Structure optimization design method for variable propeller disc inclination angle of four-axis eight-rotor unmanned aerial vehicle

Abstract

The invention discloses a structure optimization design method for a variable propeller disc inclination angle of a four-axis eight-rotor unmanned aerial vehicle. The method comprises the following steps: constructing a coaxial dual-rotor geometric model; based on the coaxial dual-rotor geometric model, performing interval parameterization analysis, and determining optimization parameters; determining boundary conditions based on the optimization parameters; acquiring a rotating speed control boundary and a lift force control boundary based on the boundary condition and the rotor wing data; according to the rotating speed control boundary and the lift force control boundary, a rotor disc inclination angle yaw moment is obtained; and based on the rotor disc inclination angle yaw moment, the optimal rotor disc inclination angle is obtained. According to the method, the optimal structural parameters are systematically determined through computational fluid mechanics numerical simulation and flight dynamics optimization algorithms, the lift efficiency, the loading capacity and the flight stability are remarkably improved in a complex flight environment, and theoretical guidance and technical support are provided for engineering design of the multi-rotor unmanned aerial vehicle.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of unmanned aerial vehicle optimization design, and particularly relates to a structural optimization design method for variable rotor disc inclination angle of a four-axle eight-rotor unmanned aerial vehicle. BACKGROUND

[0002] The conventional four-axle unmanned aerial vehicle usually adopts a single-layer rotor configuration with fixed rotor disc angle, and the following technical problems exist in the design and optimization: firstly, there is no systematic parameter optimization method, and the optimal structural parameters and control parameters cannot be scientifically determined according to specific flight conditions, resulting in poor aerodynamic efficiency; secondly, the existing design method fails to fully consider the aerodynamic interference effect between the coaxial rotors, and lacks a rotor spacing optimization method based on computational fluid dynamics; thirdly, the determination of the rotor disc inclination angle mainly relies on experience or simple test methods, and lacks a systematic optimization algorithm based on flight dynamics theory. In the prior art, although there are related researches on coaxial dual-rotor unmanned aerial vehicles, there is generally a lack of systematic innovation from the design method level, and it is impossible to provide scientific and reliable parameter optimization guidance for engineering practice. SUMMARY

[0003] To solve the above technical problems, the application provides a structural optimization design method for variable rotor disc inclination angle of a four-axle eight-rotor unmanned aerial vehicle, which systematically determines the optimal structural parameters through computational fluid dynamics numerical simulation and flight dynamics optimization algorithm, significantly improves the lift efficiency, load capacity and flight stability in complex flight environments, and provides theoretical guidance and technical support for engineering design of multi-rotor unmanned aerial vehicles.

[0004] To achieve the above purpose, the application provides a structural optimization design method for variable rotor disc inclination angle of a four-axle eight-rotor unmanned aerial vehicle, which comprises the following steps:

[0005] constructing a coaxial dual-rotor geometric model;

[0006] performing spacing parameterization analysis based on the coaxial dual-rotor geometric model to determine optimization parameters;

[0007] determining boundary conditions based on the optimization parameters;

[0008] obtaining a rotation speed control boundary and a lift control boundary based on the boundary conditions and rotor data;

[0009] obtaining a rotor disc inclination angle yawing moment according to the rotation speed control boundary and the lift control boundary;

[0010] obtaining an optimal rotor disc inclination angle based on the rotor disc inclination angle yawing moment.

[0011] Optionally, the spacing parameterization analysis based on the coaxial dual-rotor geometric model to determine the optimization parameters comprises the following steps:

[0012] Based on the coaxial rotor geometry model, a dimensionless spacing ratio and a dimensionless lift ratio are introduced for spacing parameter analysis to obtain a three-dimensional flow field calculation domain containing a key region;

[0013] Based on the three-dimensional flow field calculation domain, the optimization parameter is determined.

