A method for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV

Abstract

The present invention discloses a method for determining the rotor design parameters of a coaxial twin-rotor plateau load-bearing UAV, comprising the following steps: constructing a basic rotor model; establishing a plateau flow field coupling model; dynamic environmental parameter mapping: constructing a dynamic model to quantify the nonlinear correlation between air density and aerodynamic load under different altitude conditions, calculating the influence of altitude on aerodynamic load distribution and rotor power consumption under target thrust; plateau-adaptive rotor shape constraint design: mapping plateau environmental parameters to rotor torsion angle, chord length distribution and airfoil profile parameters, and analyzing transient aerodynamic response by combining time spectrum method and multi-grid method; multi-objective collaborative optimization: based on the comprehensive optimization objective function, considering the aerodynamic coupling effect and environmental adaptability between the upper and lower rotors of the coaxial twin-rotor, taking the phase difference angle of the upper and lower rotor blades as a variable, with the goal of minimizing the lift loss caused by aerodynamic interference, and generating rotor design parameters through a multi-objective optimization algorithm.

Description

Technical Field

[0001] The present invention relates to the technical fields of power inspection UAVs, rotor design, and the like, and in particular to a method for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV. Background Art

[0002] Currently, conventional helicopter rotor shape optimization design primarily relies on the momentum blade element theory and lift line method to theoretically design rotor negative twist distribution, chord length distribution, and airfoil profile distribution. Theoretical formulas are used to derive the expected rotor aerodynamic performance, which is then verified through wind tunnel testing. While these theoretical methods can quickly estimate rotor design performance, they lack accuracy for increasingly complex three-dimensional rotor aerodynamic performance and fail to account for the complex aerodynamic interference phenomena of tiltrotors. This often results in a significant gap between theoretically designed tiltrotor performance and actual aerodynamic performance.

[0003] In the existing technology, accurate rotor comprehensive performance design evaluation indicators are obtained to obtain a target rotor that is closer to the actual aerodynamic performance. However, since the comprehensive performance indicators are usually set based on steady-state conditions, and the air density of the rotor is reduced in the plateau environment, it is easy to affect the thrust and energy consumption of the rotor. Therefore, optimizing the rotor parameters under steady-state conditions cannot solve the problems of reduced thrust and increased energy consumption of the rotor in the plateau environment.

[0004] Coaxial twin rotors present aerodynamic interference issues. Because the upper and lower rotors rotate in opposite directions, the mutual coupling of their wake vortex systems leads to a complex superposition of induced velocity fields, which in turn causes asymmetric lift distribution and energy loss. Specifically, the downwash generated by the upper rotor directly affects the inflow conditions of the lower rotor, causing dynamic changes in the local angle of attack of the lower rotor blades, thereby reducing aerodynamic efficiency and increasing power consumption. Furthermore, the low-density air at high altitudes weakens the rotor's lift generation capability while exacerbating the diffusion and dissipation of the vortex core, further amplifying the aerodynamic interference effect between the upper and lower rotors, manifesting as increased vibration, noise, and the risk of dynamic stall. This interference not only affects the drone's hovering stability and endurance, but also exacerbates the difficulty of flight attitude control under high-altitude, high-turbulence conditions. Therefore, optimizing the phase difference angle and shape parameters of the coaxial twin rotors to mitigate the negative impact of aerodynamic interference on lift and energy consumption is key to improving drone flight performance in high-altitude environments.

[0005] Therefore, a method for determining rotor design parameters based on a plateau environment is provided to realize that the reduced air density in a plateau environment affects the thrust and energy consumption of the rotor, so as to solve the problem that conventional rotor design methods perform parameter optimization design of the rotor under steady-state conditions. In a plateau environment, the reduced air density can easily affect the thrust and energy consumption of the rotor, which is an urgent problem that needs to be solved by those skilled in the art.

[0006] Furthermore, there is an increasing demand for power inspection drones operating in high-altitude, mountainous, and complex meteorological environments. This is particularly true for high-voltage transmission line inspections in plateau regions, where drones must maintain stable flight performance and control accuracy despite low pressure, low temperature, and high turbulence. However, traditional rotor design methods are often based on standard atmospheric parameters and fail to fully consider the significant impact of the low-density air in plateaus on rotor aerodynamic efficiency. This results in insufficient lift, increased energy consumption, and significantly reduced endurance in low Reynolds number flow fields. Furthermore, existing rotor optimization technologies primarily focus on steady-state aerodynamic performance in plain environments and lack the ability to actively adapt to transient airflow disturbances in plateaus (such as sudden crosswind changes and near-ground vortex rings). This makes drones susceptible to attitude instability when flying close to power facilities, potentially leading to interruptions in inspection missions. Therefore, a rotor design approach that integrates dynamic plateau environmental parameters with multidisciplinary optimization objectives is urgently needed to improve the operational reliability and mission adaptability of drones in extreme climates and complex airspaces. Summary of the Invention

