Fan blade airfoil optimization design method, system, device and medium

Abstract

This invention discloses a method, system, equipment, and medium for optimizing the airfoil design of wind turbine blades. The method includes: adjusting the airfoil geometry parameters of the blade to be optimized to obtain several blade models with different airfoil geometry parameters; constructing several 3D flow field models around the blade models with different airfoil geometry parameters based on these models; performing gas-solid two-phase flow simulation analysis on the 3D flow field models of the blade models with different airfoil geometry parameters to obtain the critical Stokes number for airfoil wear under different airfoil geometry parameters; and obtaining the optimal design result for the airfoil geometry parameters of the blade to be optimized based on the critical Stokes number for airfoil wear under different airfoil geometry parameters. This invention utilizes numerical simulation for blade airfoil design, resulting in a simple design process, high accuracy, and effectively improving the durability of the blades and the stability and economy of the entire wind turbine.

Description

Technical Field

[0001] This invention belongs to the field of wind turbine design technology, and specifically relates to a method, system, equipment and medium for optimizing the airfoil design of wind turbine blades. Background Technology

[0002] A fan is a type of fluid machinery that converts the mechanical energy of a prime mover into the pressure potential energy and kinetic energy of a fluid. In practical applications, most fans work on a gas-solid two-phase medium, such as raw material fans in cement plants. After the impeller of a fan draws in gas containing solid particles, the particle flow trajectory is complex and different from the flow trajectory of the fluid. This causes blade wear problems to occur in such fans during short-term operation, which will seriously reduce industrial production efficiency and may even lead to production accidents in severe cases.

[0003] Currently, existing blade wear protection designs are mainly divided into two categories: one is passive wear protection methods, which mainly treat the material surface, such as plating hard metals on the material surface to improve the wear resistance of the material itself; the other is active wear protection methods, namely aerodynamic wear protection methods, which mainly consider flow characteristics and control, improve and optimize flow parameters. Among them, although passive wear protection methods can ensure the normal operation of the blade for a certain period of time, they cannot completely eliminate blade wear. In order to achieve the active wear protection effect of the blade, the airfoil accuracy requirements are high. Existing blade airfoil design methods cannot meet the airfoil accuracy requirements, and the blade airfoil design process is very difficult. Summary of the Invention

[0004] In view of the technical problems existing in the prior art, the present invention provides a wind turbine blade airfoil optimization design method, system, equipment and medium to solve the technical problem that the existing blade airfoil design methods cannot meet the airfoil accuracy requirements and the airfoil design process is very difficult when achieving the active anti-wear effect of the blade.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] This invention provides a method for optimizing the airfoil design of wind turbine blades, comprising:

[0007] Step 1: Adjust the airfoil geometry parameters of the blade to be optimized to obtain several blade models with different airfoil geometry parameters;

[0008] Step 2: Based on the blade models with different airfoil geometric parameters, construct 3D flow field models around the blade models with different airfoil geometric parameters.

[0009] Step 3: Perform gas-solid two-phase flow simulation analysis on the 3D flow field models of several blade models with different airfoil geometric parameters to obtain the critical Stokes number of airfoil wear under different airfoil geometric parameters.

[0010] Step 4: Based on the critical Stokes number of airfoil wear under different airfoil geometric parameters, obtain the optimal design result of the airfoil geometric parameters of the blade to be optimized.

[0011] Furthermore, in step 1, the airfoil geometry parameters of the blade to be optimized are one of the following: airfoil leading edge radius, airfoil maximum thickness, airfoil maximum thickness position, and airfoil maximum curvature position.

[0012] Furthermore, in step 2, 3D modeling software is used to construct 3D flow field models around blade models with different airfoil geometric parameters based on the blade models with different airfoil geometric parameters.

[0013] Furthermore, the 3D modeling software includes Solidworks software.

[0014] Furthermore, in step 3, computational fluid dynamics software is used to perform gas-solid two-phase flow simulation analysis on the 3D flow field models of blade models with different airfoil geometric parameters to obtain the critical particle diameter and critical Stokes number of airfoil wear under different airfoil geometric parameters.

