Wing aerodynamic configuration optimization method oriented to conceptual design stage

Abstract

The invention relates to a conceptual design stage-oriented aerodynamic configuration optimization method of a wing, and belongs to the technical field of aircraft design. According to the conceptual design stage-oriented aerodynamic configuration optimization method of the wing, decoupling optimization is carried out on the bending thickness of the wing, the two-dimensional and three-dimensional coupling effect can be considered in the wing optimization process, the design space dimension is effectively reduced, and optimization of induced resistance and zero lift resistance is considered; a reasonable decoupling design and a rapid aerodynamic force calculation method are adopted, the method is suitable for new concept aircraft design, and both the optimization speed and precision are considered; according to the method, decoupling optimization is carried out on the bending degree and the thickness of the wing profile based on the thin wing theory, the middle cambered surface of the wing is optimized firstly, then the thickness distribution of the key section wing profile is optimized, and the high-dimensional optimization problem is converted into a plurality of low-dimensional optimization problems, so that the effects of reducing the design space dimension and accelerating the solving speed are achieved.

Description

Technical Field

[0001] The invention relates to the technical field of aircraft design, and in particular to a wing aerodynamic shape optimization method oriented to a conceptual design stage. Background Art

[0002] At present, most of the methods for optimizing the aerodynamic shape of wings follow the idea of ​​optimizing the two-dimensional airfoil first and then optimizing the three-dimensional wing, so as to reduce design variables and improve optimization efficiency. Some studies also consider that the three-dimensional effect of the wing will cause the originally excellent airfoil to fail to achieve the expected effect, and directly study the complete three-dimensional wing, while optimizing the wing geometric parameters and airfoil parameters as design variables. However, this method will make the design space dimension larger, sacrificing some optimization efficiency and ensuring optimization quality. Some studies also use free deformation technology (FFD) to directly use the FFD control points of the aerodynamic shape as optimization variables to optimize the design of the complete three-dimensional wing.

[0003] In traditional aircraft design, the design of aerodynamic shape usually relies on the experience of designers or requires a large number of iterative calculations, which has low design efficiency and is difficult to meet the needs of rapid iteration in the early stages of design. Therefore, a method is needed to quickly optimize the aerodynamic shape design of the wing. Summary of the invention

[0004] In view of the above problems, the present invention provides a wing aerodynamic shape optimization method for the conceptual design stage. Based on the thin wing theory, the present invention decouples and optimizes the wing airfoil camber and thickness, first optimizes the wing mid-arc surface, and then optimizes the thickness distribution of the key cross-section airfoil, and transforms the high-dimensional optimization problem into multiple low-dimensional optimization problems, thereby achieving the effect of reducing the design space dimension and accelerating the solution speed.

[0005] The present invention provides a wing aerodynamic shape optimization method for the conceptual design stage, comprising:

[0006] Step 1. Obtain the aerodynamic layout, flight conditions and performance requirements of the aircraft;

[0007] Based on the aerodynamic layout, flight conditions and performance requirements of the aircraft, the wing airfoil of the aircraft is parametrically modeled to obtain an airfoil model;

[0008] Based on the airfoil model, CATIA secondary development technology is used to generate an aerodynamic geometry model of the wing under different shape parameters;

[0009] In one embodiment of the present invention, the aerodynamic layout of the aircraft includes the wing quarter chord sweep angle, dihedral angle, half span, root chord length, tip-to-root ratio, airfoil twist angles at three cross-sectional positions, and three airfoil camber thickness parameters;

[0010] The flight conditions at least include the flight altitude parameter and the speed parameter of the aircraft;

[0011] The performance requirements at least include wing stall requirements and control stability requirements;

[0012] Preferably, the parametric modeling method in step 1 is an improved geometric parameter description airfoil parameterization (IGP) method;

[0013] Step 2. Decouple the airfoil model using the thin wing theory to obtain an airfoil camber parameter and an airfoil thickness parameter;

[0014] Preferably, the airfoil thickness parameters in step 2 include the maximum airfoil thickness T, the maximum thickness position X T , dimensionless leading edge radius Dimensionless trailing edge angle;

[0015] Further, the Bézier curve is used to describe the mean camber line of the airfoil, and the mean camber line of the airfoil is characterized as an airfoil camber parameter;

[0016] Furthermore, the expression of the camber parameter of the airfoil is:

[0017]

[0018] Among them, x C is the horizontal coordinate of the mid-arc equation, y C is the ordinate of the mid-arc line equation, c1 is the airfoil camber parameter one, c2 is the airfoil camber parameter two, k is the parameter equation parameter, c3 is the airfoil camber parameter three, and c4 is the airfoil camber parameter four.