[0007] To address the above-mentioned technical problems, the present invention provides a method for determining rotor design parameters for a coaxial twin-rotor high-altitude load-carrying UAV. The method first quantifies environmental parameters under different altitude conditions by obtaining the plateau environment's temperature, humidity, vibration environmental stress, and altitude. These parameters are then incorporated into the rotor design optimization process. This method improves rotor performance in high-altitude areas, enabling the rotor to better adapt to high-altitude, low-pressure, and low-temperature environments (particularly suitable for power inspection UAVs operating in complex airspace such as plateau mountainous areas and high-voltage transmission line corridors). The method also ensures stable rotor operation in high-altitude areas (ensuring the accuracy and safety of the UAV's attitude control when operating close to power facilities in strong crosswinds and low-density flow fields). By optimizing the rotor design using different optimization parameters, the method significantly improves the lift-to-drag ratio and reduces aerodynamic drag, thereby enhancing hovering efficiency, forward flight efficiency, and overall flight performance (meeting the requirements for long-duration hovering observation, rapid forward flight transitions, and maneuvering response under unexpected operating conditions during power inspection missions). Furthermore, the method enhances flight stability and response sensitivity (providing the UAV with interference immunity and precise controllability in high-voltage electromagnetic interference environments or narrow inspection corridors).

[0008] On the basis of obtaining a general rotor optimization design scheme, based on the actual needs of rotor optimization of coaxial twin-rotor plateau load-bearing UAV, the aerodynamic coupling effect and environmental adaptability between the upper and lower rotors of the coaxial twin-rotor are considered, and the phase difference angle of the upper and lower rotor blades is used as a variable. The goal is to minimize the lift loss caused by aerodynamic interference, and the rotor design parameters are generated through a multi-objective optimization algorithm.

[0009] The present invention specifically adopts the following technical solutions:

[0010] A method for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV comprises the following steps:

[0011] Determine the geometric and aerodynamic parameter ranges of the original rotor based on the aircraft parameters and generate basic rotor parameters;

[0012] By combining the lift-torque dynamics equation with the free wake model, the aerodynamic load distribution in the low-density flow field is simulated, and the aerodynamic load distribution is used as input data for the rotor shape constraint design;

[0013] The temperature, humidity, and altitude of the plateau environment were obtained, and a dynamic model was constructed to quantify the nonlinear relationship between air density and aerodynamic load at different altitudes. This was used to modify the aerodynamic shape parameter mapping rules in the rotor shape constraint design. The Newton iteration method was used to calculate the influence of altitude on the aerodynamic load distribution and the rotor power consumption at the target thrust. These influence patterns and power consumption were used as input parameters for multi-objective optimization.

[0014] Based on the basic rotor parameters, the rotor shape constraint design is carried out: the plateau environmental parameters are mapped to the rotor twist angle, chord length distribution and airfoil profile parameters in the basic rotor parameters, and the transient aerodynamic response is analyzed by combining the time spectrum method and the multigrid method; the comprehensive optimization objective function is defined based on the transient aerodynamic response results;

[0015] Perform multi-objective optimization: Based on the comprehensive optimization objective function, a multi-objective optimization algorithm is used to generate rotor design parameters adapted to the plateau environment.

[0016] Generating basic rotor parameters not only provides an initial design benchmark but also constrains the dynamic adjustment range in plateau environments. This defines the initial design space and constraints for optimization, ensuring that subsequent dynamic parameter adjustments remain within a reasonable range.

[0017] The aerodynamic load distribution is achieved by dynamically binding aerodynamic performance and structural parameters to ensure that the optimization results meet the actual needs of the low-density flow field in the plateau. The subsequent optimization of the rotor twist angle, chord length distribution and airfoil profile parameters is combined with the rotor parameters themselves and the lift distribution, pressure distribution, torque distribution, etc. in the aerodynamic load distribution.

[0018] The influence law is a representation of the solution of the Newton iteration method, including the law of change of power with altitude; F is used to correct the aerodynamic efficiency term in multi-objective optimization. s / F ρ part.

[0019] Furthermore, generating basic rotor parameters includes:

[0020] Determine rotor radius, chord length distribution, airfoil series, and number of blades based on aircraft type and mission profile;

[0021] Parameterize the design parameters of the forward-swept, backward-swept, and downward-inverted feature points to generate a geometrically sensitive space;

[0022] A parameter combination is selected within the geometrically sensitive space to construct a basic propeller shape.

[0023] Furthermore, the free wake model discretizes the blade tip vortex through a viscous vortex particle algorithm and adopts a viscous vortex core empirical model to describe the distortion and dissipation of the vortex; the vortex particles are initialized according to the rotor speed and pitch angle, and the wake motion trajectory is tracked through a Lagrangian method;

[0024] The construction of the free wake model includes:

[0025] Based on the vorticity-velocity form of the incompressible Navier-Stokes equations, the vortex structure in the flow field is discretized into viscous vortex particles that carry vorticity, position and intensity information.

