Logistics unmanned aerial vehicle rotor aerodynamic characteristic simulation method based on CFD

Abstract

The invention relates to the technical field of computational fluid mechanics, in particular to a logistics unmanned aerial vehicle rotor aerodynamic characteristic simulation method based on CFD, and the method comprises the following steps: carrying out the simplification and geometric processing of a logistics unmanned aerial vehicle rotor model, building a computational domain containing a rotation domain and a static domain, and carrying out the grid division; importing the divided grid model into a CFD solver, setting a rotation motion condition, a turbulence model and solving parameters of the rotor wing, carrying out iterative calculation until convergence, and obtaining an aerodynamic characteristic report; and based on the aerodynamic characteristic report, generating an aerodynamic characteristic simulation diagram of the logistics unmanned aerial vehicle rotor wing so as to analyze the aerodynamic characteristics. According to the method, lift data can be directly obtained without complex mathematical equations, lift expressions of rotors of different sizes can be conveniently and rapidly compared to guide structural optimization of the rotors and the mounting disc, meanwhile, visual results such as a speed cloud picture, a pressure cloud picture and a trace picture can be generated, and reliable reference is provided for structural improvement of the rotors of the large-load logistics unmanned aerial vehicle.

Description

Technical Field

[0001] This invention relates to the field of computational fluid dynamics, specifically a CFD-based method for simulating the aerodynamic characteristics of a logistics drone rotor. Background Technology

[0002] Heavy-duty logistics drones are core equipment in modern logistics and emergency response, widely used in scenarios such as material distribution in remote areas, transportation of large equipment parts, delivery of emergency relief supplies, and large-scale agricultural material transfer. These drones operate based on a multi-rotor cooperative aerodynamic lift mechanism, using multiple sets of high-power brushless motors to drive the rotor blades at high speeds to generate stable lift, enabling vertical takeoff and landing and hovering. Simultaneously, servo motors adjust the rotational speed and blade pitch angle of each rotor to control flight attitude, speed, and flight path, achieving efficient point-to-point transportation.

[0003] However, the rotor systems of heavy-load logistics drones face stringent aerodynamic performance requirements. On the one hand, under heavy-load conditions, the rotors need to withstand greater aerodynamic loads, resulting in more complex flow field characteristics. Issues such as wingtip vortex interference, unsteady flow fields, and low Reynolds number effects become prominent, directly affecting lift stability and energy utilization efficiency. On the other hand, heavy-load requirements are often accompanied by increased rotor size and multi-rotor collaborative designs, making it difficult for traditional aerodynamic analysis methods to accurately capture the flow field coupling effects between multiple rotors.

[0004] In existing technologies, there is a significant gap in the adaptability of CFD simulation methods for heavy-load logistics drone rotors: most methods are developed based on light and small drones (payload <30kg), and do not fully consider the differences in aerodynamic characteristics under heavy loads, resulting in large deviations between simulation results and actual flight data; at the same time, there is a lack of accurate simulation schemes for the cooperative flow field of heavy-load multi-rotor drones, which makes it difficult to support the optimized design of rotor structures (such as blade size, airfoil, and layout), and easily leads to problems such as insufficient drone payload redundancy, shortened endurance, or excessive energy consumption.

[0005] Therefore, there is an urgent need for a targeted and reliable CFD simulation method to fill the technical gap in the analysis of the rotor aerodynamic characteristics of heavy-duty logistics drones. Summary of the Invention

[0006] The purpose of this invention is to provide a CFD-based simulation method for the aerodynamic characteristics of logistics drone rotors, in order to solve the problem that existing simulation methods are not applicable to the rotors of heavy-load logistics drones.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a CFD-based method for simulating the aerodynamic characteristics of a logistics drone rotor, comprising the following steps:

[0008] S1. CFD Preprocessing: Simplify and geometrically process the rotor model of the logistics drone, establish a computational domain including the rotation domain and the stationary domain, and perform mesh generation;

[0009] S2, CFD Solution: Import the meshed model into the CFD solver, set the rotor rotation conditions, turbulence model and solution parameters, perform iterative calculations until convergence, and obtain an aerodynamic characteristic report containing rotor lift and lift coefficient.