[0015] Furthermore, using computational fluid dynamics software, gas-solid two-phase flow simulation analysis was performed on 3D flow field models of blades with several different airfoil geometric parameters. The process of obtaining the critical particle diameter and critical Stokes number for airfoil wear under different airfoil geometric parameters is as follows:

[0016] Using computational fluid dynamics software, the motion of gas-solid two-phase flow of particles with different diameters in a 3D flow field model around a blade model with several different airfoil geometric parameters was simulated, and the simulation results of the motion trajectory of gas-solid two-phase flow of particles with different diameters were obtained.

[0017] Based on the simulation results of the motion trajectory of gas-solid two-phase flow of particles with different diameters, the critical particle diameter under different airfoil geometric parameters is obtained.

[0018] Based on the critical particle diameter under different airfoil geometric parameters, the critical Stokes number for airfoil wear under different airfoil geometric parameters is obtained.

[0019] Furthermore, in step 4, the process of obtaining the optimal design result of the airfoil geometry parameters of the blade to be optimized based on the critical Stokes number of airfoil wear under different airfoil geometry parameters is as follows:

[0020] The airfoil geometry parameters corresponding to the maximum critical Stokes number for airfoil wear are taken as the optimal design result for the airfoil geometry parameters of the blade to be optimized.

[0021] The present invention also provides a wind turbine blade airfoil optimization design system, comprising:

[0022] The blade model module is used to adjust the airfoil geometry parameters of the blade to be optimized, and obtain blade models with several different airfoil geometry parameters.

[0023] The flow field model module is used to construct a 3D flow field model around a blade model with several different airfoil geometric parameters based on the blade models with several different airfoil geometric parameters.

[0024] The simulation analysis module is used to perform gas-solid two-phase flow simulation analysis on the 3D flow field model of several blade models with different airfoil geometric parameters, and to obtain the critical Stokes number of airfoil wear under different airfoil geometric parameters.

[0025] The results output module obtains the optimal design results of the airfoil geometry parameters of the blade to be optimized based on the critical Stokes number of airfoil wear under different airfoil geometry parameters.

[0026] This invention also provides a wind turbine blade airfoil optimization design device, including...

[0027] Memory, used to store computer programs;

[0028] A processor is used to execute the computer program to implement the steps of the wind turbine blade airfoil optimization design method.

[0029] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the wind turbine blade airfoil optimization design method.

[0030] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0031] This invention provides a method and system for optimizing the airfoil design of wind turbine blades. It involves performing gas-solid two-phase flow simulation analysis on 3D flow field models of blades with different airfoil geometric parameters. By changing the flow field around the blade, the critical Stokes number for airfoil wear under different airfoil geometric parameters is obtained. Based on the critical Stokes number for airfoil wear under different airfoil geometric parameters, the optimal design result of the airfoil size of the blade to be optimized is determined. The optimized wind turbine blade can form a stable air film on its surface to isolate dust-laden air from contact with the blade, thereby mitigating or eliminating blade wear and achieving aerodynamic anti-wear effects. The use of numerical simulation for blade airfoil design is simple, yields high accuracy, and effectively improves the durability of the blades and the stability and economy of the entire wind turbine. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the blade model with different airfoil geometric parameters in Example 1;

[0033] Figure 2 This is a particle trajectory diagram for a 16μm particle size when the airfoil leading edge radius is 0.35% c, as shown in Example 1.

[0034] Figure 3 This is a particle trajectory diagram for a 17μm particle size when the airfoil leading edge radius is 0.35% c, as shown in Example 1.

[0035] Figure 4 This is a particle trajectory diagram for a 20 μm particle size when the airfoil leading edge radius is 0.43% c, as shown in Example 1.

[0036] Figure 5 This is a particle trajectory diagram for a 21 μm particle size when the airfoil leading edge radius is 0.43% c, as shown in Example 1.

[0037] Figure 6 This is a particle trajectory diagram for a 25μm particle size when the airfoil leading edge radius is 0.61%c, as shown in Example 1.