[0026] The amount of attached vortex ring on the rotor surface is calculated by combining lifting surface theory, and the newly generated vortex particles are released in real time according to the rotor movement to simulate the generation process of tip vortex and wake vortex.

[0027] The generation process of the tip vortex and the wake vortex is coupled to output a free wake model.

[0028] Furthermore, the dynamic model is constructed based on the unsteady Navier-Stokes equations and free vortex theory. After inputting the rotor aerodynamic load, the output is the influence of the low-density air in the plateau on the drag attenuation of the aerodynamic load and the power consumption. The convergence condition of the Newton iteration method is the speed change threshold. , where n is the rotor speed and m is the number of iterations; the rotor power consumption is calculated by the formula Calculation, where c is the power system efficiency coefficient; the air density Calculate, where Altitude The air density at is the air density at sea level, h is the altitude, and H is the attenuation height coefficient.

[0029] Furthermore, the analysis of transient aerodynamic response by combining the time spectrum method with the multigrid method includes:

[0030] Capturing the transient aerodynamic characteristics of rotor dynamic stall by time spectrum method;

[0031] Use multi-grid methods to accelerate flow field solutions to improve the prediction accuracy of aerodynamic shape parameters;

[0032] The parameters of the rotor shape constraint include:

[0033] Airfoil profile shape parameters: Optimize leading edge radius, maximum camber position and trailing edge angle based on thin wing theory;

[0034] Propeller tip geometric characteristic parameters: aerodynamic modification design for noise reduction;

[0035] Blade span parameters: used for coupled optimization of half span and installation angle;

[0036] The optimization of the airfoil section shape parameters includes dynamically adjusting the geometric shape under different Reynolds numbers.

[0037] Furthermore, the aerodynamic efficiency term is related to lift, power and drag, and the structure-stability term is related to blade pressure distribution and rotor solidity; the aerodynamic efficiency term is , the structural-stability term is , where P consumes power, P max The maximum power consumed by the rotor in hovering state to generate maximum hovering lift under different atmospheric densities is: is the performance coefficient of the rotor material, is the lift force of the aircraft, The density of the atmosphere in which the aircraft is resistance, is the blade root pressure, is the blade tip pressure, J q is the pressure difference between the upper and lower surfaces of the blade.

[0038] Furthermore, the rotor design parameters adapted to the plateau environment are generated through a multi-objective optimization algorithm. Specifically, the multi-objective optimization design is carried out through the NSGA-II multi-objective optimization algorithm, and the rotor aerodynamic shape is iteratively optimized through selection, crossover, and mutation genetic operators to obtain the Pareto optimal solution set.

[0039] Furthermore, the rotor is a coaxial twin rotor, and the negative impact of aerodynamic interference on lift and energy consumption is suppressed by optimizing the phase difference angle and shape parameters of the coaxial twin rotor. The optimization design includes:

[0040] The phase difference angle φ between the upper and lower rotors is used as a design variable, and the effect of φ on transient aerodynamic loads is analyzed using the time spectrum method.

[0041] The coupling effect of the velocity field induced by the upper and lower rotors is calculated based on the viscous vortex particle algorithm. By formula:

[0042]

[0043] Quantify, where 、 Represent the circulation distribution of the upper and lower rotors respectively, 、 is the induced velocity field; R is the rotor radius, ρ is the air density;

[0044] The phase difference angle φ and rotor shape parameters are collaboratively iteratively optimized using the NSGA-II multi-objective optimization algorithm to generate a Pareto optimal solution set.

[0045] And, an aircraft, characterized in that its rotor is obtained by optimizing the design according to the above method.

[0046] And, a system for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV, comprising:

[0047] The basic rotor modeling module is used to determine the geometric and aerodynamic parameter ranges of the original rotor based on the aircraft parameters and generate basic rotor parameters;

[0048] The plateau flow field coupling module simulates the aerodynamic load distribution in low-density flow fields by combining the lift-torque dynamics equation with the free wake model. The aerodynamic load distribution serves as input data for rotor shape constraint design.

[0049] An environmental parameter processing module is used to obtain the temperature, humidity, and altitude of the plateau environment, construct a dynamic model to quantify the nonlinear relationship between air density and aerodynamic load at different altitudes, and use it to modify the aerodynamic shape parameter mapping rules in the rotor shape constraint design. The module also uses the Newton iteration method to calculate the influence of altitude on the aerodynamic load distribution and the rotor power consumption under the target thrust. These influences and power consumption are used as input parameters for multi-objective optimization.

