在翼航空发动机性能数字孪生建模方法  

Digital twin modeling method for on-wing aero-engine performance

作　　者：李春华 宁顺刚 杨彩琼 孙见忠[1] LI Chunhua;NING Shungang;YANG Caiqiong;SUN Jianzhong(College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China;The 28th Research Institute of China Electronics Technology Group Corporation,Nanjing 210007,China;AECC Sichuan Gas Turbine Research Institute,Mianyang 621700,China)

机构地区：[1]南京航空航天大学民航学院,南京211106 [2]中国电子科技集团第二十八研究所,南京210007 [3]中国航发四川燃气涡轮研究院,四川绵阳621700

出　　处：《兵器装备工程学报》2023年第6期204-212,共9页Journal of Ordnance Equipment Engineering

基　　金：国家自然科学基金项目(52072176)。

摘　　要：由于在翼发动机的运行环境和使用条件多变,发动机多运行在非设计状态,基于试车数据的稳态性能模型难以反映发动机运行的真实状况,鉴于此,提出了基于发动机在翼状态数据的性能模型修正方法,通过循环迭代计算的设计点性能匹配和特性图缩放和特性图参数寻优的非设计点性能匹配,借助GasTurb软件构建了某型CFM56-7B发动机在翼性能数字孪生模型,模型全工况多参数预测误差小于2.67%,验证了该方法的有效性和实用性。Due to the changeable operating environment and service conditions,on-wing engines often run in an undesigned state,and a steady-state performance model based on test data cannot reflect the true state of engine operation.In view of this,this paper proposes a performance model correction method based on QAR data.Through design point performance matching of cyclic iterative calculation and non-design point performance matching of characteristic map scaling and characteristic map parameter optimization,an on-wing performance digital twin model of a certain type of CFM56-7B engine is constructed with the help of GasTurb software.The multi-parameter prediction error of the model is less than 2.67%,which verifies the effectiveness and practicability of the method.

关 键 词：性能数字孪生 在翼发动机 GasTurb 特性图缩放 QAR数据 

分 类 号：TH212[机械工程—机械制造及自动化] TH213.3