[0010] S3. CFD Post-processing: Based on the aerodynamic characteristic report, generate an aerodynamic characteristic simulation diagram of the logistics drone rotor on the rotor's symmetry plane to analyze the aerodynamic characteristics.

[0011] Preferably, the rotor model of the logistics drone in step S1 is a complete model including multiple rotors, arms and a central mounting plate;

[0012] The simplification and geometric processing includes: removing the central mounting plate, arms and central mounting holes from the whole model that have no substantial impact on aerodynamic characteristics, to obtain a simplified model containing only multiple isolated rotors;

[0013] The sharp areas at the tips of the rotor blades are rounded and smoothed.

[0014] Preferably, the computational domain in step S1 specifically includes:

[0015] For each rotor in the simplified model, create a cylindrical rotor domain shell that surrounds that rotor;

[0016] Create a cuboid global computational domain shell that surrounds all the cylindrical rotor domain shells;

[0017] By using Boolean operations, independent sub-rotation domains containing the corresponding rotor entities are extracted from the interior of each cylindrical rotor domain shell.

[0018] Merge all the independent sub-rotation domains to form a unified rotation domain;

[0019] By performing Boolean operations between the outer shell of the cuboid's overall computational domain and the overall rotation domain, the outer static domain is extracted;

[0020] The overall rotating domain and the stationary domain together constitute the computational domain for CFD calculations.

[0021] Preferably, in the calculation domain of step S1:

[0022] The diameter of the cylindrical rotor shell is 1.4 times the rotor diameter;

[0023] The length and width of the outer shell of the cuboid overall computational domain are 9 times the rotor length and diameter, respectively;

[0024] The distance from the inlet surface of the computing domain shell to the rotor rotation center is 4 times that of the rotor;

[0025] The distance from the exit surface of the computing domain shell to the rotor rotation center is 12 times that of the rotor.

[0026] Preferably, the mesh division in step S1 is a non-uniform mesh division, specifically including:

[0027] The first unit size is set on the rotor surface to refine the mesh;

[0028] The rotation domain is meshed by setting a second unit size larger than the first unit size;

[0029] The interface between the rotating domain and the stationary domain is meshed by setting a third unit size larger than the second unit size;

[0030] The static domain is meshed by setting a fourth unit size that is larger than the third unit size.

[0031] Preferably, obtaining the rotor's aerodynamic characteristics report in step S2 specifically includes:

[0032] Set the turbulence model to the Spalart-Allmaras single-equation model;

[0033] In the unit region conditions, define the mesh motion for the rotation domain corresponding to each rotor, set the rotation speed, rotation center coordinates and rotation axis direction vector; and set the surface type of all rotors to moving wall.

[0034] The solution method is set to the pressure-based SIMPLE algorithm, and the discretization schemes for the momentum equation and turbulence-related terms are both set to second-order upwind schemes.

[0035] Create a force report in the report definition and set the force vector to a direction perpendicular to the rotor's plane of rotation to obtain the rotor's lift or lift coefficient;

[0036] The computational domain is initialized, and the number of iteration steps is set for steady-state calculation. When the monitored lift coefficient residual is less than the set threshold, it is determined to be converged, and the aerodynamic characteristic report is output based on the converged flow field data.

[0037] Preferably, the aerodynamic characteristic simulation diagram in step S3 includes a cloud diagram and a trace diagram.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

[0039] This invention simplifies the model, constructs the computational domain and meshes the computational domain in CFD preprocessing, sets precise parameters and iteratively calculates in the solution stage, and performs visualization analysis in post-processing. It can directly obtain rotor lift data that is basically consistent with the actual situation without complex mathematical equations. It can also accurately capture complex flow field characteristics such as wingtip vortex interference and unsteady flow field under heavy load conditions, as well as the flow field coupling effect between multiple rotors. It fills the technical gap in the simulation of rotor aerodynamic characteristics of heavy-load logistics UAVs. It can quickly compare the lift performance of rotors of different sizes to intuitively guide the structural optimization of rotors and mounting disks. At the same time, it can clearly analyze the airflow conditions by generating visualization results such as velocity cloud maps, pressure cloud maps, and trace maps. It effectively solves the problems of poor adaptability and large simulation deviation of traditional light and small UAV simulation methods, and improves the situation of insufficient payload redundancy, shortened endurance and excessive energy consumption of UAVs. It provides a reliable reference for the rotor structure optimization of heavy-load logistics UAVs. Attached Figure Description

[0040] Figure 1 This is a schematic flowchart of the overall process of the CFD-based simulation method for the rotor aerodynamic characteristics of a logistics drone according to the present invention.