[0050] A rotor shape constraint design module is used to perform rotor shape constraint design based on basic rotor parameters, map plateau environmental parameters to the rotor twist angle, chord length distribution, and airfoil profile parameters in the basic rotor parameters, analyze transient aerodynamic response using a time spectrum method and a multigrid method, and define a comprehensive optimization objective function based on the transient aerodynamic response results; map plateau environmental parameters to the rotor twist angle, chord length distribution, and airfoil profile parameters, analyze transient aerodynamic response using a time spectrum method and a multigrid method, and define a comprehensive optimization objective function based on the transient aerodynamic response results;

[0051] The multi-objective optimization module is used to generate rotor design parameters adapted to the plateau environment through a multi-objective optimization algorithm based on the comprehensive optimization objective function.

[0052] And, an electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the program.

[0053] A non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0054] Compared to existing technologies, the present invention and its preferred embodiment optimize the rotor design by incorporating plateau environmental parameters. This improves rotor performance at high altitudes, reduces drag loss, and increases efficiency in both hover and forward flight (particularly suitable for power inspection UAVs requiring long-duration hovering observation and rapid relocation in complex plateau and mountainous terrain). By incorporating plateau environmental parameters into the rotor design, the rotor is better adapted to the high altitude, low air pressure, and low temperature environment (addressing issues such as insufficient lift and weak crosswind resistance caused by low-density air during power inspection missions), minimizing performance degradation due to environmental changes and ensuring stable rotor operation at high altitudes (ensuring the UAV's attitude stability and safe obstacle avoidance capabilities in electromagnetic interference environments such as high-voltage transmission line corridors). By optimizing the blade shape and angle of attack, the rotor can propel more air at the same speed, thereby reducing energy consumption and extending flight time (meeting the dual requirements of power inspection missions for endurance and maneuverability in emergency situations). By combining the basic rotor aerodynamic model with the free-wake model, a rotor aerodynamic model is developed. This model accurately describes the rotor's flow field characteristics under different flight conditions (allowing for high-precision prediction of complex flow fields such as near-ground flight and gust disturbances during power inspections), significantly improving the accuracy of aerodynamic load predictions and providing reliable data support for design optimization. The rotor aerodynamic model integrates aerodynamic, structural dynamics, and flight mechanics parameters to support the coordinated optimization of the rotor's aerodynamic shape, structural strength, and flight performance (the optimized rotor balances turbulence resistance and control sensitivity in narrow inspection corridors). By analyzing aerodynamic performance in hover and forward flight using the free-wake model, the lift-to-drag ratio of the rotor type can be determined at different altitudes. By optimizing the rotor twist angle and chord length distribution, the rotor's thrust and efficiency in low-density environments can be optimized, resulting in optimized parameters for the airfoil profile shape, blade tip geometry, and blade span. Airfoil section optimization parameters dynamically adjust the geometry of each blade section, maintaining a high lift-to-drag ratio across various Reynolds numbers (meeting the aerodynamic stability requirements of power inspection drones flying across altitudes from low-altitude plains to high-altitude areas), ensuring aerodynamic stability across a wide Reynolds number range. Tip geometry optimization parameters locally optimize the blade tip shape, reducing rotor noise while improving aerodynamic efficiency (minimizing interference with high-voltage equipment acoustic testing during drone inspections). Spanwise optimization parameters optimize the blade half-span and mounting angle coupling parameters, improving the rotor's lift-to-drag ratio and interference rejection (enhancing interference resistance and precise hovering capabilities in high-voltage electromagnetic fields). Optimizing the rotor design using different optimization parameters significantly improves the lift-to-drag ratio and reduces aerodynamic drag, thereby enhancing hovering efficiency, forward flight efficiency, and overall flight performance (providing a high-precision, high-reliability flight platform for precise transmission line inspections). BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0056] Figure 1 This is a flow chart of a method for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV according to an embodiment of the present invention.

[0057] Figure 2 This is a comparison chart of the lift-to-drag ratio of the front and rear airfoils optimized according to an embodiment of the present invention. DETAILED DESCRIPTION

[0058] Hereinafter, specific embodiments of the present application will be described in detail with reference to the accompanying drawings. Based on these detailed descriptions, those skilled in the art will be able to clearly understand the present application and implement the present application. Without violating the principles of the present application, the features of different embodiments may be combined to obtain new implementations, or certain features of certain embodiments may be substituted to obtain other preferred implementations.

[0059] To make the features and advantages of the present invention more clearly understood, the following embodiments are specifically described in detail with reference to the accompanying drawings.