[0014] Optionally, determining the optimization parameter based on the three-dimensional flow field calculation domain comprises:

[0015] The three-dimensional flow field calculation domain is subjected to CFD numerical calculation by using a sliding mesh method and an SST k-ω turbulence model to determine an optimal spacing parameter, and the optimization parameter is calculated by using the dimensionless lift ratio.

[0016] Optionally, the method for calculating the optimization parameter is:

[0017]

[0018] wherein k aero is the optimization parameter, and P is the dimensionless lift ratio.

[0019] Optionally, the boundary condition is:

[0020]

[0021] wherein Ω boundary is a system boundary constraint vector, M is a total mass, g is a gravity acceleration scalar, n is a rotor shaft number, Δω max is a maximum relative rotation speed difference, is a maximum yaw angle acceleration, and F hover is a hovering thrust demand.

[0022] Optionally, based on rotor data, the rotation speed control boundary and the lift control boundary are obtained by:

[0023] Based on rotor data, a rotation speed-throttle interpolation function and a lift-throttle interpolation function are constructed;

[0024] According to the rotation speed-throttle interpolation function and the lift-throttle interpolation function, the rotation speed control boundary and the lift control boundary are obtained.

[0025] Optionally, the rotation speed-throttle interpolation function is:

[0026]

[0027] wherein ω(δ) is a rotation speed throttle function, F ω (δ) is a rotation speed throttle interpolation function, c i is a rotation speed throttle interpolation coefficient, and δ iis the throttle value, i is the rotational speed, and the throttle interpolation function is an interpolation point index.

[0028] The lift-throttle interpolation function is:

[0029]

[0030] where F(δ) is a lift-throttle function, G(δ) is a lift-throttle interpolation function, d i is a lift-throttle interpolation coefficient, and m is an interpolation point index of the lift-throttle interpolation function.

[0031] Optionally, the blade tilt angle yawing moment is:

[0032]

[0033] where M θ is a blade tilt angle moment vector, θ is a blade tilt angle, L y is a yawing arm, δ max , δ min is a throttle control boundary, ω max , ω min is a rotational speed control boundary.

[0034] Optionally, based on the blade tilt angle yawing moment, the optimal blade tilt angle is obtained by:

[0035] Based on the blade tilt angle yawing moment, a yawing shaft dynamics equation is obtained.

[0036] Based on the yawing shaft dynamics equation, the optimal blade tilt angle is obtained.

[0037] Compared with the prior art, the present application has the following advantages and technical effects:

[0038] The innovative tilt angle variable propeller disc structure design and calculation method enables the rotor system to perform real-time angle adjustment according to different flight conditions and task requirements, significantly improves the maneuvering performance and steering response flexibility of the unmanned aerial vehicle in a complex environment, and provides technical support for multiple flight modes such as precise hovering, rapid maneuvering and stable cruising; the coaxial rotor spacing configuration optimized by computational fluid dynamics minimizes the aerodynamic interference effect between the upper and lower rotors, increases the unit power aerodynamic lift by about 77% compared with the traditional single rotor scheme, and greatly improves the load capacity and endurance of the unmanned aerial vehicle. At the same time, the high-frequency response capability and control precision of the attitude control system are effectively ensured; the topologically optimized hollow main beam structure design provides the possibility of structural gravity center adjustment and spacious internal space layout for the unmanned aerial vehicle during flight under the premise of meeting the strict structural strength and stiffness requirements. This design not only enhances the adaptability of the unmanned aerial vehicle to various complex flight conditions, but also provides sufficient installation space and flexible configuration options for carrying various task loads and special equipment; a complete four-axle eight-rotor unmanned aerial vehicle optimization design method system is established, filling the gap in systematic design methods in this field. Through the comprehensive use of multidisciplinary optimization theory, scientific theoretical guidance and standardized design process are provided for engineering practice, significantly improving the design efficiency and reliability; the whole set of optimization design method has good universality and scalability, and can provide parameter optimization guidance for multi-rotor unmanned aerial vehicles of different specifications and purposes, and has important engineering application value and popularization prospect. BRIEF DESCRIPTION OF DRAWINGS