[0038] Figure 7 This is a particle trajectory diagram for a 26μm particle size at a leading edge radius of 0.61% c in Example 1;

[0039] Figure 8 This is a particle trajectory diagram for a 25μm particle size when the airfoil leading edge radius is 0.70% c, as shown in Example 1.

[0040] Figure 9 This is a particle trajectory diagram for a 26μm particle size at a leading edge radius of 0.70% c in Example 1;

[0041] Figure 10 This is a graph showing the variation of the critical Stokes number under different leading edge diameters in Example 1;

[0042] Figure 11 This is a schematic diagram of the blade model with different airfoil geometric parameters in Example 2;

[0043] Figure 12 This is an enlarged view of the leading edge portion of the blade model with different airfoil geometric parameters in Example 2;

[0044] Figure 13 This is a particle trajectory diagram of a 13μm particle at the maximum curvature position of 25.8%c in Example 2;

[0045] Figure 14 This is a particle trajectory diagram of a 14μm particle at the maximum curvature position of 25.8%c in Example 2;

[0046] Figure 15 This is a particle trajectory diagram of a 25μm particle at the maximum curvature position of 34.6%c in Example 2;

[0047] Figure 16 This is a particle trajectory diagram of a 26μm particle at the maximum curvature position of 34.6%c in Example 2;

[0048] Figure 17 This is a trajectory diagram of the leading edge of a 22μm particle at the maximum curvature position of 52.2%c in Example 2;

[0049] Figure 18 This is a trajectory diagram of the leading edge of a 23μm particle at the maximum curvature position of 52.2%c in Example 2;

[0050] Figure 19 This is a trajectory diagram of the tail edge of a 23μm particle at the maximum curvature position of 52.2%c in Example 2;

[0051] Figure 20 This is a trajectory diagram of the leading edge of a 10μm particle at the maximum curvature position of 61.1%c in Example 2;

[0052] Figure 21 This is a trajectory diagram of the leading edge of an 11μm particle at the maximum curvature position of 61.1%c in Example 2;

[0053] Figure 22 This is a trajectory diagram of the trailing edge of an 11μm particle at the maximum curvature position of 61.1%c in Example 2;

[0054] Figure 23 This is a graph showing the change in the critical Stokes number at different maximum surface positions in Example 2. Detailed Implementation

[0055] To make the technical problems solved by the present invention, the technical solutions, and the beneficial effects clearer, the following specific embodiments provide a further detailed description of the present invention. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of the invention.

[0056] This invention provides a method for optimizing the airfoil of wind turbine blades, comprising the following steps:

[0057] Step 1: Obtain the original design values ​​of the airfoil geometry parameters of the blade to be optimized; wherein, the airfoil geometry parameters of the blade to be optimized are one of the following: airfoil leading edge radius, airfoil maximum thickness, airfoil maximum thickness position, and airfoil maximum curvature position.

[0058] Step 2: Based on the original design values ​​of the airfoil geometry parameters of the blade to be optimized, and combined with the range of possible values ​​of the airfoil geometry parameters of the blade to be optimized, adjust the airfoil geometry parameters of the blade to be optimized to obtain several blade models with different airfoil geometry parameters.

[0059] Step 3: Based on the blade models with different airfoil geometric parameters, construct a 3D flow field model around the blade models with different airfoil geometric parameters; specifically, using 3D modeling software, construct a 3D flow field model around the blade models with different airfoil geometric parameters; wherein, the 3D modeling software includes Solidworks software.

[0060] Step 4: Perform gas-solid two-phase flow simulation analysis on the 3D flow field models of blade models with different airfoil geometric parameters to obtain the critical Stokes number of airfoil wear under different airfoil geometric parameters.

[0061] The specific process is as follows:

[0062] The 3D flow field models around blades with different airfoil geometric parameters were meshed to obtain several meshed 3D flow field models.

[0063] Using computational fluid dynamics software, the motion of gas-solid two-phase flow of particles with different diameters in a 3D flow field model after several grid divisions was simulated, and the simulation results of the motion trajectory of gas-solid two-phase flow of particles with different diameters were obtained.