[0060] The embodiment of the present invention provides Figure 1 The specific process of the method for determining the rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV shown in the figure includes the following steps:

[0061] S1: Obtain relevant parameters of the aircraft, determine the parameters of the original rotor according to the relevant parameters of the aircraft, and obtain the basic propeller type according to the original rotor parameters;

[0062] As a preferred solution of this embodiment, the method for obtaining the original rotor parameters specifically includes:

[0063] Parameterizing the original rotor to obtain the design parameter range of the rotor characteristic points, wherein the rotor characteristic points include: forward-swept characteristic points, backward-swept characteristic points, downward-reversed characteristic points, and rotor aerodynamic parameters;

[0064] Different parameters are selected within the design parameter range of the rotor feature points to construct the basic rotor of the aircraft. The rotor aerodynamic parameters are selected as follows:

[0065]

[0066] Where T is the tension parameter, is the lift coefficient, is the air density, D is the rotor diameter, and n is the rotor speed;

[0067] in, is the power parameter to overcome the resistance torque, is the power coefficient;

[0068]

[0069]

[0070] in, is the efficiency parameter, J is the pitch ratio, reflecting the airflow angle at the blade tip, and V is the axial velocity.

[0071] S2: Use the parameters of the basic propeller obtained in S1 to build a rotor aerodynamic model, use the rotor aerodynamic model to simulate the aerodynamic performance of the basic rotor, and obtain the aerodynamic load of the rotor;

[0072] As a preferred solution of this embodiment, the method of constructing a rotor aerodynamic model using the original rotor parameters specifically includes:

[0073] Based on the rotor radius, rotor chord length and speed parameters, the dynamic equations of lift and torque are established, including the interaction between propellers and the effect of air resistance;

[0074] The rotor force and moment are calculated by combining the rotor and fuselage with wind tunnel data, and the unsteady aerodynamic model is used to describe the local aerodynamic load changes on the rotor.

[0075] Calculate the flow field disturbance during near-ground flight using the NS equations and correct the pull and torque coefficients;

[0076] The basic rotor aerodynamic model is established using the dynamic equations of lift and torque, the changes in the rotor's local aerodynamic load, and the thrust and torque coefficients, as follows:

[0077] The viscous vortex particle algorithm is used to spatially discretize the rotor tip vortex through line vortex discretization. The viscous vortex core empirical model is used to reflect the distortion and dissipation of the tip vortex, and a free wake model is established.

[0078] The rotor aerodynamic basic model and free wake model are integrated into the rotor aerodynamic model.

[0079] Establish a free wake model, including:

[0080] Based on the vorticity-velocity form of the incompressible Navier-Stokes equations, the vortex structure in the flow field is discretized into viscous vortex particles, each of which carries vorticity, position and intensity information.

[0081] The large-scale vortex in the rotor wake is discretized into small vortex elements, and the motion trajectory of the rotor wake is described by the Lagrangian method.

[0082] Initialize the vortex particle distribution according to the rotor speed and pitch angle, set the initial vortex field and calculate the vortex particle transport process;

[0083] The amount of attached vortex ring on the rotor surface is calculated by combining lifting surface theory, and the newly generated vortex particles are released in real time according to the rotor movement to simulate the generation process of tip vortex and wake vortex.

[0084] The generation process of the tip vortex and the wake vortex is coupled to obtain the free wake model, which is specifically expressed as follows:

[0085] ‌

[0086] in, is the radial position of the vortex element on the blade The position vector at is the free velocity vector, is the azimuth, is the vortex age, is the wake distortion;

[0087] In this step, the rotor aerodynamic model is obtained by combining the rotor aerodynamic basic model with the free wake model. The aerodynamic basic model can accurately describe the flow field characteristics of the rotor in different flight states, such as induced velocity distribution and aeroelastic coupling effect, by integrating free wake analysis, blade-vortex interference effect and nonlinear blade torsion distribution factors, significantly improving the accuracy of aerodynamic load prediction and providing reliable data support for optimized design. The rotor aerodynamic model integrates aerodynamics, structural dynamics and flight mechanics parameters, supports the coordinated optimization of the rotor aerodynamic shape, structural strength and flight performance, and can achieve rapid and high-precision simulation of the rotor flow field. By analyzing the aerodynamic performance in hovering and forward flight states through the free wake model, the change law of the lift-to-drag ratio of the rotor type at different altitudes can be clarified.

[0088] S3: Obtain the temperature, humidity, and altitude of the plateau environment, quantify the environmental parameters under different altitude conditions, and calculate the influence of altitude on the aerodynamic load distribution and the rotor power consumption under the target thrust using the Newton iteration method;

[0089] As a preferred solution of this embodiment, the Newton iteration method is used to calculate and determine the influence of altitude on aerodynamic load distribution, specifically including:

[0090] A dynamic model was constructed based on the unsteady Navier-Stokes equations and free vortex theory. The aerodynamic loads of the rotor were input into the dynamic model, and the influence of low-density air in the plateau on the aerodynamic loads of the rotor was output.