[0019] Furthermore, the airfoil thickness parameter expression is:

[0020] t=t1x 0.5 +t2x+t3x 2 +t4x 3 +t5x 4

[0021] Among them, t1 is the 0.5-order coefficient, t2 is the 1-order coefficient, t3 is the 2-order coefficient, t4 is the 3-order coefficient, t5 is the 4-order coefficient, and x is the lateral position of the airfoil.

[0022] Preferably, step 2 further comprises obtaining a control parameter of the airfoil based on the thickness of the airfoil;

[0023] Furthermore, the expression of the control parameter of the airfoil is:

[0024]

[0025] Among them, X TThe maximum thickness position of the airfoil, T is the maximum thickness of the airfoil, β TE is the trailing edge angle of the airfoil, and ρ0 is the leading edge radius of the airfoil.

[0026] Step 3. Establish an initial wing mid-camber model based on the wing aerodynamic geometry model and airfoil camber parameters;

[0027] Obtain multiple airfoil camber parameters; preset lift coefficient; formulate pitch moment coefficient constraint conditions;

[0028] Let n = 1, when n = 1 is the initial value of the airfoil camber parameter;

[0029] Step 4. Input the airfoil camber parameter n into the wing mid-camber model D n , the vortex lattice method is used to solve the lift coefficient and the corresponding aircraft wing angle of attack B is obtained n ;

[0030] Preferably, in step 4, the vortex lattice method is used to solve the lift coefficient to obtain the corresponding angle of attack B of the aircraft wing. n The specific steps include:

[0031] A series of discrete horseshoe vortices are arranged on each grid; each horseshoe vortex includes two free vortex lines; the two free vortex lines are arranged at two ends of the grid respectively and extend to infinity along the incoming flow direction;

[0032] Arrange the two free vortex lines of each horseshoe vortex on the 1 / 4 chord line of the grid;

[0033] The midpoint of the 3 / 4 chord of each grid is selected as the corresponding control point. Under the condition of non-penetration, the induced velocity caused by a series of discrete horseshoe vortices on each control point is calculated and the corresponding grid vortex strength is obtained to obtain the vortex strength of each grid.

[0034] Set the angle of attack; preset the lift coefficient;

[0035] The vortex strength of each grid is used to solve the wing aerodynamic force at the angle of attack according to the Kutta-Zhukovsky lift circulation theorem;

[0036] Based on the wing aerodynamic force under the angle of attack, the range of the angle of attack is gradually narrowed by searching and combining the dichotomy method. When the angle of attack is reduced to between two adjacent integers, the angle of attack B of the aircraft wing corresponding to the lift coefficient is obtained by linear interpolation. n .

[0037] Step 5. Based on the lift coefficient and the corresponding aircraft wing angle of attack B n , the induced drag coefficient C of the airfoil camber parameter n is obtained n ;

[0038] Under the condition of keeping the moment coefficient constraint, the minimum induced drag coefficient is taken as the first optimization goal;

[0039] Step 6. Based on the optimization objective 1 and the moment coefficient constraint, a multi-island genetic algorithm is used to optimize the wing mid-camber model D n and the airfoil camber parameter n are optimized to obtain an optimized wing mid-camber model and optimized airfoil camber parameters;

[0040] Preferably, the expression of the induced drag coefficient in step 6 is:

[0041] E=Min{CDi(n)},n∈A1

[0042] Where E is the induced drag coefficient, CDi(n) is the induced drag coefficient of the nth airfoil camber parameter, and A1 is the design space corresponding to the design variables.

[0043] Step 7. Determine whether the optimization target 1 meets the convergence condition. If not, set n=n+1 and return to step 4. If the convergence condition is met, take the optimized airfoil camber parameter as the optimal airfoil camber parameter and execute the next step.