[0064] Based on the simulation results of the motion trajectory of gas-solid two-phase flow of particles with different diameters, the critical particle diameter under different airfoil geometric parameters is obtained.

[0065] Based on the critical particle diameter under different airfoil geometric parameters, the critical Stokes number for airfoil wear under different airfoil geometric parameters is obtained.

[0066] Step 5: Based on the critical Stokes number of airfoil wear under different airfoil geometric parameters, obtain the optimization range of the design results of the airfoil geometric parameters of the blade to be optimized; wherein, the airfoil geometric parameter corresponding to the maximum critical Stokes number of airfoil wear is taken as the optimization design result of the airfoil geometric parameters of the blade to be optimized, and the optimization range of the design results of the airfoil geometric parameters of the blade to be optimized is obtained based on the optimization design result of the airfoil geometric parameters of the blade to be optimized.

[0067] Step 6: Take the optimized range of the design results of the airfoil geometry parameters of the blade to be optimized as the range of possible values ​​of the airfoil geometry parameters of the blade to be optimized, and repeat the above steps 2-5 to obtain the optimal design results of the airfoil geometry parameters of the blade to be optimized.

[0068] Design principles:

[0069] The wind turbine blade airfoil optimization method of this invention involves adjusting the airfoil geometry parameters of the blade to be optimized to establish several blade models with different airfoil geometry parameters; constructing several 3D flow field models around the blade models with different airfoil geometry parameters based on these models; using the 3D flow field model of each airfoil geometry parameter blade model as the research scope and computational domain for gas-solid two-phase flow simulation; performing gas-solid two-phase flow simulation analysis on the 3D flow field model of each airfoil geometry parameter blade model, including particles of different diameters, to obtain the motion trajectory of particles of different diameters in the 3D flow field model of the blade models with different airfoil geometry parameters; and then performing simulation analysis on the particles of different diameters in the airfoil geometry parameters. The motion trajectory analysis of the 3D flow field model around the blade model with different airfoil geometric parameters yields the critical particle diameter under different airfoil geometric parameters. Specifically, when the particle size is smaller than a certain specific size, no wear occurs on the airfoil surface; however, when the particle size is larger than this specific size, airfoil wear occurs, and the amount of wear increases with the increase of particle size. In this case, the specific particle size is taken as the critical particle diameter. Based on the critical particle diameter under different airfoil geometric parameters, the critical Stokes number of airfoil wear under different airfoil geometric parameters is calculated. Finally, the airfoil geometric parameters corresponding to the maximum critical Stokes number of airfoil wear are taken as the optimal design result of the airfoil geometric parameters of the blade to be optimized.

[0070] The wind turbine blade airfoil optimization design method described in this invention changes the flow field around the airfoil by adjusting its geometric dimensions, forming a stable air film on the blade surface. This film isolates dust-laden air from contacting the blade, thereby mitigating or eliminating blade wear. This invention relies on computer numerical simulation, making it easy to implement and significantly improving the blade's wear resistance. Compared to traditional wear-resistant methods, it reduces the wear resistance requirements of materials, offering better economic efficiency. Theoretically, it can provide a longer-lasting wear-resistant effect.

[0071] This invention also provides a wind turbine blade airfoil optimization design system, including a blade model module, a flow field model module, a simulation analysis module, and a result output module. The blade model module is used to adjust the airfoil geometry parameters of the blade to be optimized, obtaining several blade models with different airfoil geometry parameters. The flow field model module is used to construct several 3D flow field models around the blade models with different airfoil geometry parameters based on the several blade models with different airfoil geometry parameters. The simulation analysis module is used to perform gas-solid two-phase flow simulation analysis on the 3D flow field models of the blade models with different airfoil geometry parameters, respectively, to obtain the critical Stokes number of airfoil wear under different airfoil geometry parameters. The result output module obtains the optimal design result of the airfoil geometry parameters of the blade to be optimized based on the critical Stokes number of airfoil wear under different airfoil geometry parameters.

