A propeller aerodynamic optimization design method for multi-working-condition unmanned aerial vehicle

Abstract

This invention relates to an aerodynamic optimization design method for propellers of multi-condition unmanned aerial vehicles (UAVs), and more particularly to an optimization design method for propellers of low Reynolds number and small advance ratio UAVs based on genetic algorithms and sheet theory. It belongs to the field of aerodynamic performance technology for micro fixed-wing UAVs. The method optimizes the thrust coefficient, hovering and cruise efficiency of the propellers of UAVs with low Reynolds number and small advance ratio under hovering and cruise conditions. The chord length and twist angle of the corresponding propeller blades are obtained through the optimized thrust coefficient, hovering and cruise efficiency, and the UAV propeller configuration is designed based on the chord length and twist angle of the propeller blades.

Description

Technical Field

[0001] This invention relates to the field of aerodynamic performance technology for micro fixed-wing unmanned aerial vehicles (UAVs), specifically to a propeller aerodynamic optimization design method for multi-condition UAVs, and more particularly to a low Reynolds number, small advance ratio multi-condition UAV propeller optimization design method based on genetic algorithm and strip theory. Background Technology

[0002] Micro multi-aerial fixed-wing unmanned aerial vehicles (UAVs) are a relatively special type of aircraft. In recent years, due to their unique flight capabilities such as hovering, horizontal forward flight, and vertical takeoff and landing, as well as their advantages of multifunctionality, ease of use, high cost-effectiveness, and broad application prospects, they have attracted widespread attention from academia and industry, sparking a large-scale research boom both domestically and internationally. The propeller, as a crucial core power component of UAVs, is of great research significance.

[0003] Currently, there is a lack of practical tools and design methods for optimizing the design of propellers for micro-UAVs. One reason is the multi-condition problem. Because micro-UAVs have multiple flight modes, based on the characteristics of the propeller, a propeller with a larger chord length and a smaller twist angle is needed when hovering to generate greater thrust to overcome the weight of the fuselage. During cruise, due to the influence of the incoming airflow velocity, a propeller with a smaller chord length and a larger twist angle is needed to keep the blade elements in the high-efficiency range and reduce flight drag. In addition, since most propellers on micro-UAVs are fixed-pitch propellers, using fixed-pitch propellers does not affect the propeller angle of attack, and therefore does not change the propeller lift. The different operating conditions make the propeller design configuration relatively complex.

[0004] Secondly, due to the low flight speed and high propeller speed of micro drones, the flight Reynolds number of micro drones is low and the forward ratio is small, which further leads to a significant reduction in the aerodynamic performance of micro propellers.

[0005] Thirdly, there is the issue of propeller wake. The wake of a micro propeller develops in a spiral shape. The lower the Reynolds number, the stronger the wake produced by the propeller. In the hovering state, the propeller wake shrinks significantly, which will seriously affect the hovering efficiency.

[0006] Therefore, design research is needed for propellers with low Reynolds number, small advance ratio, and wide operating conditions. Summary of the Invention

[0007] In view of the above problems, this invention provides a propeller aerodynamic optimization design method for multi-condition UAVs. Based on multi-objective optimization algorithm and strip theory, the thrust coefficient, hovering and cruise efficiency of the propeller of UAVs with low Reynolds number and small advance ratio are optimized for hovering and cruise conditions. The chord length and twist angle of the corresponding propeller blades are obtained through the optimized thrust coefficient, hovering and cruise efficiency, and the UAV propeller configuration is designed based on the chord length and twist angle of the propeller blades.

[0008] This invention provides a propeller aerodynamic optimization design method for multi-condition unmanned aerial vehicles (UAVs), specifically a propeller aerodynamic optimization design method for low Reynolds number and small advance ratio multi-condition micro fixed-wing UAVs, comprising:

[0009] S1. Determine the design parameters of the propeller for the multi-condition UAV.

[0010] Preferably, the multiple operating conditions in step S1 include: hovering operating condition and cruise operating condition of the UAV propeller;

[0011] Preferably, the design parameters in step S1 include: UAV type, UAV propeller geometry parameters, and propeller performance parameters in cruise and hovering states.

[0012] Furthermore, the drone is a micro fixed-wing drone;

[0013] The geometric parameters of the UAV propeller include the propeller chord length distribution and twist angle distribution; the blade element tension and torque of the propeller chord length distribution and twist angle distribution are obtained based on the force triangle of the propeller blade element and the blade theory;

[0014] The propeller's performance parameters in cruise mode include the incoming flow velocity and propeller speed during cruise; the propeller's performance parameters in hover mode include the incoming flow velocity and propeller speed during hover.

