 airplane[R].AIAA 92-3743,1992. [3] Garg S.NASA glenn research in controls and diagnostics for intelligent aerospace propulsion systems[R].NASA/TM-2005-214036,2005. [4] Litt J S,Simon D L,Garg S,et al.A survey of intelligent control and health management technologies for aircraft propulsion systems[R].NASA/TM-2005-213622,2005. [5] Garg S.aircraft turbine engine control research at NASA Glenn Research Center[R].NASA/TM-2013-217821,2013. [6] 尹大伟.航空发动机模型求解算法及性能寻优控制中的参数估计研究[D].长沙:国防科学技术大学,2011.YIN Dawei.Algorithms for solving aeroengine nonlinear mathematical model and parameter estimation in performance-seeking control\[D\].Changsha:National University of Defense Technology,2011.(in Chinese) [7] 王海泉,欧阳玲,黄杰.涡扇发动机机载自适应模型及其性能蜕化估计[J].计算机仿真,2012,29(10):76-80.WANG Haiquan,OUYANG Ling,HUANG Jie.Research on airborne real-time adaptive model of aero-engine and performance degenerate estimate[J].Computer Simulation,2012,29(10):76-80.(in Chinese) [8] 鲁峰,黄金泉,吕怡秋,等.基于非线性自适应滤波的发动机气路部件健康诊断方法[J].航空学报,2013,34(11):2529-2538.LU Feng,HUANG Jinquan,L Yiqiu,et al.Aircraft engine gas-path componets health diagnosis based on nonlinear adaptive filters[J].Acta Aeronautics et Astronautica Sinica,2013,34(11):2529-2538.(in Chinese) [9] 鲁峰,黄金泉,陈煜.航空发动机部件性能故障融合诊断方法研究[J].航空动力学报,2009,24(7):1649-1653.LU Feng,HUANG Jinquan,CHEN Yi.Research on performance fault fusion diagnosis of aero-engine component[J].Journal of Aerospace Power,2009,24(7):1649-1653.(in Chinese) [10] 王芳,樊思齐.MAPS方法在航空发动机性能寻优控制中的作用[J].航空动力学报,2005,20(3):503-507.WANG Fang,FAN Siqi.Study of methods fot turbofan engine performance seeking control[J].Journal of Aerospace Power,2005,20(3):503-507.(in Chinese) [11] 朱玉斌,樊思齐,李华聪,等.航空发动机性能寻优控制混合优化算法[J].航空动力学报,2006,21(2):422-426ZHU Yubin,FAN Siqi,LI Huachong,et al.Research of hybrid optimization method for aeroengine performance seeking control[J].Journal of Aerospace Power,2006,21(2):422-426.(in Chinese) [12] 刘小勇,樊思齐.采用BP网络辨识航空发动机数学模型[J].航空动力学报,1996,11(2):153-156.LIU Xiaoyong,FAN Siqi.A use of BP network to identify aero-engine mathematical model[J].Journal of Aerospace Power,1996,11(2):153-156.(in Chinese) [13] 丁凯峰,樊思齐.基于RBF网络的航空发动机辨识模型[J].航空动力学报,2000,15(3):205-208.DING Kaifeng,FAN Siqi.Aero-engine identification model based on RBF network l[J].Journal of Aerospace Power,2000,15(3):205-208.(in Chinese) [14] ZHAO Yongping,SUN Jianguo.Fast online approximation for hard support vector regression and its application to analytical redundancy for aeroengines[J].Chinese Journal of Aeronautics,2010,23(2):145-152. [15] ZHAO Yongping,SUN Jianguo.A fast method to approximately train hard support vector regression[J].Neural Networks,2010,23(10):1276-1285. [16] 王健康.航空发动机模型基优化控制技术研究[D].南京:南京航空航天大学,2013.WANG Jiankang.Research on model-based optimal control for aero-engines\[D\].Nanjing:Nanjing University of Aeronautics and Astronautics,2013.(in Chinese) [17] Smith R H,Chisholm J D,Stewart J F,et al.Optimizing aircraft performance with adaptive,integrated flight/propusion control[J].Journal of Engineering for Gas Turbines and Power,1991,113(1):88-94. [18] Powers S G.An electronic workshop on the performance seeking control and propulsion controlled aircraft results of the F-15 highly integrated digital electronic control flight research program[R].NASA TM-104278,1995. [19] 廉筱纯,吴虎.航空发动机原理[M].西安:西北工业大学出版社,2005. [20] 聂恰耶夫Ю Н.航空动力装置控制规律与特性[M].单凤桐,译.北京:国防工业出版社,1999. [21] 王琴芳.航空燃气涡轮发动机原理[M].南京:南京航空航天大学出版社,2010. [22] Ball W H.Rapid evaluation of propulsion system effects[R].Technical Report AFFDL-TR 78-91,19. [23] 孙丰勇,张海波,叶志峰.超声速进气道/发动机一体化控制[J].航空动力学报,2014,29(10):2279-2287.SUN Fengyong,ZHANG Haibo,YE Zhifeng.Study of integrated performance for supersonic inlet/engine[J].Journal of Aerospace Power,2014,29(10):2279-2287.(in Chinese)
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