[0072] The present invention also provides a wind turbine blade airfoil optimization design device, comprising: a memory for storing a computer program; and a processor for executing the computer program to implement the steps of the wind turbine blade airfoil optimization design method.

[0073] When the processor executes the computer program, it implements the steps of the above-mentioned wind turbine blade airfoil optimization design method, for example: adjusting the airfoil geometry parameters of the blade to be optimized to obtain several blade models with different airfoil geometry parameters; constructing several 3D flow field models around the blade models with different airfoil geometry parameters based on the several blade models with different airfoil geometry parameters; performing gas-solid two-phase flow simulation analysis on the 3D flow field models of the blade models with different airfoil geometry parameters respectively to obtain the critical Stokes number of airfoil wear under different airfoil geometry parameters; and obtaining the optimal design result of the airfoil geometry parameters of the blade to be optimized based on the critical Stokes number of airfoil wear under different airfoil geometry parameters.

[0074] Alternatively, when the processor executes the computer program, it implements the functions of each module in the above system, such as: a blade model module, used to adjust the airfoil geometry parameters of the blade to be optimized to obtain several blade models with different airfoil geometry parameters; a flow field model module, used to construct several 3D flow field models around the blade models with different airfoil geometry parameters based on the several blade models with different airfoil geometry parameters; a simulation analysis module, used to perform gas-solid two-phase flow simulation analysis on the 3D flow field models of the blade models with several different airfoil geometry parameters to obtain the critical Stokes number of airfoil wear under different airfoil geometry parameters; and a result output module, used to obtain the optimal design result of the airfoil geometry parameters of the blade to be optimized based on the critical Stokes number of airfoil wear under different airfoil geometry parameters.

[0075] For example, the computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing preset functions, wherein the instruction segments describe the execution process of the computer program in the wind turbine blade airfoil optimization design device. For example, the computer program can be divided into a blade model module, a flow field model module, a simulation analysis module, and a result output module. The specific functions of each module are as follows: The blade model module is used to adjust the airfoil geometry parameters of the blade to be optimized to obtain several blade models with different airfoil geometry parameters; the flow field model module is used to construct several 3D flow field models around the blade models with different airfoil geometry parameters based on the several blade models with different airfoil geometry parameters; the simulation analysis module is used to perform gas-solid two-phase flow simulation analysis on the 3D flow field models of the blade models with several different airfoil geometry parameters to obtain the critical Stokes number of airfoil wear under different airfoil geometry parameters; the result output module obtains the optimal design result of the airfoil geometry parameters of the blade to be optimized based on the critical Stokes number of airfoil wear under different airfoil geometry parameters.

[0076] The wind turbine blade airfoil optimization design equipment can be a desktop computer, laptop, handheld computer, or cloud server, etc. The equipment may include, but is not limited to, processors and memory. Those skilled in the art will understand that the above are examples of wind turbine blade airfoil optimization design equipment and do not constitute a limitation on the equipment. It may include more components than described above, or combine certain components, or use different components. For example, the equipment may also include input / output devices, network access devices, buses, etc.

[0077] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or any conventional processor. The processor is the control center of the wind turbine blade airfoil optimization design equipment, connecting all parts of the equipment via various interfaces and lines.

[0078] The memory can be used to store the computer program and / or modules. The processor realizes various functions of the wind turbine blade airfoil optimization design equipment by running or executing the computer program and / or modules stored in the memory and calling the data stored in the memory.

[0079] The memory may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function (such as sound playback or image playback). The data storage area may store data created based on the use of the phone (such as audio data or a phonebook). Furthermore, the memory may include high-speed random access memory (RAM) and non-volatile memory, such as hard disks, RAM, plug-in hard disks, SmartMediaCards (SMC), Secure Digital (SD) cards, flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0080] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the wind turbine blade airfoil optimization design method.

