Longitudinal Aerodynamic Parameter Identification for Blended-Wing-Body Aircraft Based on a Wind Tunnel Virtual Flight Test
The wind tunnel virtual flight test realizes the dynamic semi-free flight of the model in the wind tunnel through the deflections of the control surface and uses the test data to identify the aerodynamic derivatives. The difference in dynamics between the wind tunnel virtual flight and the free flig...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
|
| Series: | Aerospace |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2226-4310/9/11/689 |
| _version_ | 1797469526336471040 |
|---|---|
| author | Lixin Wang Shang Tai Ting Yue Hailiang Liu Yanling Wang Chen Bu |
| author_facet | Lixin Wang Shang Tai Ting Yue Hailiang Liu Yanling Wang Chen Bu |
| author_sort | Lixin Wang |
| collection | DOAJ |
| description | The wind tunnel virtual flight test realizes the dynamic semi-free flight of the model in the wind tunnel through the deflections of the control surface and uses the test data to identify the aerodynamic derivatives. The difference in dynamics between the wind tunnel virtual flight and the free flight leads to discrepancies between the identification and theoretical results. To solve the problems, a step-by-step identification and correction method for aerodynamic derivatives is established based on the difference between the equations of motion of wind tunnel virtual flight and free flight to identify and correct the lift, drag derivatives, pitch moment derivatives, and velocity derivatives, respectively. To establish an aerodynamic parameter identification model, the flight dynamics equation is expressed as a decoupled form of the free flight force and the influence of the test support frame force on the model’s motions through linearization. To ensure the identification accuracy of each aerodynamic derivative, an excitation signal design method based on amplitude–frequency characteristic analysis is proposed. The longitudinal aerodynamic parameter identification results of a blended-wing-body aircraft show that identification results with higher accuracy can be obtained by adopting the proposed identification and correction method. |
| first_indexed | 2024-03-09T19:21:40Z |
| format | Article |
| id | doaj.art-1a64000c5d884411a88b1cb3ea3cc150 |
| institution | Directory Open Access Journal |
| issn | 2226-4310 |
| language | English |
| last_indexed | 2024-03-09T19:21:40Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Aerospace |
| spelling | doaj.art-1a64000c5d884411a88b1cb3ea3cc1502023-11-24T03:15:52ZengMDPI AGAerospace2226-43102022-11-0191168910.3390/aerospace9110689Longitudinal Aerodynamic Parameter Identification for Blended-Wing-Body Aircraft Based on a Wind Tunnel Virtual Flight TestLixin Wang0Shang Tai1Ting Yue2Hailiang Liu3Yanling Wang4Chen Bu5School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, ChinaSchool of Aeronautic Science and Engineering, Beihang University, Beijing 100191, ChinaSchool of Aeronautic Science and Engineering, Beihang University, Beijing 100191, ChinaSchool of Aeronautic Science and Engineering, Beihang University, Beijing 100191, ChinaAVIC Aerodynamics Research Institute, Harbin 150001, ChinaAVIC Aerodynamics Research Institute, Harbin 150001, ChinaThe wind tunnel virtual flight test realizes the dynamic semi-free flight of the model in the wind tunnel through the deflections of the control surface and uses the test data to identify the aerodynamic derivatives. The difference in dynamics between the wind tunnel virtual flight and the free flight leads to discrepancies between the identification and theoretical results. To solve the problems, a step-by-step identification and correction method for aerodynamic derivatives is established based on the difference between the equations of motion of wind tunnel virtual flight and free flight to identify and correct the lift, drag derivatives, pitch moment derivatives, and velocity derivatives, respectively. To establish an aerodynamic parameter identification model, the flight dynamics equation is expressed as a decoupled form of the free flight force and the influence of the test support frame force on the model’s motions through linearization. To ensure the identification accuracy of each aerodynamic derivative, an excitation signal design method based on amplitude–frequency characteristic analysis is proposed. The longitudinal aerodynamic parameter identification results of a blended-wing-body aircraft show that identification results with higher accuracy can be obtained by adopting the proposed identification and correction method.https://www.mdpi.com/2226-4310/9/11/689wind tunnel virtual flight testparameter identificationleast-squares methodmaximum likelihood estimationblended-wing-body |
| spellingShingle | Lixin Wang Shang Tai Ting Yue Hailiang Liu Yanling Wang Chen Bu Longitudinal Aerodynamic Parameter Identification for Blended-Wing-Body Aircraft Based on a Wind Tunnel Virtual Flight Test Aerospace wind tunnel virtual flight test parameter identification least-squares method maximum likelihood estimation blended-wing-body |
| title | Longitudinal Aerodynamic Parameter Identification for Blended-Wing-Body Aircraft Based on a Wind Tunnel Virtual Flight Test |
| title_full | Longitudinal Aerodynamic Parameter Identification for Blended-Wing-Body Aircraft Based on a Wind Tunnel Virtual Flight Test |
| title_fullStr | Longitudinal Aerodynamic Parameter Identification for Blended-Wing-Body Aircraft Based on a Wind Tunnel Virtual Flight Test |
| title_full_unstemmed | Longitudinal Aerodynamic Parameter Identification for Blended-Wing-Body Aircraft Based on a Wind Tunnel Virtual Flight Test |
| title_short | Longitudinal Aerodynamic Parameter Identification for Blended-Wing-Body Aircraft Based on a Wind Tunnel Virtual Flight Test |
| title_sort | longitudinal aerodynamic parameter identification for blended wing body aircraft based on a wind tunnel virtual flight test |
| topic | wind tunnel virtual flight test parameter identification least-squares method maximum likelihood estimation blended-wing-body |
| url | https://www.mdpi.com/2226-4310/9/11/689 |
| work_keys_str_mv | AT lixinwang longitudinalaerodynamicparameteridentificationforblendedwingbodyaircraftbasedonawindtunnelvirtualflighttest AT shangtai longitudinalaerodynamicparameteridentificationforblendedwingbodyaircraftbasedonawindtunnelvirtualflighttest AT tingyue longitudinalaerodynamicparameteridentificationforblendedwingbodyaircraftbasedonawindtunnelvirtualflighttest AT hailiangliu longitudinalaerodynamicparameteridentificationforblendedwingbodyaircraftbasedonawindtunnelvirtualflighttest AT yanlingwang longitudinalaerodynamicparameteridentificationforblendedwingbodyaircraftbasedonawindtunnelvirtualflighttest AT chenbu longitudinalaerodynamicparameteridentificationforblendedwingbodyaircraftbasedonawindtunnelvirtualflighttest |