[0041] Figure 2 This is a schematic diagram of the rotor structure of a logistics drone, based on the CFD-based method for simulating the aerodynamic characteristics of the drone rotor according to the present invention. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Please see Figure 1-2 This invention provides a technical solution: a CFD-based method for simulating the aerodynamic characteristics of a logistics drone rotor, comprising the following steps:

[0044] S1. CFD Preprocessing: The rotor model of the logistics drone is simplified and geometrically processed to establish a computational domain including rotational and stationary domains, and meshing is performed. Specifically:

[0045] S1.1 Remove the center mounting plate and arms from the initial model of the logistics drone rotor, and smooth the rounded corners to obtain a simplified model of the logistics drone rotor; the initial model of the logistics drone rotor includes six rotors distributed in a regular hexagonal shape, arms, and a center mounting plate for overall assembly. The simplified model is as follows: Figure 2As shown. In this embodiment, SolidWorks software is used to simplify the initial model and export it as a *.STEP format;

[0046] When the rotor of a logistics drone is working, the central mounting hole of the rotor will affect the direction of airflow; moreover, in the actual installation process, the central mounting hole needs to be connected to the servo motor and there will be no gap. Therefore, in order to make the simulation closer to the actual effect, the present invention removes the central mounting hole to simplify the model.

[0047] During the process of drawing the mesh and setting conditions for subsequent simulation calculations, the connection structure needs to be extracted separately to make it independent; otherwise, interference will occur. Therefore, it is removed during simplification.

[0048] The sharp corners at the top of the rotor model can affect the realism of the simulation, so the corners need to be smoothed out.

[0049] S1.2. Import the simplified model obtained in step 1.1 into the SpaceClaim software in CFD; draw the outer shell of the six rotors and the overall shell: the rotor domain shell is a cylinder and the overall shell is a cuboid. In this embodiment, the ANSYS Workbench software is opened, a Fluent simulation module is created, and in the first geometry item, the exported *.STEP format file is imported into the SpaceClaim software. In the SpaceClaim software, a cylindrical rotor domain shell is drawn at one rotor position, with a size slightly larger than the rotor size. Then, the cylindrical rotor domain shells are drawn sequentially for the other five rotors, using the same method. Next, the computational domain shell is drawn, with the shell shape selected as a cuboid and the region selected as all solids. It needs to be as large as possible to prevent airflow obstruction, which would affect the simulation results. The cylindrical rotor domain shell simulates the cylindrical region formed by rotor rotation, so the cylindrical shape is chosen. The shape of the computational domain shell does not have a significant impact. The cuboid shape is used for more flexible setting of operating conditions. In this embodiment, the diameter of the cylindrical rotor domain shell is 1.4 times the rotor diameter, the length and width of the computational domain are 9 times the rotor diameter, the distance from the inlet of the computational domain shell to the rotor is 4 times the rotor diameter, and the distance from the outlet to the rotor is 12 times the rotor diameter.

[0050] In DesignModeler, Boolean operations are performed on the overall shell to extract the shells of the six rotors and each rotor; Boolean operations are performed on the shells of the six rotors respectively to extract the independent sub-rotation domains of each rotor after removing the solid structure; the six independent sub-rotation domains are merged to form an overall rotation domain that includes the entire range of motion of the six rotors. This overall rotation domain and the surrounding stationary sub-domain together constitute a complete computational domain.