[0039] The accompanying drawings, which form a part of this application, are included to provide a further understanding of the application and are incorporated in and constitute a part of this application. The embodiments of this application, and of which the principles are explained, are illustrated in the drawings, wherein:

[0040] Figure 1 is a three-dimensional structure schematic diagram of the unmanned aerial vehicle of the embodiment of the present application, wherein 1, 2 are front and rear main bearing rods, 3, 4 are lateral support rods, 5, 6 are central connecting rods, 7, 8 are diagonal reinforcing rods, 9, 10, 11, 12 are upper and lower layer connecting rods;

[0041] Figure 2 is a top view structure schematic diagram of the unmanned aerial vehicle of the embodiment of the present application;

[0042] Figure 3 is a side view structure schematic diagram of the unmanned aerial vehicle of the embodiment of the present application;

[0043] Figure 4 is a structure schematic diagram of the unmanned aerial vehicle frame structure of the embodiment of the present application;

[0044] Figure 5 is a structure schematic diagram of the unmanned aerial vehicle fork assembly and rotor structure of the embodiment of the present application;

[0045] Figure 6 A schematic diagram of the rotor tilting of the unmanned aerial vehicle of the embodiment of the present application;

[0046] Figure 7 A trend chart of the change of the rotor aerodynamic force with its spacing;

[0047] Figure 8 A cloud chart of the flow field change in the rotor rotation process;

[0048] Figure 9 A flow chart of a variable pitch angle structure optimization design method of a four-axle eight-rotor unmanned aerial vehicle of the embodiment of the present application. DETAILED DESCRIPTION

[0049] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0050] It should be noted that the steps shown in the flow chart of the accompanying drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flow chart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0051] The present application proposes a variable pitch angle structure optimization design method of a four-axle eight-rotor unmanned aerial vehicle, as shown in Figure 9 , specifically comprising the following steps:

[0052] Constructing a coaxial double-rotor geometric model;

[0053] Based on the coaxial double-rotor geometric model, performing spacing parameterization analysis to determine the optimization parameters;

[0054] Based on the optimization parameters, determining the boundary conditions;

[0055] Based on the boundary conditions and the rotor data, obtaining the speed control boundary and the lift control boundary;

[0056] According to the speed control boundary and the lift control boundary, obtaining the pitch angle yaw moment of the rotor;

[0057] Based on the pitch angle yaw moment of the rotor, obtaining the optimal pitch angle.

[0058] Specifically, step A: the fuselage structure parameter design as shown in Figure 4 , the design adopts a double-layer "II" type four-arm bearing structure fuselage main frame, and the front and rear two main bearing arms of the four-arm structure are respectively provided with fork assembly mounting nodes at the ends thereof;

[0059] Step B: the fork assembly configuration asFigure 5 As shown, the fork type assembly is arranged at the four end positions of the front and rear main bearing arms, and each fork type assembly contains two mirror-symmetrically arranged rotor mounting units;

[0060] Step C: Coaxial rotor spacing optimization, using computational fluid dynamics method to determine the optimal axial spacing of eight rotor power assemblies, wherein the specific optimization value diagram is as shown in Figure 7 As shown, the flow field characteristic diagram is as shown in Figure 8 As shown, as shown in Table 1, the coaxial rotor spacing configuration optimized by computational fluid dynamics minimizes the aerodynamic interference effect between the upper and lower rotors, increases the unit power aerodynamic lift by about 77% compared with the traditional single rotor scheme, and greatly improves the load performance and endurance of the unmanned aerial vehicle;

[0061] Table 1

[0062]

[0063] Wherein, 1. K is the ratio of rotor spacing H to rotor radius R;

[0064] 2. Lift increase ratio = (coaxial double rotor lift-single rotor lift) / single rotor lift x 100%;

[0065] 3. The bold value represents the peak lift when K=0.4;

[0066] Step D: Rotor disc tilt angle optimization calculation, establish a rotor disc tilt angle optimization model, calculate the optimal tilt angle of each rotor within ±15°, and the rotor disc tilt angle diagram is as shown in Figure 6 As shown;

[0067] Step E: Control system implementation, manual adjustment and locking of the rotor disc tilt angle is realized through the adjustable angle connecting mechanism.