[0044] Step 8. Obtain multiple airfoil thickness parameters; let m=1, when m=1 is the initial value of the airfoil thickness parameter;

[0045] Step 9. Generate the corresponding airfoil file S based on the optimal airfoil camber parameter, airfoil thickness parameter m and lift coefficient m ;

[0046] Step 10. Use the X-FOIL algorithm to modify the airfoil file S m Solve to obtain the corresponding airfoil drag coefficient;

[0047] The minimum airfoil drag coefficient is taken as the second optimization target; the airfoil drag coefficient includes a friction drag coefficient and a pressure difference drag coefficient;

[0048] It can be understood that the X-FOIL algorithm solves the flow field by applying a two-dimensional panel method and arranging sources and vortices on the airfoil surface for linear superposition;

[0049] Preferably, the expression of the airfoil drag coefficient in step 10 is:

[0050] F=Min{Cd(m)},m∈A2

[0051] Among them, F is the airfoil drag coefficient value, m is the airfoil thickness parameter, A2 refers to the design space corresponding to the design variable, and Cd(m) is the drag coefficient of the mth airfoil thickness parameter.

[0052] Preferably, the expression of the airfoil resistance is:

[0053]

[0054] Where Ψ(x, y) is the airfoil drag at the coordinate point (x, y), lnr(·) is the velocity potential function, s is the coordinate of the vortex or source, γ is the vector size from the coordinate point of the vortex or source to the coordinate point in the flow field, θ is the angle of the vector, and u ∞ =q ∞ cosα,v ∞ =q ∞ sinα,u ∞ is the acceleration in the x direction at infinity, v ∞ is the x-direction velocity at infinity, q ∞ is the velocity in the y direction at infinity.

[0055] Step 11. According to the optimization target, the airfoil thickness parameter m is optimized using a pattern search method to obtain an optimized airfoil thickness parameter;

[0056] Step 12. Determine whether the optimization target meets the convergence condition. If not, set m=m+1 and return to step 9. If the convergence condition is met, take the optimized airfoil thickness parameter as the optimal airfoil thickness parameter and execute the next step.

[0057] Step 13: Generate an optimal wing aerodynamic shape model based on the optimal airfoil camber parameter and the optimal airfoil thickness parameter;

[0058] Step 14. Optimize the wing aerodynamic shape using the optimal wing aerodynamic shape model.

[0059] Compared with the prior art, the present invention has at least the following beneficial effects:

[0060] (1) The present invention decouples and optimizes the camber thickness of the airfoil, and can take into account the coupling effect of two-dimensional and three-dimensional in the airfoil optimization process, effectively reducing the design space dimension, and taking into account the optimization of induced drag and zero-lift drag;

[0061] (2) The present invention adopts reasonable decoupling design and fast aerodynamic calculation method, which is suitable for the design of new concept aircraft and optimizes both speed and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The drawings are only for the purpose of illustrating particular embodiments and are not to be construed as limiting the invention.

[0063] Figure 1 A schematic diagram of a flow chart of a wing aerodynamic shape optimization method for a conceptual design stage in an embodiment of the present invention;

[0064] Figure 2A schematic diagram of airfoil parameter definition in the IGP method in an embodiment of the present invention;

[0065] Figure 3 Schematic diagram of a wing airfoil in an embodiment of the present invention. DETAILED DESCRIPTION

[0066] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. In addition, the present invention can also be implemented in other ways different from those described herein, and therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0067] A specific embodiment of the present invention, as Figure 1-3 , discloses a wing aerodynamic shape optimization method for the conceptual design stage, and the specific implementation steps are as follows:

[0068] Step 1. Obtain the aerodynamic layout, flight conditions and performance requirements of the aircraft;

[0069] Based on the aerodynamic layout, flight conditions and performance requirements of the aircraft, the wing airfoil of the aircraft is parametrically modeled to obtain an airfoil model;

[0070] Based on the airfoil model, CATIA secondary development technology is used to generate an aerodynamic geometry model of the wing under different shape parameters;

[0071] In one embodiment of the present invention, the aerodynamic layout of the aircraft includes the wing quarter chord sweep angle, dihedral angle, half span, root chord length, tip-to-root ratio, airfoil twist angles at three cross-sectional positions, and three airfoil camber thickness parameters;

[0072] The flight conditions at least include the flight altitude parameter and the speed parameter of the aircraft;

[0073] The performance requirements at least include wing stall requirements and control stability requirements;

[0074] Preferably, the parametric modeling method in step 1 is an improved geometric parameter description airfoil parameterization (IGP) method;