[0051] The rotation domain and the stationary domain are combined into a geometric model part, thereby realizing the shared topology of the rotation domain and the stationary domain;

[0052] S1.3. Import the geometric model part into the Meshing software in CFD, and name the outlet and inlet of the stationary domain; select the hexacoach surface, set the element size to 5mm, and generate the local mesh for the rotor; select the global rotating domain, set the element size to 20mm, and generate the local mesh for the global rotating domain; select the interface between the global rotating domain and the stationary domain, set the element size to 50mm, and generate the local mesh for the interface; select the stationary domain, set the element size to 150mm, and generate the local mesh for the stationary domain. In this embodiment, each part is named first: the stationary domain is named wailiuchang, and the inlet and outlet are named respectively; the hexacoach surface is collectively named fan, and the rotating domain is collectively named xuan; the interface between the global rotating domain and the stationary domain is named jiaojie; in the mesh options of the Meshing software, add face size adjustment, select the geometry to be meshed as the local area, set the element size, check capture curvature and capture proximity, set dilation, and perform mesh generation. The element size can be modified as needed; after the mesh is generated, check the mesh quality, select skewness, and it should not exceed 0.9.

[0053] S2. CFD Solution: Import the meshed model into the CFD solver, set the rotor rotation conditions, turbulence model, and solution parameters, and perform iterative calculations until convergence. Obtain an aerodynamic characteristic report containing rotor lift and lift coefficient, specifically:

[0054] S2.1 Update the local mesh obtained in step 1 to the F1uent software in CFD;

[0055] The model selected is the Spalart-Allmaras single-equation model;

[0056] S2.2 In the unit region conditions, set the six rotors: Select mesh motion and set the rotation speed, rotation center, and rotation axis direction of the six rotors respectively. Specify the rotation axis direction (such as Z-axis) and the coordinates of the rotation center, and set the rotation speed to 2800 rpm; In the boundary conditions, set the surface of the six rotors as a moving wall, and its motion is associated with the adjacent rotation domain.

[0057] S2.3 Set the solution method to SIMPLE, and select SecondOrderUpwind for momentum, hysteresis kinetic energy, and end flow dissipation rate. Selecting higher-order relaxation terms can better simulate the rotor rotation and make the experimental results more accurate.

[0058] S2.4. Set the lift in the aerodynamic report of the logistics drone rotor. Set the normal lift to be solved, create a force or lift definition in the aerodynamic characteristic report definition, and set the inverse vector direction to the vector direction of the rotor normal force. The report output type can be selected as lift or lift coefficient, and the region can be selected as logistics drone rotor;

[0059] CFD simulation can directly obtain the rotor normal force (lift in the report) without the need for complex mathematical equations and formulas. It is intuitive, simple and convenient, and the results obtained are basically consistent with the actual situation.

[0060] S2.5 Initialize and set the number of iteration steps. Upon reaching steady-state convergence, obtain the aerodynamic report of the logistics drone rotor. Perform standard initialization of the above settings. If no errors are found, steady-state iterative calculations can be performed. Simulation verification using Fluent software shows that with approximately 1800 calculation steps, the rotor blades can complete ten rotations and reach steady-state convergence, obtaining a stable target value. Fluent software judges convergence based on the stability of the defined target value. Convergence is achieved when the difference between the current calculation and the previous calculation is less than a small value, where the small value ranges from 10. -4 ~10 -7 Convergence is defined as the residual lift coefficient being less than 10⁻⁴ to 10⁻⁷.

[0061] S3. CFD Post-processing: Based on the aerodynamic characteristic report, generate an aerodynamic characteristic simulation diagram of the logistics drone rotor on the rotor's symmetry plane to analyze the aerodynamic characteristics. Specifically, import the aerodynamic characteristic report of the logistics drone rotor obtained in step 2 into CFD-Post, and establish a plane Plane that coincides with the rotor's symmetry plane. Select the type of cloud map to generate on the plane Plane and generate the corresponding cloud map. Draw traces on the plane Plane to generate a trace map.

[0062] In this embodiment, after creating the Plane, create a new contour, select Location on the Plane, select Velocity to draw the velocity contour, select Pressure to draw the pressure contour, and select Local for the Range. This will automatically locate the highest and lowest values. Alternatively, create a new vector to draw a trace diagram, which will show the airflow and allow for the analysis of turbulence.