[0015] The incoming flow velocity and propeller speed during the propeller cruise mode create a flight environment with a low Reynolds number and a small advance ratio; the incoming flow velocity and propeller speed during the propeller hovering mode also create a flight environment with a low Reynolds number and a small advance ratio.

[0016] Going further,

[0017] The expression for the leaf element tension is:

[0018]

[0019] Where dT is the blade element thrust of the propeller, ρ is the air density, and c l denoted as ρ, where b is the propeller lift coefficient; b is the propeller blade element chord length; and a is the propeller axial induced velocity coefficient. v aLet V0 be the axial induced velocity of the propeller, T be the propeller thrust, φ be the propeller inlet angle, γ be the propeller drag angle, and dr be the derivative of the propeller blade element radius r.

[0020] The expression for the torque is:

[0021]

[0022] Where dQ is the propeller torque, ρ is the air density, and c l denoted as ρ, where b is the propeller lift coefficient; b is the propeller blade element chord length; and a is the propeller axial induced velocity coefficient. v a Let V0 be the axial induced velocity of the propeller, T be the propeller thrust, φ be the propeller inlet angle, γ be the propeller drag angle, and dr be the derivative of the propeller blade element radius r.

[0023] Furthermore, the incoming flow velocity in the cruise mode is 15-20 m / s, and the propeller speed is 15,000-20,000 rpm; the incoming flow velocity in the hovering mode is 0 m / s, and the propeller speed is 15,000-200,000 rpm.

[0024] The flight environment has a low Reynolds number Re≤350000 and a small advance ratio J≤0.1.

[0025] S2. Based on the design parameters of the UAV propeller, the strip theory, and the database, construct an aerodynamic solution model for the UAV propeller; embed the UAV propeller aerodynamic solution model into a genetic algorithm to obtain an aerodynamic optimization framework for the UAV propeller.

[0026] Preferably, the database in step S2 includes: lift coefficient, drag coefficient, angle of attack, Reynolds number, and Mach number of 19 airfoil elements; the database is established using xfoil's rapid prediction capability; the lift coefficient, drag coefficient, angle of attack, Reynolds number, and Mach number of the 19 airfoil elements in the database are used to calculate the thrust and torque of the 19 airfoil sections, and then the total thrust and total torque of the propeller are obtained by integration.

[0027] S3. Set multiple sets of design variables for UAV propellers under various operating conditions, and determine multiple optimization objectives and constraints of the UAV propeller aerodynamic optimization framework;

[0028] The design variables of the UAV propeller under multiple working conditions are input into the UAV propeller aerodynamic optimization framework for optimization. Multiple optimization objectives are searched for until convergence, and a solution set with optimal values ​​of multiple objectives is obtained.

[0029] Preferably, the specific steps for obtaining the solution set with multiple objective optimal values ​​in step S3 include:

[0030] Multiple sets of design variables for UAV propellers under various operating conditions were set, and multiple optimization objectives and constraints of the UAV propeller aerodynamic optimization framework were determined.

[0031] Input the design variables of multiple sets of UAV propellers under multiple working conditions into the UAV propeller aerodynamic solution model in the UAV propeller aerodynamic optimization framework, and output the propeller aerodynamic performance corresponding to the design variables.

[0032] Based on the propeller aerodynamic performance, multiple optimization objectives are optimized until convergence, resulting in a solution set with optimal values ​​for multiple objectives.

[0033] Determine whether the solution set with multiple objective optimal values ​​satisfies the constraints.

[0034] If yes, the optimal solution set is directly output as the final optimized solution set; otherwise, the next set of propeller design variables is re-optimized until the constraints are met, and the final optimized solution set is output.

[0035] S4. Select the design variables corresponding to the final optimized solution set, and design the propeller configuration of the multi-condition UAV based on the design variables.

[0036] Preferably, the multiple optimization objectives mentioned in step S3 include: propeller hovering efficiency and propeller cruise efficiency, which are obtained through the UAV propeller aerodynamic solution model;

[0037] The hovering efficiency is the ratio of the useful work done by the propeller thrust when the propeller is hovering to the shaft work generated by the motor; the cruise efficiency is the ratio of the useful work done by the propeller thrust when the propeller is cruising to the shaft work generated by the motor.