[0068] Further, based on the coaxial double rotor geometric model, the spacing parameterization analysis is carried out, and the optimization parameters include:

[0069] Based on the coaxial double rotor geometric model, the dimensionless spacing ratio and the dimensionless lift ratio are introduced for spacing parameter analysis, and a three-dimensional flow field calculation domain containing the key region is obtained;

[0070] Based on the three-dimensional flow field calculation domain, the optimization parameters are determined.

[0071] Specifically, a three-dimensional geometric model of coaxial double rotors is established, so that the upper and lower rotors are mirror distributed and the rotation directions are opposite;

[0072] Define the dimensionless spacing ratio K=H / R, wherein H is the axial distance between the upper and lower rotors, and R is the rotor radius;

[0073] Adjusting the spacing ratio K, generating multiple sets of calculation models, and dividing the flow field into rotating and stationary domains for each model;

[0074] CFD numerical calculation is performed by using the sliding mesh technique and the SST k-omega turbulence model;

[0075] The lift ratio P under different spacings is calculated as the optimization target, and is defined as P = (T2-T1) / T1, where T2 is the lift of the coaxial rotors, and T1 is the lift generated by the single rotor.

[0076] The optimal spacing parameter K is determined, and the air interference coefficient k is calculated through the lift ratio P aero , preparing for subsequent calculation of the blade pitch angle.

[0077] Further, based on the three-dimensional flow field calculation domain, the optimization parameters include:

[0078] CFD numerical calculation is performed on the three-dimensional flow field calculation domain by using the sliding mesh method and the SST k-omega turbulence model, the optimal spacing parameter is determined, and the optimization parameter is calculated through the dimensionless lift ratio.

[0079] Further, based on the rotor data, the speed control boundary and the lift control boundary include:

[0080] Based on the rotor data, the speed-throttle interpolation function and the lift-throttle interpolation function are constructed;

[0081] According to the speed-throttle interpolation function and the lift-throttle interpolation function, the speed control boundary and the lift control boundary are obtained.

[0082] Further, based on the blade pitch angle yawing moment, the optimal blade pitch angle includes:

[0083] Based on the blade pitch angle yawing moment, the yaw axis dynamics equation is obtained;

[0084] Based on the yaw axis dynamics equation, the optimal blade pitch angle is obtained.

[0085] The embodiment specifically includes the following core steps:

[0086] Step 1, geometric modeling and parametric design:

[0087] According to the specific use conditions and performance requirements of the unmanned aerial vehicle, a suitable high-efficiency airfoil profile is selected, and a precise coaxial rotor geometric model is established by using a three-dimensional modeling software. Ensure that the upper and lower rotors are arranged in a completely mirror-symmetrical manner, so that the two rotors can generate upward lift in opposite rotating directions, and the respective generated counter-torque can be offset, achieving the design goal of zero net torque output.

[0088] Step 2, spacing parametric analysis:

[0089] A dimensionless pitch ratio K is introduced as a key design parameter, defined as K = H / R, where H represents the axial distance between the upper and lower rotors, and R represents the standard radius of the rotor blades. Through parametric modeling techniques, the range of K values ​​is systematically adjusted to generate multiple sets of three-dimensional flow field calculation models covering different pitch ratios. A dimensionless lift ratio P is introduced as an optimization objective, defined as P = (T2 - T1) / T1, where T2 is the sum of the lift of the coaxial dual rotors, and T1 is the lift generated by a single rotor.