[0063] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0064] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A CFD-based method for simulating the aerodynamic characteristics of a logistics drone rotor, characterized by: Includes the following steps: S1. CFD Preprocessing: Simplify and geometrically process the rotor model of the logistics drone, establish a computational domain including the rotation domain and the stationary domain, and perform mesh generation; S2, CFD Solution: Import the meshed model into the CFD solver, set the rotor rotation conditions, turbulence model and solution parameters, perform iterative calculations until convergence, and obtain an aerodynamic characteristic report containing rotor lift and lift coefficient. S3. CFD Post-processing: Based on the aerodynamic characteristic report, generate an aerodynamic characteristic simulation diagram of the logistics drone rotor on the rotor's symmetry plane to analyze the aerodynamic characteristics.

2. The CFD-based method for simulating the aerodynamic characteristics of a logistics drone rotor as described in claim 1, characterized in that: The rotor model of the logistics drone in step S1 is a complete model that includes multiple rotors, arms and a central mounting plate. The simplification and geometric processing includes: removing the central mounting plate, arms and central mounting holes from the whole model that have no substantial impact on aerodynamic characteristics, to obtain a simplified model containing only multiple isolated rotors; The sharp areas at the tips of the rotor blades are rounded and smoothed.

3. The CFD-based method for simulating the aerodynamic characteristics of a logistics drone rotor as described in claim 2, characterized in that: The computational domain in step S1 specifically includes: For each rotor in the simplified model, create a cylindrical rotor domain shell that surrounds that rotor; Create a cuboid global computational domain shell that surrounds all the cylindrical rotor domain shells; By using Boolean operations, independent sub-rotation domains containing the corresponding rotor entities are extracted from the interior of each cylindrical rotor domain shell. Merge all the independent sub-rotation domains to form a unified rotation domain; By performing Boolean operations between the outer shell of the cuboid's overall computational domain and the overall rotation domain, the outer static domain is extracted; The overall rotating domain and the stationary domain together constitute the computational domain for CFD calculations.

4. The CFD-based method for simulating the aerodynamic characteristics of a logistics drone rotor according to claim 3, characterized in that: In the calculation domain of step S1: The diameter of the cylindrical rotor shell is 1.4 times the rotor diameter; The length and width of the outer shell of the cuboid overall computational domain are 9 times the rotor length and diameter, respectively; The distance from the inlet surface of the computing domain shell to the rotor rotation center is 4 times that of the rotor; The distance from the exit surface of the computing domain shell to the rotor rotation center is 12 times that of the rotor.

5. The CFD-based method for simulating the aerodynamic characteristics of a logistics drone rotor according to claim 4, characterized in that: In step S1, the mesh is divided into a non-uniform mesh, specifically including: The first unit size is set on the rotor surface to refine the mesh; The rotation domain is meshed by setting a second unit size larger than the first unit size; The interface between the rotating domain and the stationary domain is meshed by setting a third unit size larger than the second unit size; The static domain is meshed by setting a fourth unit size that is larger than the third unit size.

6. The CFD-based method for simulating the aerodynamic characteristics of a logistics drone rotor according to claim 5, characterized in that: The specific steps in step S2 to obtain the rotor's aerodynamic characteristics report include: Set the turbulence model to the Spalart-Allmaras single-equation model; In the unit region conditions, define the mesh motion for the rotation domain corresponding to each rotor, set the rotation speed, rotation center coordinates, and rotation axis direction vector; and set the surface type of all rotors to moving wall. The solution method is set to the pressure-based SIMPLE algorithm, and the discretization schemes for the momentum equation and turbulence-related terms are both set to second-order upwind schemes. Create a force report in the report definition and set the force vector to a direction perpendicular to the rotor's plane of rotation to obtain the rotor's lift or lift coefficient; The computational domain is initialized, and the number of iteration steps is set for steady-state calculation. When the monitored lift coefficient residual is less than the set threshold, it is determined to be converged, and the aerodynamic characteristic report is output based on the converged flow field data.

7. The CFD-based method for simulating the aerodynamic characteristics of a logistics drone rotor according to claim 6, characterized in that: The aerodynamic characteristic simulation diagram in step S3 includes a cloud diagram and a trace diagram.

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