[0038] The optimal solution set includes the optimized hovering efficiency and optimized cruise efficiency of the UAV propellers;

[0039] Preferably, the objective function expression for the optimization objective is:

[0040] minF(Δ)=min{f1=-η h (Δ),f2=-η c (Δ)}

[0041] Where F(Δ) represents hovering efficiency and cruise efficiency, η h For propeller hovering efficiency, η c For propeller cruise efficiency, f1 is the optimization function in the propeller hovering state, f2 represents the optimization function in the cruise state, and Δ is the design variable of the multi-condition UAV propeller.

[0042] Preferably, step S3, which involves setting the multi-condition UAV propeller design variables, specifically includes:

[0043] Obtain the chord length distribution and twist angle distribution of the propeller blades of UAVs under various operating conditions;

[0044] The chord length distribution and twist angle distribution are parameterized using B-splines to obtain the chord length parameters and twist angle parameters of the UAV propeller blades. The chord length parameters and twist angle parameters of the UAV propeller blades are then used as design variables for multi-condition UAV propellers.

[0045] The technical solution of this invention uses B-splines to parameterize the chord length distribution and twist angle distribution to obtain design variables. The chord length distribution and twist angle distribution on the blade can be described with very few variables. Moreover, the distribution of the design variables conforms to the chord length and twist angle distribution law of the propeller, avoiding local abrupt changes in variables and making the variables highly controllable.

[0046] Preferably, the expression for the design variables of the multi-condition UAV propeller is: ;

[0047] Δ=(c(r),θ(r))

[0048] Where Δ is the optimization design variable, c(r) is the chord length distribution of the propeller blades, and θ(r) is the variable for the propeller blades.

[0049] Let r be the twist angle distribution of the propeller blades, and r be the radius at the radial section of the propeller.

[0050] Preferably, the constraints are the propeller hovering thrust and the propeller cruise thrust, expressed as:

[0051]

[0052] If p1 > 0, then h1 = 0

[0053] If p1≤0, then h1=1

[0054] Where p1 is the propeller hovering thrust coefficient, T hover The thrust for hovering the propeller at the target. h1 is the thrust after the propeller hovering optimization iteration, and h1 is the control coefficient of the propeller hovering penalty term.

[0055]

[0056] If p2 > 0, then h2 = 0

[0057] If p2≤0, then h2=1

[0058] Where p2 is the propeller cruise thrust coefficient, T criise For the thrust of the propeller to cruise the target, h2 is the thrust after the propeller cruise optimization iteration, and h2 is the control coefficient of the propeller cruise penalty term.

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

[0060] The technical solution of this invention is based on multi-objective optimization algorithm and strip theory, and establishes an aerodynamic optimization framework for UAV propellers. Through the UAV propeller aerodynamic optimization framework, the thrust coefficient and hovering and cruise efficiency of propellers with low Reynolds number and small advance ratio are accurately predicted for hovering and cruise conditions. The chord length and twist angle of the corresponding propeller blades are obtained by using the predicted thrust coefficient and hovering and cruise efficiency. The UAV propeller configuration is designed based on the chord length and twist angle of the propeller blades. Attached Figure Description

[0061] The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of the invention.

[0062] Figure 1 This is a schematic diagram of the multi-objective optimization flowchart for the propeller of the micro fixed-wing UAV of the present invention;

[0063] Figure 2 This is a schematic diagram illustrating the optimized hovering and cruising efficiency of the present invention. Detailed Implementation

[0064] To better understand the above-described objectives, features, and advantages of the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other. Furthermore, the present invention can be implemented in other ways different from those described herein; therefore, the scope of protection of the present invention is not limited to the specific embodiments disclosed below.

[0065] A specific embodiment of the present invention, such as Figure 1-2 This invention discloses a propeller aerodynamic optimization design method for multi-condition unmanned aerial vehicles (UAVs). To illustrate the effectiveness of the proposed method, a specific embodiment is provided below for detailed explanation of the above-mentioned technical solution. The specific implementation steps are as follows:

[0066] This invention provides an aerodynamic optimization design method for propellers of multi-condition UAVs with low Reynolds number and small advance ratio, specifically an aerodynamic optimization design method for propellers of multi-condition micro fixed-wing UAVs with low Reynolds number and small advance ratio, comprising:

[0067] S1. Determine the design parameters of the propeller for the multi-condition UAV.