[0090] Step 3: CFD numerical simulation calculation:

[0091] For each parameterized coaxial dual-rotor computational model, a precise computational domain was partitioned to construct a three-dimensional flow field computational domain containing the following key regions:

[0092] The rotating domain is a cylindrical rotating domain with a radius of 1.2R (R is the rotor radius) centered on each rotor blade, and an axial height of 3.5L (L is the characteristic length), to ensure that the flow field around the rotor blade is fully contained within the rotating domain.

[0093] The stationary domain is a cylindrical stationary domain, in which the upper end of the rotating domain is approximately 6R from the upper end of the stationary domain, the lower end of the rotating domain is approximately 20R from the lower end of the stationary domain, and the radius of the stationary domain is approximately 12R. This stationary domain provides sufficient computational space for the rotor's far-field flow.

[0094] A sliding mesh interface is established between the rotating and stationary domains, and a conservative interpolation method is used to ensure the conservation and transfer of mass, momentum, and energy.

[0095] High-quality meshes are generated using a hybrid structured and unstructured meshing technique:

[0096] An O-type structured mesh is used on the rotor blade surface to ensure that the y+ value is controlled at around 1. The total number of boundary layer mesh layers is 15, with a growth rate of 1.2.

[0097] The blade surface uses a triangular unstructured mesh with 100 nodes in the chord direction and 50 nodes in the span direction to ensure accurate capture of the blade's geometric features.

[0098] Tetrahedral unstructured meshes are used in the rotating domain, with the mesh size gradually transitioning from small meshes on the blade surface to large meshes in the far field, with a growth rate of 1.2.

[0099] Mesh skewness is controlled below 0.85, and orthogonality quality is maintained above 0.15.

[0100] Calculation parameter settings:

[0101] The control equation is based on the Navier-Stokes equation group, solved by the Reynolds time-averaged method, the SST k-omega two-equation turbulence model is selected, the sliding mesh technology is used to process the rotor rotation, and the second-order upwind difference format is used for spatial discretization, and the time step is set to 1 / 360 of the rotor rotation period, to ensure the time accuracy of the calculation.

[0102] The boundary conditions of the calculation domain are set as follows:

[0103] The far-field inlet adopts a pressure inlet boundary condition, and the outlet adopts a pressure outlet boundary condition, and the pressure difference between the inlet and the outlet is set to a standard atmospheric pressure condition.

[0104] Step 4: Optimization parameter determination

[0105] Run high-precision CFD numerical calculation, systematically statistics and analysis of different rotor axial spacing configuration under the lift characteristics, to establish the quantitative relationship between the spacing parameters and the aerodynamic performance. In the premise of ensuring P as large as possible and not affecting the attitude control of the aircraft, determine the optimal ratio K. After determining the lift ratio P of the coaxial double rotors, the aerodynamic interference coefficient k under this spacing can be calculated aero , the specific formula is: Provide key coefficients for subsequent calculation of blade pitch angle.

[0106] Blade pitch angle optimization calculation method: this embodiment establishes a blade pitch angle calculation method based on flight dynamics theory and optimization algorithm, which provides the optimal blade pitch angle parameters for unmanned aerial vehicles under different flight conditions, the specific implementation steps are as follows:

[0107] Step 1: Setting of multi-condition boundary conditions:

[0108] The boundary of the yaw channel performance is set as:

[0109]

[0110] Where, Ω boundary ∈R 3×1 is the system boundary constraint vector, M∈R+ is the total mass, g∈R + is the gravity acceleration scalar, n∈Z + is the number of rotor shafts, Δω max ∈R + is the maximum relative speed difference, is the maximum yaw angle acceleration, F hover ∈R + is the hover thrust demand.

[0111] Step 2: Speed-throttle interpolation function based on rotor data:

[0112] The non-linear relationship between the rotational speed and the throttle is described by piecewise linear interpolation:

[0113]

[0114] The specific piecewise form is where ω j , ω j+1 correspond to the rotational speed values for the throttle interval [δ j , δ j+1 ].