[0091] The Newton iteration method is used to calculate the rotor power consumption under the target thrust at altitude, as follows:

[0092]

[0093]

[0094] in, is the tensile force value, are the rotor geometric parameters, is the rotor speed, Altitude The air density at is the target pulling force, is the air density at sea level, H is the attenuation height;

[0095] Update the rule using Newton iteration method:

[0096]

[0097] Convergence is judged when Stop iteration when ,;

[0098] ‌Calculate power‌, substitute the converged Value to power formula:

[0099] in, is the power system efficiency coefficient.

[0100] S4: Determine the design constraints and optimization objectives of the rotor shape based on the relevant parameters and mission profile of the aircraft, combined with environmental parameters at different altitudes and rotor power consumption at target thrust;

[0101] As a preferred solution of this embodiment, determining the design constraints of the rotor shape specifically includes:

[0102] Mapping plateau environmental parameters to rotor design parameters to obtain the adjusted rotor twist angle parameters and chord length distribution parameters;

[0103] The transient aerodynamic response of the rotor is analyzed by coupling the time spectrum method and the multigrid method when the rotor is in flight, and the aerodynamic shape parameters of the rotor are obtained.

[0104] Based on the thin airfoil theory, a high lift-to-drag ratio airfoil is determined over a wide Reynolds number range, and the airfoil profile shape parameters, blade tip geometric characteristic parameters, and blade span parameters are obtained.

[0105] As a preferred solution of this embodiment, determining the optimization target specifically includes:

[0106]

[0107]

[0108] Among them, P is the power consumption, P maxThe maximum power consumed by the rotor in hovering state to generate maximum hovering lift under different atmospheric densities is: is the atmospheric density, is the atmospheric density at altitude i, To optimize the goal, is the performance coefficient of the rotor material, is the lift force of the aircraft, The density of the atmosphere in which the aircraft is resistance, is the blade root pressure, is the blade tip pressure, J q is the pressure difference between the upper and lower surfaces of the blade.

[0109] In this step, the rotor twist angle optimization parameters and chord length distribution optimization parameters can be used to optimize the thrust and efficiency of the rotor in a low-density environment, and the airfoil section shape optimization parameters, blade tip geometry optimization parameters and blade span optimization parameters are obtained. The airfoil section shape optimization parameters can be used to dynamically adjust the geometric shapes of each blade section to maintain a high lift-to-drag ratio at different Reynolds numbers, ensuring the stability of aerodynamic performance within a wide Reynolds number range. The blade tip geometry optimization parameters can be used to locally optimize the blade tip shape, reducing rotor noise while improving aerodynamic efficiency. The blade span optimization parameters can be used to optimize the blade half-span and installation angle coupling parameters to improve the lift-to-drag ratio and anti-interference capability of the rotor. The optimization results are as follows: Figure 2 shown.

[0110] By "introducing plateau environmental parameters and optimizing the design of the rotor, the performance of the rotor in high altitude areas can be improved, the thrust loss can be reduced, the efficiency in hovering and forward flight can be improved, the rotor can better adapt to the high altitude, low pressure and low temperature environment, and the performance degradation caused by environmental changes can be reduced. It ensures the stable operation of the rotor in high altitude areas, pushes more air at the same speed, thereby reducing energy consumption and extending flight time." The technical solution can achieve the technical effect of "reducing the thrust of the rotor and increasing energy consumption in the plateau environment."

[0111] S5: Optimize the rotor design based on the rotor shape design constraints and optimization objectives;

[0112] As a preferred solution of this embodiment, the design optimization of the rotor specifically includes:

[0113] Multi-objective optimization design is carried out using the NSGA-II multi-objective optimization algorithm. The rotor aerodynamic shape is iteratively optimized through selection, crossover, and mutation genetic operators to obtain the Pareto optimal solution set. The rotor aerodynamic shape is iteratively optimized through selection, crossover, and mutation genetic operators as follows:

[0114]

[0115] ' is the fitness convergence threshold, is the maximum number of iterations, For the Generate the optimal fitness value‌ ;

[0116] The Pareto optimal solution set is analyzed and processed to determine whether the optimization converges. If it converges, the result is output, and an optimal solution that meets the design requirements is selected and the process ends. Otherwise, a new optimal solution is selected as the new initial solution and NSGA-II is used again to carry out multi-objective optimization design.

[0117] As a preferred embodiment, in plateau environments, the coordinated optimization of coaxial twin rotors needs to comprehensively consider the aerodynamic coupling effect between the upper and lower rotors and the environmental adaptability. By introducing the phase difference parameterization design, the phase difference angle of the upper and lower rotor blades is adjusted. As the key variable, the objective function is to minimize the lift loss caused by aerodynamic interference. ,in It is generated by the interaction of the induced velocity fields of the upper and lower rotor wakes, and its dynamic distribution is calculated using the viscous vortex particle algorithm:

[0118]

[0119] In the formula 、 Represent the circulation distribution of the upper and lower rotors respectively, 、 is the induced velocity field. Combined with the time spectrum method analysis In order to study the influence of transient aerodynamic loads, the NSGA-II multi-objective optimization algorithm is used to realize the collaborative iterative optimization of phase difference and rotor shape parameters, and finally generate the Pareto optimal solution set.