[0081] If the modules / units integrated in the wind turbine blade airfoil optimization design system are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0082] Based on this understanding, the present invention can implement all or part of the processes in the above-described wind turbine blade airfoil optimization design method, or it can be accomplished by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the above-described wind turbine blade airfoil optimization design method. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or a preset intermediate form, etc.

[0083] The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0084] It should be noted that the content contained in the computer-readable storage medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable storage medium does not include electrical carrier signals and telecommunication signals.

[0085] Example 1

[0086] In this embodiment 1, the optimization design process of the airfoil leading edge radius of the A18 wind turbine blade is taken as an example.

[0087] This embodiment 1 provides a method for optimizing the airfoil of a wind turbine blade, including the following steps:

[0088] Step 1: Obtain the original design parameters of the airfoil leading edge radius of the blade to be optimized; wherein, the original design parameters of the airfoil leading edge radius of the blade to be optimized are 0.52%c.

[0089] Step 2: Based on the original design parameters of the airfoil leading edge radius of the blade to be optimized, and considering the possible value range of the airfoil leading edge radius, adjust the parameters of the airfoil leading edge radius to obtain several blade models with different airfoil leading edge radii. These models include blade models with airfoil radii of 0.35%c, 0.43%c, 0.61%c, and 0.70%c, as shown in the attached figure. Figure 1 As shown.

[0090] Step 3: Using Solidworks software, construct 3D flow field models around blade models with different airfoil leading edge radii based on the blade models with different airfoil leading edge radii.

[0091] Step 4: Perform gas-solid two-phase flow simulation analysis on the 3D flow field models of blade models with different airfoil leading edge radii to obtain the critical Stokes number of airfoil wear under different airfoil leading edge radii.

[0092] The specific process is as follows:

[0093] The 3D flow field models around blades with different leading edge radii were meshed to obtain several meshed 3D flow field models.

[0094] Using computational fluid dynamics software, the motion of gas-solid two-phase flow involving particles of different diameters was simulated in a 3D flow field model with several meshes. The simulation results of the motion trajectories of the gas-solid two-phase flow with particles of different diameters were obtained. In the gas-solid two-phase flow simulation analysis, an inlet velocity of 14.6 m / s and a solid particle density of 1550 kg / m³ were set at a 6° angle of attack. -3 ;

[0095] Based on the simulation results of the motion trajectory of gas-solid two-phase flow of particles with different diameters, the critical particle diameter under different airfoil leading edge radii is obtained.

[0096] Based on the critical particle diameter under different airfoil leading edge radii, the critical Stokes number of airfoil wear under different airfoil leading edge radii is obtained; the results of critical particle diameter and critical Stokes number of airfoil wear under different airfoil leading edge radii are shown in Table 1 below.

[0097] Table 1 Critical particle diameter and critical Stokes number for airfoil wear at different airfoil leading edge radii.

[0098]

[0099] Step 5: Based on the critical Stokes number for airfoil wear under different airfoil leading edge radii, obtain the optimization range of the design result for the airfoil leading edge radius of the blade to be optimized; wherein, the airfoil geometric parameters corresponding to the maximum critical Stokes number for airfoil wear are taken as the optimization design result for the airfoil leading edge radius of the blade to be optimized, and the optimization range of the design result for the airfoil leading edge radius of the blade to be optimized is obtained based on the optimization design result for the airfoil leading edge radius of the blade to be optimized.

[0100] Step 6: Use the optimized range of the design result of the airfoil leading edge radius of the blade to be optimized as the range of possible values ​​for the airfoil leading edge radius of the blade to be optimized. Repeat the above steps 2-5 to obtain the optimal design result of the airfoil leading edge radius of the blade to be optimized.

[0101] As attached Figure 2-9 As shown, attached Figure 2-9 The figures show the trajectories of particles of different sizes with different leading-edge radii. Figure 2-9 As can be seen, when the particle diameter is smaller than the critical particle diameter, the particles bypass the airfoil and do not collide; when the particle diameter is larger than the critical particle diameter, most particles will still bypass the airfoil, and a small number of particles will break through the boundary layer, collide with the airfoil, reflect and flow out, thus causing erosion of the airfoil. Since the angle of attack of the airfoil is greater than 0°, erosion mainly occurs on the lower half of the leading edge of the airfoil.