[0115] Step 3: Lift-throttle interpolation function based on rotor data (single rotor data here):

[0116] The non-linear relationship between the lift and the throttle is described by piecewise linear interpolation:

[0117]

[0118] The specific piecewise form is where F j , F j+1 correspond to the rotational speed values for the throttle interval [δ j , δ j+1 ].

[0119] Step 4: Inverse interpolation algorithm for throttle boundary constraints:

[0120] The throttle control boundary is derived from the rotational speed boundary, defined as:

[0121]

[0122] F -1 is the rotational speed-throttle inverse interpolation function, ω max , ω min are the rotational speed control boundaries, and δ max , δ min are brought into the lift-throttle interpolation function to obtain the lift boundaries G F (δ max ), G F (δ min ).

[0123] Step 5: Expression of the tilt angle yaw moment of the rotor disc

[0124] The per-axis rotor disc tilt angle moment vector is defined as:

[0125]

[0126] where M θ is the rotor disc tilt angle moment vector, θ is the rotor disc tilt angle, and L y is the yaw arm.

[0127] Step 6: Lagrange expression of rigid body dynamics

[0128] The kinetic and potential energy of the system are defined as:

[0129]

[0130] The yaw axis dynamics equation is derived from the Euler-Lagrange equation:

[0131]

[0132] where, I zz is the yaw axis moment of inertia, is the yaw angle, and Q(δ) is the inverse torsional function.

[0133] Step 7: Variational expression of the constrained optimization problem:

[0134] The optimal blade pitch angle is defined as a constrained optimization problem:

[0135]

[0136] where, Θ is the feasible region, is the minimum yaw angle acceleration requirement.

[0137] The present application also provides a fuselage structure design scheme matched with the above optimization method:

[0138] The upper and lower double-layer "II" type four-arm bearing structure design is adopted after structural mechanics optimization analysis, and the optimal structure parameters are determined through finite element analysis. The main bearing beam of the fuselage is made of high-strength 7075-T6 aluminum alloy material, and the key structure connection node adopts advanced argon arc welding and friction stir welding composite process.

[0139] The hollow truss design optimized by structural mechanics is innovatively adopted, the optimal opening position, size and shape are determined through finite element analysis, and the internal storage space and equipment installation space of the unmanned aerial vehicle are significantly increased on the premise of maintaining the structural stiffness and strength indexes. At the same time, the possibility of dynamic adjustment of the structure gravity center is provided.

[0140] The fork assembly is precisely manufactured by 6061-T6 aluminum alloy material, has a double-arm beam structure design, and realizes the continuous adjustable function of the rotor blade tilt angle through a precise mechanical connection mechanism. The adjustable angle connection mechanism adopts a design scheme of high-strength stainless steel bolt matched with wear-resistant sleeve, and realizes the precise manual adjustment function of the blade tilt angle by controlling the pre-tightening force of the bolt.

[0141] The present embodiment will be described in detail below with reference to the accompanying drawings:

[0142] AsFigures 1-3 As shown, the application provides a coaxial eight-rotor unmanned aerial vehicle structure based on advanced aerodynamic design, which mainly comprises three core functional modules of a bearing body main frame I, a multi-degree-of-freedom fork assembly II and a high-efficiency rotor power assembly III.

[0143] Specific implementation of the coaxial rotor spacing optimization method:

[0144] According to the CFD optimization method of the application, a three-dimensional geometric model of the coaxial dual-rotor is established, and the XW E6 rotor blade is selected. The rotor radius R is 0.3 m, and the spacing ratio K value is adjusted by parameterization to generate five groups of calculation models of K=0.2, 0.3, 0.4, 0.5 and 0.6.

