替代模型
推进
多转子
计算机科学
控制工程
执行机构
航程(航空)
空气动力学
灵敏度(控制系统)
系统工程
工程类
航空航天工程
人工智能
电子工程
机器学习
作者
Francesco De Giorgi,Marc Budinger,Ion Hazyuk,Aurélien Reysset,Florian Sanchez
出处
期刊:AIAA Journal
[American Institute of Aeronautics and Astronautics]
日期:2021-04-14
卷期号:59 (7): 2490-2502
被引量:8
摘要
This paper presents a new methodology for obtaining surrogate models suitable for the preliminary design of aircraft application systems. The methodology is based on a dimensional and sensitivity analysis adapted to the needs and constraints arising from multidisciplinary design. It enables simpler and lighter models to be obtained, with satisfactory predictive accuracy over a large range of validity. These surrogate models can cover a very large area of applications, where the components may vary from very small to very large sizes, because of their broad range of validity. Avoiding the reconstruction of the model offers advantages in terms of capitalization and justifying the concept of reuse. The proposed approach is applied to generate surrogate models of a permanent magnet brushless motor used in two types of applications: one is for the preliminary design of a flight control electromechanical actuator and the other is for the preliminary design of an electric propulsion system for a multirotor drone.
科研通智能强力驱动
Strongly Powered by AbleSci AI