[0075] Step 2. Decouple the airfoil model using the thin wing theory to obtain an airfoil camber parameter and an airfoil thickness parameter;

[0076] Preferably, the airfoil thickness parameters in step 2 include the maximum airfoil thickness T, the maximum thickness position X T , dimensionless leading edge radius Dimensionless trailing edge angle;

[0077] Further, the Bézier curve is used to describe the mean camber line of the airfoil, and the mean camber line of the airfoil is characterized as an airfoil camber parameter;

[0078] Furthermore, the expression of the camber parameter of the airfoil is:

[0079]

[0080] Among them, x C is the horizontal coordinate of the mid-arc equation, y C is the ordinate of the mid-arc line equation, c1 is the airfoil camber parameter one, c2 is the airfoil camber parameter two, k is the parameter equation parameter, c3 is the airfoil camber parameter three, and c4 is the airfoil camber parameter four.

[0081] Furthermore, the airfoil thickness parameter expression is:

[0082] t=t1x 0.5 +t2x+t3x 2 +t4x 3 +t5x 4

[0083] Among them, t1 is the 0.5-order coefficient, t2 is the 1-order coefficient, t3 is the 2-order coefficient, t4 is the 3-order coefficient, t5 is the 4-order coefficient, and x is the lateral position of the airfoil.

[0084] Preferably, step 2 further comprises obtaining a control parameter of the airfoil based on the thickness of the airfoil;

[0085] Furthermore, the expression of the control parameter of the airfoil is:

[0086]

[0087] Among them, X T The maximum thickness position of the airfoil, T is the maximum thickness of the airfoil, β TE is the trailing edge angle of the airfoil, and ρ0 is the leading edge radius of the airfoil.

[0088] Step 3. Establish an initial wing mid-camber model based on the wing aerodynamic geometry model and airfoil camber parameters;

[0089] Obtain multiple airfoil camber parameters; preset lift coefficient; formulate pitch moment coefficient constraint conditions;

[0090] Let n = 1, when n = 1 is the initial value of the airfoil camber parameter;

[0091] Step 4. Input the airfoil camber parameter n into the wing mid-camber model D n , the vortex lattice method is used to solve the lift coefficient and the corresponding aircraft wing angle of attack B is obtained n ;

[0092] Preferably, in step 4, the vortex lattice method is used to solve the lift coefficient to obtain the corresponding angle of attack B of the aircraft wing. n The specific steps include:

[0093] A series of discrete horseshoe vortices are arranged on each grid; each horseshoe vortex includes two free vortex lines; the two free vortex lines are arranged at two ends of the grid respectively and extend to infinity along the incoming flow direction;

[0094] Arrange the two free vortex lines of each horseshoe vortex on the 1 / 4 chord line of the grid;

[0095] The midpoint of the 3 / 4 chord of each grid is selected as the corresponding control point. Under the condition of non-penetration, the induced velocity caused by a series of discrete horseshoe vortices on each control point is calculated and the corresponding grid vortex strength is obtained to obtain the vortex strength of each grid.

[0096] Set the angle of attack; preset the lift coefficient;

[0097] The vortex strength of each grid is used to solve the wing aerodynamic force at the angle of attack according to the Kutta-Zhukovsky lift circulation theorem;

[0098] Based on the wing aerodynamic force under the angle of attack, the range of the angle of attack is gradually narrowed by searching and combining the dichotomy method. When the angle of attack is reduced to between two adjacent integers, the angle of attack B of the aircraft wing corresponding to the lift coefficient is obtained by linear interpolation. n .

[0099] Step 5. Based on the lift coefficient and the corresponding aircraft wing angle of attack B n , the induced drag coefficient C of the airfoil camber parameter n is obtained n ;

[0100] Under the condition of keeping the moment coefficient constraint, the minimum induced drag coefficient is taken as the first optimization goal;

[0101] Step 6. Based on the optimization objective 1 and the moment coefficient constraint, a multi-island genetic algorithm is used to optimize the wing mid-camber model D n and the airfoil camber parameter n are optimized to obtain an optimized wing mid-camber model and optimized airfoil camber parameters;

[0102] Preferably, the expression of the induced drag coefficient in step 6 is:

[0103] E=Min{CDi(n)},n∈A1

[0104] Where E is the induced drag coefficient, CDi(n) is the induced drag coefficient of the nth airfoil camber parameter, and A1 is the design space corresponding to the design variables.