[0068] Preferably, the multiple operating conditions in step S1 include: hovering operating condition and cruise operating condition of the UAV propeller;

[0069] Preferably, the design parameters in step S1 include: UAV type, UAV propeller geometry parameters, and propeller performance parameters in cruise and hovering states.

[0070] Furthermore, the drone is a micro fixed-wing drone;

[0071] The geometric parameters of the UAV propeller include the propeller chord length distribution and twist angle distribution; the blade element tension and torque of the propeller chord length distribution and twist angle distribution are obtained based on the force triangle of the propeller blade element and the blade theory;

[0072] The propeller's performance parameters in cruise mode include the incoming flow velocity and propeller speed during cruise; the propeller's performance parameters in hover mode include the incoming flow velocity and propeller speed during hover.

[0073] The incoming flow velocity and propeller speed during the propeller cruise mode create a flight environment with a low Reynolds number and a small advance ratio; the incoming flow velocity and propeller speed during the propeller hovering mode also create a flight environment with a low Reynolds number and a small advance ratio.

[0074] Going further,

[0075] The expression for the leaf element tension is:

[0076]

[0077] Where dT is the blade element thrust of the propeller, ρ is the air density, and c l denoted as ρ, where b is the propeller lift coefficient; b is the propeller blade element chord length; and a is the propeller axial induced velocity coefficient. v a Let V0 be the axial induced velocity of the propeller, T be the propeller thrust, φ be the propeller inlet angle, γ be the propeller drag angle, and dr be the derivative of the propeller blade element radius r.

[0078] The expression for the torque is:

[0079]

[0080] Where dQ is the propeller torque, ρ is the air density, and c l denoted as ρ, where b is the propeller lift coefficient; b is the propeller blade element chord length; and a is the propeller axial induced velocity coefficient. v a Let V0 be the axial induced velocity of the propeller, T be the propeller thrust, φ be the propeller inlet angle, γ be the propeller drag angle, and dr be the derivative of the propeller blade element radius r.

[0081] Furthermore, the incoming flow velocity in the cruise mode is 15-20 m / s, and the propeller speed is 15,000-20,000 rpm; the incoming flow velocity in the hovering mode is 0 m / s, and the propeller speed is 15,000-200,000 rpm.

[0082] The flight environment has a low Reynolds number Re≤350000 and a small advance ratio J≤0.1.

[0083] S2. Based on the design parameters of the UAV propeller, the strip theory, and the database, construct an aerodynamic solution model for the UAV propeller; embed the UAV propeller aerodynamic solution model into a genetic algorithm to obtain an aerodynamic optimization framework for the UAV propeller.

[0084] Preferably, the database in step S2 includes: lift coefficient, drag coefficient, angle of attack, Reynolds number, and Mach number of 19 airfoil elements; the database is established using xfoil's rapid prediction capability; the lift coefficient, drag coefficient, angle of attack, Reynolds number, and Mach number of the 19 airfoil elements in the database are used to calculate the thrust and torque of the 19 airfoil sections, and then the total thrust and torque of the propeller are obtained by integration;

[0085] S3. Set multiple sets of design variables for UAV propellers under various operating conditions, and determine multiple optimization objectives and constraints of the UAV propeller aerodynamic optimization framework;

[0086] The design variables of the UAV propeller under multiple working conditions are input into the UAV propeller aerodynamic optimization framework for optimization. Multiple optimization objectives are searched for until convergence, and a solution set with optimal values ​​of multiple objectives is obtained.

[0087] Preferably, the specific steps for obtaining the solution set with multiple objective optimal values ​​in step S3 include:

[0088] Multiple sets of design variables for UAV propellers under various operating conditions were set, and multiple optimization objectives and constraints of the UAV propeller aerodynamic optimization framework were determined.

[0089] Input the design variables of multiple sets of UAV propellers under multiple working conditions into the UAV propeller aerodynamic solution model in the UAV propeller aerodynamic optimization framework, and output the propeller aerodynamic performance corresponding to the design variables.

[0090] Based on the propeller aerodynamic performance, multiple optimization objectives are optimized until convergence, resulting in a solution set with optimal values ​​for multiple objectives.

[0091] Determine whether the solution set with multiple objective optimal values ​​satisfies the constraints.

[0092] If yes, the optimal solution set is directly output as the final optimized solution set; otherwise, the next set of propeller design variables is re-optimized until the constraints are met, and the final optimized solution set is output.