[0145] The CFD numerical calculation is performed by using the computational fluid dynamics software, the total number of grids is about 8 million, the rotating domain adopts the sliding mesh technology, and the turbulence model selects the SST k-ω model. The calculation results show that:

[0146] When K=0.2: the lift is T=39.82 N, and there is serious aerodynamic interference;

[0147] When K=0.3: the lift coefficient T=42.13 N, and the aerodynamic interference is obviously reduced;

[0148] When K=0.4: the lift coefficient T=47.87 N, and the lift performance is greatly improved;

[0149] When K=0.5: the lift coefficient T=47.75 N, and the lift slightly decreases;

[0150] When K=0.6: the lift coefficient T=48.12 N, and the lift tends to be stable;

[0151] The lift and attitude control of the unmanned aerial vehicle are comprehensively considered, and therefore the optimal spacing ratio K=0.4 is determined, that is, the spacing H between the upper and lower rotors is 0.12 m. The lift ratio under the spacing is about 1.76, and the aerodynamic interference coefficient is about 0.88.

[0152] Specific implementation of the rotor disc tilt angle optimization method:

[0153] For the four-axis eight-rotor unmanned aerial vehicle with a full-load hovering total weight M=20 kg, the reference speed is 2646 RPM, the yaw equivalent force arm is about 0.304 m, and the moment of inertia is about 2.47 kg\cdot pm2. According to the rotor disc tilt angle optimization method of the application:

[0154] Step 1: set the boundary of the yaw channel performance as:

[0155] Maximum speed difference: Δω max = 20%·ω0, minimum angular acceleration: Single-rotor nominal lift: Fhover = 27.8 N.

[0156] Step 2: Establish the rotational speed-throttle interpolation function, the specific data as shown in Table 2:

[0157] Table 2

[0158]

[0159] According to the above data table, the piecewise linear interpolation function is specifically in the form of:

[0160]

[0161] Step 3: Establish the lift-throttle interpolation function, the specific data as shown in Table 3:

[0162] Table 3

[0163]

[0164] According to the above data table, the piecewise linear interpolation function is specifically in the form of:

[0165]

[0166] Step 4: Determine the throttle boundary:

[0167]

[0168] Lift boundary:

[0169]

[0170] Step 5: Expression of the rudder angle yawing moment:

[0171]

[0172] Step 6: Solution of the yaw axis dynamics equation:

[0173] δ max = 46.8% throttle corresponding power about 385 W→Q(δ max ) ≈ 1.20 N·pm

[0174] δ min = 31.8% throttle corresponding power about 140 W→Q(δ min ) ≈ 0.45 N·pm

[0175]

[0176] Step 7: Solution of the constrained optimization problem:

[0177]

[0178] The determination of the fuselage structure parameters:

[0179] The fuselage main frame adopts a double-layer "II" type four-arm bearing structure design optimized by structural mechanics analysis. The upper and lower frames are rigidly connected by four precisely arranged diagonal support bars using argon arc welding process, forming a high-strength three-dimensional truss structure. The specific structure parameters are determined by finite element analysis optimization: the lengths of the front and rear main bearing bars 1 and 2 are 752.31 mm, which are designed as the core components mainly bearing flight loads; the lengths of the lateral support bars 3 and 4 are 608.17 mm, mainly bearing lateral stability and torsional stiffness; the lengths of the central connecting bars 5 and 6 are 252.29 mm, used for connecting the upper and lower frames and transmitting loads; the lengths of the diagonal reinforcing bars 7 and 8 are 469.39 mm, providing additional structural stiffness and stability; the lengths of the upper and lower connecting bars 9, 10, 11 and 12 are all 345.04 mm, ensuring the spatial stability of the overall structure. All bearing bars are designed with a circular cross-section of 28 mm in outer diameter and 2.5 mm in wall thickness, and the material used is high-strength 7075-T6 aluminum alloy, which has excellent strength-to-weight ratio and corrosion resistance, with a tensile strength of 524 MPa and a yield strength of 455 MPa, ensuring the safety and reliability of the overall structure under complex flight loads. The geometric center of the fuselage is provided with a modular flight control system installation compartment and a power battery storage compartment. The installation positions of these functional cabins are all equipped with standardized quick connection interfaces, supporting flexible adjustment and reconfiguration according to task requirements. The modular design concept not only facilitates daily maintenance, but also quickly adapts to changes in load, differences in endurance requirements, and various operating flight conditions.