[0105] Step 7. Determine whether the optimization target 1 meets the convergence condition. If not, set n=n+1 and return to step 4. If the convergence condition is met, take the optimized airfoil camber parameter as the optimal airfoil camber parameter and execute the next step.

[0106] Step 8. Obtain multiple airfoil thickness parameters; let m=1, when m=1 is the initial value of the airfoil thickness parameter;

[0107] Step 9. Generate the corresponding airfoil file S based on the optimal airfoil camber parameter, airfoil thickness parameter m and lift coefficient m ;

[0108] Step 10. Use the X-FOIL algorithm to modify the airfoil file S m Solve to obtain the corresponding airfoil drag coefficient;

[0109] The minimum airfoil drag coefficient is taken as the second optimization target; the airfoil drag coefficient includes a friction drag coefficient and a pressure difference drag coefficient;

[0110] It can be understood that the X-FOIL algorithm solves the flow field by applying a two-dimensional panel method and arranging sources and vortices on the airfoil surface for linear superposition;

[0111] Preferably, the expression of the airfoil drag coefficient in step 10 is:

[0112] F=Min{Cd(m)},m∈A2

[0113] Among them, F is the airfoil drag coefficient value, m is the airfoil thickness parameter, A2 refers to the design space corresponding to the design variable, and Cd(m) is the drag coefficient of the mth airfoil thickness parameter.

[0114] Preferably, the expression of the airfoil resistance is:

[0115]

[0116] Where Ψ(x, y) is the airfoil drag at the coordinate point (x, y), lnr(·) is the velocity potential function, s is the coordinate of the vortex or source, γ is the vector size from the coordinate point of the vortex or source to the coordinate point in the flow field, θ is the angle of the vector, and u ∞ =q ∞ cosα,v ∞ =q ∞ sinα,u ∞ is the acceleration in the x direction at infinity, v ∞ is the x-direction velocity at infinity, q ∞ is the y-direction velocity at infinity.

[0117] Step 11. According to the optimization target, the airfoil thickness parameter m is optimized using a pattern search method to obtain an optimized airfoil thickness parameter;

[0118] Step 12. Determine whether the optimization target meets the convergence condition. If not, set m=m+1 and return to step 9. If the convergence condition is met, take the optimized airfoil thickness parameter as the optimal airfoil thickness parameter and execute the next step.

[0119] Step 13: Generate an optimal wing aerodynamic shape model based on the optimal airfoil camber parameter and the optimal airfoil thickness parameter;

[0120] Step 14. Optimize the wing aerodynamic shape using the optimal wing aerodynamic shape model.

[0121] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A wing aerodynamic shape optimization method for the conceptual design stage, characterized in that: include: Step 1. Establish an airfoil model; The airfoil model is used to generate an aerodynamic geometry model of the wing using CATIA secondary development technology; Step 2. Decouple the airfoil model using the thin wing theory to obtain an airfoil camber parameter and an airfoil thickness parameter; Step 3. Establish a wing mid-camber model based on the wing aerodynamic geometry model and airfoil camber parameters; preset the lift coefficient; Let n = 1, when n = 1 is the initial value of the airfoil camber parameter; Step 4. Input the airfoil camber parameter n into the wing mid-camber model D n , the vortex lattice method is used to solve the lift coefficient and obtain the angle of attack B of the aircraft wing n ; Step 5. Based on the lift coefficient and the angle of attack B of the aircraft wing n , the induced drag coefficient C of the airfoil camber parameter n is obtained n ; Set optimization goal one; Step 6. Based on the optimization goal 1, a multi-island genetic algorithm is used to optimize the wing mid-camber model D n and the airfoil camber parameter n are optimized to obtain an optimized wing mid-camber model and optimized airfoil camber parameters; Step 7. Determine whether the optimization objective 1 meets the convergence condition. If not, set n=n+1 and return to step 4. If the convergence condition is met, the optimized airfoil camber parameter is taken as the optimal airfoil camber parameter and the next step is executed; Step 8. Let m = 1, when m = 1, it is the initial value of the airfoil thickness parameter; Step 9. Obtain the airfoil thickness parameter m; generate the corresponding airfoil file S based on the optimal airfoil camber parameter, airfoil thickness parameter m and lift coefficient m ; Step 10. Use the X-FOIL algorithm to modify the airfoil file S m Solve and obtain the corresponding airfoil drag coefficient; set optimization goal 2; Step 11. According to the second optimization goal, the airfoil thickness parameter m is optimized using a pattern search method to obtain an optimized airfoil thickness parameter; Step 12. Determine whether the second optimization objective meets the convergence condition. If not, set m=m+1 and return to step 9. If the convergence condition is met, take the optimized airfoil thickness parameter as the optimal airfoil thickness parameter and execute the next step. Step 13: Generate an optimal wing aerodynamic shape model based on the optimal airfoil camber parameter and the optimal airfoil thickness parameter; Step 14. Optimize the wing aerodynamic shape based on the optimal wing aerodynamic shape model.