[0120] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors and a memory for storing one or more computer programs; the program includes program instructions, and the processor is used to execute the program instructions stored in the memory. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is used to implement one or more instructions, specifically for loading and executing one or more instructions in a computer storage medium to implement the above method.

[0121] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium having a computer program stored thereon, which, when executed by a processor, performs the above-described method. The storage medium may be any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0122] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0123] The above shows and describes the basic principles, main features and advantages of the present disclosure. Those skilled in the art should understand that the present disclosure is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present disclosure. Various changes and improvements may be made to the present disclosure without departing from the spirit and scope of the present disclosure, and such changes and improvements shall fall within the scope of the present disclosure.

[0124] The present invention is not limited to the above-mentioned optimal implementation mode. Anyone can derive various other forms of methods for determining rotor design parameters based on plateau environments under the guidance of the present invention. All equal changes and modifications made within the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. A method for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV, characterized in that: The following steps are involved: Determine the geometric and aerodynamic parameter ranges of the original rotor based on the aircraft parameters and generate basic rotor parameters; By combining the lift-torque dynamics equation with the free wake model, the aerodynamic load distribution in low-density flow fields is simulated. The temperature, humidity, and altitude of the plateau environment are obtained, and a dynamic model is constructed to quantify the nonlinear relationship between air density and aerodynamic load at different altitudes. This is used to modify the aerodynamic shape parameter mapping rules in the rotor shape constraint design. The Newton iteration method is used to calculate the influence of altitude on aerodynamic load distribution and the rotor power consumption under target thrust. Mapping plateau environmental parameters to the rotor twist angle, chord length distribution, and airfoil profile parameters in the basic rotor parameters, analyzing the transient aerodynamic response by combining the time spectrum method with the multigrid method; and defining a comprehensive optimization objective function based on the transient aerodynamic response results; Based on the comprehensive optimization objective function, a multi-objective optimization algorithm is used to generate rotor design parameters adapted to the plateau environment; The dynamic model is constructed based on the unsteady Navier-Stokes equations and free vortex theory. After inputting the rotor aerodynamic load, the output is the influence of the low-density air on the aerodynamic load and the power consumption. The convergence condition of the Newton iteration method is the speed change threshold. , where n is the rotor speed and m is the number of iterations; the rotor power consumption is calculated by the formula Calculated, where c is the power system efficiency coefficient; the air density is calculated by Calculate, where Altitude The air density at is the air density at sea level, h is the altitude, and H is the attenuation height coefficient; The comprehensive optimization objective function is composed of the sum of the aerodynamic efficiency term and the structural-stability term: the aerodynamic efficiency term is related to lift, power and drag, and the structural-stability term is related to the blade pressure distribution and rotor solidity; the aerodynamic efficiency term is , the structural-stability term is , where P is the power consumption, The maximum power consumed by the rotor in hovering state to generate maximum hovering lift under different atmospheric densities is: is the performance coefficient of the rotor material, is the lift force of the aircraft, The density of the atmosphere in which the aircraft is resistance, is the blade root pressure, is the blade tip pressure, J q is the pressure difference between the upper and lower surfaces of the blade; The rotor is a coaxial twin rotor, and the optimized design includes: The phase difference angle φ between the upper and lower rotors is used as a design variable, and the effect of φ on transient aerodynamic loads is analyzed using the time spectrum method. Calculate the coupling effect of the upper and lower rotor induced velocity fields and lift loss based on the viscous vortex particle algorithm By formula: Quantify, where 、 Represent the circulation distribution of the upper and lower rotors respectively, 、 is the induced velocity field; R is the rotor radius, ρ is the air density; The phase difference angle φ and rotor shape parameters are collaboratively iteratively optimized using the NSGA-II multi-objective optimization algorithm to generate a Pareto optimal solution set.

2. The method for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV according to claim 1, characterized in that: Generating basic rotor parameters includes: Determine rotor radius, chord length distribution, airfoil series, and number of blades based on aircraft type and mission profile; Parameterize the design parameters of the forward-swept, backward-swept, and downward-inverted feature points to generate a geometrically sensitive space; A parameter combination is selected within the geometrically sensitive space to construct a basic propeller shape.