[0093] S4. Select the design variables corresponding to the final optimized solution set, and design the propeller configuration of the multi-condition UAV based on the design variables.

[0094] Preferably, the multiple optimization objectives mentioned in step S3 include: propeller hovering efficiency and propeller cruise efficiency, which are obtained through the UAV propeller aerodynamic solution model;

[0095] The hovering efficiency is the ratio of the useful work done by the propeller thrust when the propeller is hovering to the shaft work generated by the motor; the cruise efficiency is the ratio of the useful work done by the propeller thrust when the propeller is cruising to the shaft work generated by the motor.

[0096] The optimal solution set includes the optimized hovering efficiency and optimized cruise efficiency of the UAV propellers;

[0097] Preferably, the objective function expression for the optimization objective is:

[0098] minF(Δ)=min{f1=-η h (Δ),f2=-η c (Δ)}

[0099] Where F(Δ) represents hovering efficiency and cruise efficiency, η h For propeller hovering efficiency, η c For propeller cruise efficiency, f1 is the optimization function in the propeller hovering state, f2 represents the optimization function in the cruise state, and Δ is the design variable of the multi-condition UAV propeller.

[0100] Preferably, step S3, which involves setting the multi-condition UAV propeller design variables, specifically includes:

[0101] Obtain the chord length distribution and twist angle distribution of the propeller blades of UAVs under various operating conditions;

[0102] The chord length distribution and twist angle distribution are parameterized using B-splines to obtain the chord length parameters and twist angle parameters of the UAV propeller blades. The chord length parameters and twist angle parameters of the UAV propeller blades are then used as design variables for multi-condition UAV propellers.

[0103] The technical solution of this invention uses B-splines to parameterize the chord length distribution and twist angle distribution to obtain design variables. The chord length distribution and twist angle distribution on the blade can be described with very few variables. Moreover, the distribution of the design variables conforms to the chord length and twist angle distribution law of the propeller, avoiding local abrupt changes in variables and making the variables highly controllable.

[0104] Preferably, the expression for the design variables of the multi-condition UAV propeller is: ;

[0105] Δ=(c(r),θ(r))

[0106] Where Δ is the optimization design variable, c(r) is the chord length distribution of the propeller blades, and θ(r) is the variable for the propeller blades.

[0107] Let r be the twist angle distribution of the propeller blades, and r be the radius at the radial section of the propeller.

[0108] Preferably, the constraints are the propeller hovering thrust and the propeller cruise thrust, expressed as:

[0109]

[0110] If p1 > 0, then h1 = 0

[0111] If p1≤0, then h1=1

[0112] Where p1 is the propeller hovering thrust coefficient, T hover The thrust for hovering the propeller at the target. h1 is the thrust after the propeller hovering optimization iteration, and h1 is the control coefficient of the propeller hovering penalty term.

[0113]

[0114] If p2 > 0, then h2 = 0

[0115] If p2≤0, then h2=1

[0116] Where p2 is the propeller cruise thrust coefficient, T cruise For the thrust of the propeller to cruise the target, h2 is the thrust after the propeller cruise optimization iteration, and h2 is the control coefficient of the propeller cruise penalty term.

[0117] Subsequently, a penalty function method is used to constrain the nonlinear problem in the optimization, transforming it into a linear problem. At the same time, when the optimization algorithm finds an infeasible point, the value of the objective function can be maximized, with the penalty increasing the further away from the constraint, thereby accelerating the convergence speed of the multi-objective optimization algorithm.

[0118] Finally, to verify the effectiveness of the algorithm proposed in this invention, the optimized results were analyzed. It was found that as cruise efficiency increases, hovering efficiency decreases, indicating that cruise efficiency and hovering efficiency are two contradictory objective functions. When the blade twist angle increases and the chord length decreases, the propeller's cruise efficiency increases and hovering efficiency decreases; conversely, when the blade twist angle decreases and the chord length increases, the propeller's hovering efficiency increases and cruise efficiency decreases. Figure 2 As shown.

[0119] Simultaneously, regions where both cruise and hovering efficiencies are relatively high after optimization were identified, and three points within these regions were selected as research objects for aerodynamic solutions. The cruise and hovering efficiencies of the optimized three propellers were compared with those of the prototype propeller. The analysis results show that the cruise and hovering efficiencies of the optimized propellers were improved by an average of 1.12% and 8.84%, respectively. This demonstrates that the algorithm presented in this invention can effectively optimize the aerodynamic performance of micro fixed-wing UAVs under wide operating conditions; see Table 1 below.