2. The wing aerodynamic shape optimization method for the conceptual design stage according to claim 1 is characterized in that: Step 1 to obtain the wing The specific steps of the model include: Obtain the aerodynamic layout, flight conditions and performance requirements of the aircraft; The aircraft's wing airfoil is parametrically modeled based on the aircraft's aerodynamic layout, flight conditions, and performance requirements to obtain an airfoil model.

3. The wing aerodynamic shape optimization method for the conceptual design stage according to claim 1 is characterized in that: The optimization objective 1 in step 5 is to minimize the induced drag coefficient under the constraint of maintaining the pitching moment coefficient; The second optimization goal in step 10 is the minimum airfoil drag coefficient.

4. The wing aerodynamic shape optimization method for the conceptual design stage according to claim 1 is characterized in that: The airfoil drag coefficient in step 10 includes a friction drag coefficient and a pressure difference drag coefficient.

5. The wing aerodynamic shape optimization method for the conceptual design stage according to claim 1 is characterized in that: The expression of the camber parameter of the airfoil is: Among them, x C is the horizontal coordinate of the mid-arc equation, y C is the ordinate of the mid-arc line equation, c1 is the airfoil camber parameter one, c2 is the airfoil camber parameter two, k is the parameter equation parameter, c3 is the airfoil camber parameter three, and c4 is the airfoil camber parameter four.

6. The wing aerodynamic shape optimization method for the conceptual design stage according to claim 1 is characterized in that: The airfoil thickness parameter expression is: t=t1x 0.5 +t2x+t3x 2 +t4x 3 +t5x 4 Among them, t is the airfoil thickness parameter value, t1 is the 0.5-order coefficient, t2 is the 1-order coefficient, t3 is the 2-order coefficient, t4 is the 3-order coefficient, t5 is the 4-order coefficient, and x is the lateral position of the airfoil.

7. The wing aerodynamic shape optimization method for the conceptual design stage according to claim 1 is characterized in that: Step 4: Based on the lift coefficient, the vortex grid method is used to solve the corresponding aircraft wing angle of attack B. n The specific steps include: A series of discrete horseshoe vortices are arranged on each grid; each horseshoe vortex includes two free vortex lines; the two free vortex lines are arranged at two ends of the grid respectively and extend to infinity along the incoming flow direction; Arrange the two free vortex lines of each horseshoe vortex on the 1 / 4 chord line of the grid; The midpoint of the 3 / 4 chord of each grid is selected as the corresponding control point. Under the condition of non-penetration, the induced velocity caused by a series of discrete horseshoe vortices on each control point is calculated and the corresponding grid vortex strength is obtained to obtain the vortex strength of each grid. Set the angle of attack; preset the lift coefficient; The vortex strength of each grid is used to solve the wing aerodynamic force at the angle of attack according to the Kutta-Zhukovsky lift circulation theorem; Based on the wing aerodynamic force under the angle of attack, the range of the angle of attack is gradually narrowed by searching and combining the dichotomy method. When the angle of attack is reduced to between two adjacent integers, the angle of attack B of the aircraft wing corresponding to the lift coefficient is obtained by linear interpolation. n .

8. The wing aerodynamic shape optimization method for the conceptual design stage according to claim 1 is characterized in that: The expression of the induced drag coefficient in step 6 is: E=Min{CDi(n)},n∈A1 Where E is the induced drag coefficient, CDi(n) is the induced drag coefficient of the nth airfoil camber parameter, and A1 is the design space corresponding to the design variables.

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