[0180] The fork assembly is precisely manufactured with 6061-T6 aluminum alloy material with excellent processing performance and fatigue resistance. Its innovative double-arm beam structure design realizes the continuous adjustable function of the rotor disc tilt angle through precise mechanical connection mechanism, providing enhanced maneuverability and attitude control capability for the unmanned aerial vehicle.

[0181] The above is only the preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any changes or replacements within the technical scope disclosed in the present application can be easily thought of by those skilled in the art, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A variable pitch angle structure optimization design method for a quadrotor unmanned aerial vehicle, characterized in that, The method comprises the following steps: constructing a coaxial rotor geometry model; performing spacing parameterization analysis based on the coaxial rotor geometry model to determine optimization parameters; determining boundary conditions based on the optimization parameters; obtaining a rotation speed control boundary and a lift control boundary based on the boundary conditions and rotor data; obtaining a blade tilt angle yaw moment according to the rotation speed control boundary and the lift control boundary; obtaining an optimal blade tilt angle based on the blade tilt angle yaw moment.

2. The method of claim 1, wherein the method is characterized by: The method of performing spacing parameterization analysis based on the coaxial rotor geometry model to determine optimization parameters comprises the following steps: introducing dimensionless spacing ratios and dimensionless lift ratios based on the coaxial rotor geometry model to perform spacing parameterization analysis, and obtaining a three-dimensional flow field calculation domain containing a key region; determining the optimization parameters based on the three-dimensional flow field calculation domain.

3. The method of claim 2, wherein the method further comprises: The method of determining the optimization parameters based on the three-dimensional flow field calculation domain comprises the following steps: performing CFD numerical calculation on the three-dimensional flow field calculation domain by using a sliding mesh method and an SST k-ω turbulence model to determine optimal spacing parameters, and calculating the optimization parameters by using dimensionless lift ratios.

4. The method of claim 3, wherein the method is characterized by: The method of calculating the optimization parameters comprises the following steps: where k aero is an optimization parameter and P is a dimensionless lift ratio.

5. The method of claim 4, wherein the method further comprises: The boundary conditions are: where Ω boundary is the system boundary constraint vector, M is the total mass, g is the gravitational acceleration scalar, n is the number of rotor shafts, Δω max is the maximum relative speed difference, is the maximum yaw angle acceleration, F hover is the hover thrust demand.

6. The method of claim 5, wherein the method is characterized by: The method of obtaining a rotation speed control boundary and a lift control boundary based on rotor data comprises the following steps: constructing a rotation speed-throttle interpolation function and a lift-throttle interpolation function based on rotor data; obtaining a rotation speed control boundary and a lift control boundary according to the rotation speed-throttle interpolation function and the lift-throttle interpolation function.

7. The method of claim 6, wherein the method further comprises: The rotation speed-throttle interpolation function is: Where ω(δ) is the speed throttle function, F ω (δ) is the speed throttle interpolation function, c i is the speed throttle interpolation coefficient, δ i is the throttle value, and i is the speed throttle interpolation function interpolation point label. The lift-throttle interpolation function is: Where F(5) is the lift throttle function, G(5) is the lift throttle interpolation function, d i is the lift throttle interpolation coefficient, and m is the lift throttle interpolation function interpolation point index.

8. The method of claim 7, wherein the method is characterized by: The blade tilt angle yaw moment is: where M θ is the blade tilt moment vector, θ is the blade tilt angle, L y is the yawing force arm, δ max , δ min is the throttle control boundary, ω max , ω min is the rotational speed control boundary.

9. The method of claim 7, wherein the method further comprises: The method of obtaining an optimal blade tilt angle based on the blade tilt angle yaw moment comprises the following steps: obtaining a yaw axis dynamics equation based on the blade tilt angle yaw moment; obtaining the optimal blade tilt angle based on the yaw axis dynamics equation.

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