[0120] Table 1

[0121]

[0122] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A propeller aerodynamic optimization design method for a multi-condition unmanned aerial vehicle (UAV), characterized in that, include: S1. Determine the design parameters of the propeller for the multi-condition UAV. S2. Based on the design parameters of the UAV propeller, the strip theory, and the database, construct an aerodynamic solution model for the UAV propeller; embed the UAV propeller aerodynamic solution model into a genetic algorithm to obtain an aerodynamic optimization framework for the UAV propeller. S3. Set multiple sets of design variables for UAV propellers under various operating conditions, and determine multiple optimization objectives and constraints of the UAV propeller aerodynamic optimization framework; The design variables of the UAV propeller under multiple working conditions are input into the UAV propeller aerodynamic optimization framework for optimization. Multiple optimization objectives are searched for until convergence, and a solution set with optimal values ​​of multiple objectives is obtained. S4. Select the design variables corresponding to the final optimized solution set, and design the propeller configuration of the multi-condition UAV based on the design variables. The constraints are the propeller hovering thrust and the propeller cruise thrust; The expressions for the propeller hovering thrust and propeller cruise thrust are: like ,but like ,but in, This is the propeller hovering thrust coefficient. The thrust for hovering the propeller at the target. Optimize the thrust for propeller hovering after iteration. This refers to the control coefficient for the propeller hovering penalty term; like ,but like ,but in, This is the propeller cruise thrust coefficient. For the thrust of the propeller to cruise the target, Optimize the thrust for propeller cruise after iteration. This is the control coefficient for the propeller cruise penalty term.

2. The propeller aerodynamic optimization design method for multi-condition UAVs according to claim 1, characterized in that, The design parameters mentioned in step S1 include the type of UAV, the geometric parameters of the UAV propeller, and the performance parameters of the propeller in cruise and hovering states.

3. The propeller aerodynamic optimization design method for multi-condition UAVs according to claim 2, characterized in that, The propeller's performance parameters in cruise mode include the incoming flow and rotational speed during cruise; the propeller's performance parameters in hover mode include the incoming flow and rotational speed during hover.

4. The propeller aerodynamic optimization design method for multi-condition UAVs according to claim 2, characterized in that, The geometric parameters of the UAV propeller include the propeller chord length distribution and the twist angle distribution.

5. The propeller aerodynamic optimization design method for multi-condition UAVs according to claim 1, characterized in that, Step S3, which describes obtaining a solution set with multiple objective optimal values, includes the following specific steps: Multiple sets of design variables for UAV propellers under various operating conditions were set, and multiple optimization objectives and constraints of the UAV propeller aerodynamic optimization framework were determined. Input the design variables of multiple sets of UAV propellers under multiple working conditions into the UAV propeller aerodynamic solution model in the UAV propeller aerodynamic optimization framework, and output the propeller aerodynamic performance corresponding to the design variables. Based on the propeller aerodynamic performance, multiple optimization objectives are optimized until convergence, resulting in a solution set with optimal values ​​for multiple objectives. Determine whether the solution set with multiple objective optimal values ​​satisfies the constraints. If yes, the optimal solution set is directly output as the final optimized solution set; otherwise, the next set of propeller design variables is re-optimized until the constraints are met, and the final optimized solution set is output.

6. The propeller aerodynamic optimization design method for multi-condition UAVs according to claim 1, characterized in that, The multiple optimization objectives mentioned in step S3 include propeller hovering efficiency and propeller cruise efficiency.

7. The propeller aerodynamic optimization design method for multi-condition UAVs according to claim 1, characterized in that, The objective function expression for the optimization objective in step S3 is: in, Let be the objective function for hovering efficiency and cruise efficiency. For hovering efficiency, For cruise efficiency, This represents the optimization function in the hovering state. This represents the optimization function during cruise mode. A function to optimize design variables.

8. The propeller aerodynamic optimization design method for multi-condition UAVs according to claim 1, characterized in that, The expression for the design variables of the multi-condition UAV propeller is: in, To optimize the function values ​​of the design variables, c(r) represents the chord length distribution of the propeller blades, θ(r) represents the twist angle distribution of the propeller blades, and r represents the radius at the radial section of the propeller.

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