[0102] As attached Figure 10 As shown, attached Figure 10 The figure shows the variation curves of the critical Stokes number under different leading edge diameters; from the appendix... Figure 10 As shown in Table 1, the analysis of the critical Stokes number of airfoil wear under different airfoil geometric parameters reveals that, within the preset range, the critical Stokes number of airfoil wear increases with the increase of the airfoil leading edge radius, and there is no linear relationship between the two. When the airfoil leading edge radius is small, the airfoil leading edge radius has a greater impact on the critical Stokes number of airfoil wear, while as the airfoil leading edge radius increases, the impact on the critical Stokes number of airfoil wear becomes smaller.

[0103] Example 2

[0104] In this embodiment 2, the optimization design process of the maximum curvature position of the A18 wind turbine blade is taken as an example.

[0105] The design principle and operation steps of this embodiment 2 are basically the same as those of the wind turbine blade airfoil optimization design method described in embodiment 1, except that:

[0106] The original design parameter for the maximum surface curvature position of the blade to be optimized is 43.2%c; several blade models with different maximum surface curvature positions include blade models with maximum surface curvature positions of 25.8%c, 34.6%c, 52.2%c, and 61.1%c, as shown in the appendix. Figure 11-12 As shown in Table 2, the results of the critical particle diameter and the critical Stokes number of airfoil wear at different maximum curvature positions are shown below.

[0107] Table 2 Critical particle diameter and critical Stokes number for airfoil wear at different maximum curvature positions.

[0108]

[0109] As attached Figure 13-22 As shown, attached Figure 13-22 The figures show the trajectories of particles of different sizes at different positions of maximum curvature. Figure 13-22 It can be seen that when the maximum curvature is located at 25.8%c and 34.6%c, the wear of the airfoil by the particles mainly occurs on the lower surface of the airfoil leading edge. When the maximum curvature is located at 52.2%c and 61.1%c, when the particle diameter is larger than the critical particle diameter but not much different from it, it does not collide with the airfoil leading edge when it flows over the airfoil leading edge. Instead, it is carried by the airflow after passing over the leading edge and then collides with the airfoil at the trailing edge.

[0110] As attached Figure 23 As shown, attached Figure 23The figure shows the variation curves of the critical Stokes number at different maximum surface positions. Figure 23 As can be seen from Table 2, at the beginning of the preset range, the critical particle diameter and critical Stokes number increase with the increase of the maximum curvature position. Then, with the increase of the maximum curvature position, the critical particle diameter and critical Stokes number begin to decrease rapidly, and the wear condition of the airfoil surface deteriorates.

[0111] The description of the relevant parts of the wind turbine blade airfoil optimization design system, equipment and computer-readable storage medium provided in this embodiment 1-2 can be found in the detailed description of the corresponding parts of the wind turbine blade airfoil optimization design method described in this embodiment, and will not be repeated here.

[0112] The wind turbine blade airfoil optimization method and system of this invention establishes a series of blade airfoils with different airfoil characteristic dimensions by modifying and adjusting the parameters of the airfoil characteristic dimensions of the blade to be optimized, and establishes a 3D flow field model for each airfoil characteristic dimension. The 3D flow field model serves as the research scope and computational domain for gas-solid two-phase flow simulation. The 3D flow field model is meshed in 3D modeling software, and then numerical simulation is performed on the meshed 3D flow field model in computational fluid dynamics software.

[0113] In this invention, during the numerical simulation of the 3D flow field model after mesh generation, a gas-solid two-phase flow simulation containing particles of different diameters is used to obtain the motion trajectory of a particle of a certain diameter in the 3D flow field model of the airfoil under a certain airfoil geometric parameters; then, based on the motion trajectory, the critical particle diameter is obtained; and based on the critical particle diameter, the critical Stokes number for airfoil wear is calculated; finally, based on the critical Stokes number for airfoil wear, the optimal design result of the airfoil size of the blade to be optimized is obtained.