3. The method for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV according to claim 1, characterized in that: The free wake model discretizes the blade tip vortex through a viscous vortex particle algorithm and uses a viscous vortex core empirical model to describe the distortion and dissipation of the vortex; The vortex particles are initialized according to the rotor speed and pitch angle, and the wake motion trajectory is tracked by the Lagrangian method; The construction of the free wake model includes: Based on the vorticity-velocity form of the incompressible Navier-Stokes equations, the vortex structure in the flow field is discretized into viscous vortex particles that carry vorticity, position and intensity information. The amount of attached vortex ring on the rotor surface is calculated by combining lifting surface theory, and the newly generated vortex particles are released in real time according to the rotor movement to simulate the generation process of tip vortex and wake vortex. The generation process of the tip vortex and the wake vortex is coupled to output a free wake model.

4. The method for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV according to claim 1, characterized in that: The analysis of transient aerodynamic response by combining the time spectrum method with the multigrid method includes: Capturing the transient aerodynamic characteristics of rotor dynamic stall by time spectrum method; Use multi-grid methods to accelerate flow field solutions to improve the prediction accuracy of aerodynamic shape parameters; The parameters of the rotor shape constraint include: Airfoil profile shape parameters: Optimize leading edge radius, maximum camber position and trailing edge angle based on thin wing theory; Propeller tip geometric characteristic parameters: aerodynamic modification design for noise reduction; Blade span parameters: used for coupled optimization of half span and installation angle; The optimization of the airfoil section shape parameters includes dynamically adjusting the geometric shape under different Reynolds numbers.

5. The method for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV according to claim 1, characterized in that: The rotor design parameters adapted to the plateau environment are generated through a multi-objective optimization algorithm. Specifically, the multi-objective optimization design is carried out through the NSGA-II multi-objective optimization algorithm, and the rotor aerodynamic shape is iteratively optimized through selection, crossover, and mutation genetic operators to obtain the Pareto optimal solution set.

6. An aircraft, characterized in that: The rotor is obtained by optimizing the design according to any one of claims 1 to 5.

7. A system for determining rotor design parameters of a coaxial twin-rotor high-altitude load-carrying UAV, characterized in that: include: The basic rotor modeling module is used to determine the geometric and aerodynamic parameter ranges of the original rotor based on the aircraft parameters and generate basic rotor parameters; The plateau flow field coupling module simulates the aerodynamic load distribution under low-density flow fields by combining the lift-torque dynamics equation with the free wake model; The environmental parameter processing module is used to obtain the temperature, humidity, and altitude of the plateau environment, build a dynamic model to quantify the nonlinear relationship between air density and aerodynamic load under different altitude conditions, and use it to correct the aerodynamic shape parameter mapping rules in the rotor shape constraint design. The Newton iteration method is used to calculate the influence of altitude on aerodynamic load distribution and the rotor power consumption under target thrust. The rotor shape constraint design module is used to perform rotor shape constraint design, map plateau environmental parameters to the rotor twist angle, chord length distribution, and airfoil profile parameters in the basic rotor parameters, analyze the transient aerodynamic response by combining the time spectrum method with the multigrid method, and define a comprehensive optimization objective function based on the transient aerodynamic response results; A multi-objective optimization module is used to generate rotor design parameters adapted to the plateau environment through a multi-objective optimization algorithm based on the comprehensive optimization objective function; The dynamic model is constructed based on the unsteady Navier-Stokes equations and free vortex theory. After inputting the rotor aerodynamic load, the output is the influence of the low-density air on the aerodynamic load and the power consumption. The convergence condition of the Newton iteration method is the speed change threshold. , where n is the rotor speed and m is the number of iterations; the rotor power consumption is calculated by the formula Calculated, where c is the power system efficiency coefficient; the air density is calculated by Calculate, where Altitude The air density at is the air density at sea level, h is the altitude, and H is the attenuation height coefficient; The comprehensive optimization objective function is composed of the sum of the aerodynamic efficiency term and the structural-stability term: the aerodynamic efficiency term is related to lift, power and drag, and the structural-stability term is related to the blade pressure distribution and rotor solidity; the aerodynamic efficiency term is , the structural-stability term is , where P is the power consumption, The maximum power consumed by the rotor in hovering state to generate maximum hovering lift under different atmospheric densities is: is the performance coefficient of the rotor material, is the lift force of the aircraft, The density of the atmosphere in which the aircraft is resistance, is the blade root pressure, is the blade tip pressure, J q is the pressure difference between the upper and lower surfaces of the blade; The rotor is a coaxial twin rotor, and the optimized design includes: The phase difference angle φ between the upper and lower rotors is used as a design variable, and the effect of φ on transient aerodynamic loads is analyzed using the time spectrum method. Calculate the coupling effect of the upper and lower rotor induced velocity fields and lift loss based on the viscous vortex particle algorithm By formula: Quantify, where 、 Represent the circulation distribution of the upper and lower rotors respectively, 、 is the induced velocity field; R is the rotor radius, ρ is the air density; The phase difference angle φ and rotor shape parameters are collaboratively iteratively optimized using the NSGA-II multi-objective optimization algorithm to generate a Pareto optimal solution set.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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