[0114] In this invention, by adjusting the geometry of the airfoil, the flow field around the airfoil changes, forming a stable air film on the blade surface, isolating dusty air from contacting the blade, thereby reducing or eliminating blade wear; it is based on computer numerical simulation, which is easy to implement and can significantly improve the blade's wear resistance.

[0115] In this invention, the influence of a single airfoil geometric parameter on the erosion and wear characteristics of the airfoil surface is analyzed by changing the parameter of that airfoil geometric parameter. Based on the critical Stokes number for airfoil wear, the optimal airfoil geometric parameter value for wear resistance under a preset working condition is determined. When it is necessary to comprehensively adjust multiple airfoil geometric parameters to optimize the wear resistance of the airfoil, or to optimize the airfoil under a comprehensive evaluation criterion that combines aerodynamic performance and wear resistance, existing multi-parameter optimization methods are used for optimization calculations. Among them, the multi-parameter optimization method is, for example, the particle swarm optimization algorithm.

[0116] The above embodiments are merely one of the implementation methods for achieving the technical solution of the present invention. The scope of protection claimed by the present invention is not limited to this embodiment, but also includes any variations, substitutions and other implementation methods that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention.

Claims

1. A method for optimizing the airfoil design of wind turbine blades, characterized in that, include: Step 1: Adjust the airfoil geometry parameters of the blade to be optimized to obtain several blade models with different airfoil geometry parameters; In step 1, the airfoil geometry parameters of the blade to be optimized are one of the following: airfoil leading edge radius, airfoil maximum thickness, airfoil maximum thickness position, and airfoil maximum curvature position; Step 2: Based on the blade models with different airfoil geometric parameters, construct a 3D flow field model around the blade models with different airfoil geometric parameters; In Step 2, 3D modeling software is used to construct a 3D flow field model around the blade models with different airfoil geometric parameters based on the blade models with different airfoil geometric parameters. Step 3: Perform gas-solid two-phase flow simulation analysis on the 3D flow field models of several blade models with different airfoil geometric parameters to obtain the critical Stokes number of airfoil wear under different airfoil geometric parameters. Using computational fluid dynamics software, gas-solid two-phase flow simulation analysis was performed on 3D flow field models of blades with different airfoil geometric parameters. The process of obtaining the critical particle diameter and critical Stokes number for airfoil wear under different airfoil geometric parameters is as follows: Using computational fluid dynamics software, the motion of gas-solid two-phase flow of particles with different diameters in 3D flow field models around blades with different airfoil geometric parameters was simulated, and the simulation results of the motion trajectory of gas-solid two-phase flow of particles with different diameters were obtained. Based on the simulation results of the motion trajectory of gas-solid two-phase flow of particles with different diameters, the critical particle diameter under different airfoil geometric parameters was obtained. Based on the critical particle diameter under different airfoil geometric parameters, the critical Stokes number of airfoil wear under different airfoil geometric parameters was obtained. Step 4: Based on the critical Stokes number of airfoil wear under different airfoil geometric parameters, obtain the optimization range of the design results of the airfoil geometric parameters of the blade to be optimized; wherein, the airfoil geometric parameter corresponding to the maximum critical Stokes number of airfoil wear is taken as the optimization design result of the airfoil geometric parameters of the blade to be optimized, and the optimization range of the design results of the airfoil geometric parameters of the blade to be optimized is obtained based on the optimization design result of the airfoil geometric parameters of the blade to be optimized. Step 5: Take the optimized range of the design results of the airfoil geometry parameters of the blade to be optimized as the range of possible values ​​of the airfoil geometry parameters of the blade to be optimized, and repeat the above steps 2-4 to obtain the optimal design results of the airfoil geometry parameters of the blade to be optimized.

2. The wind turbine blade airfoil optimization design method according to claim 1, characterized in that, The 3D modeling software includes Solidworks software.

3. A wind turbine blade airfoil optimization design system, characterized in that, A method for optimizing the airfoil design of wind turbine blades as described in any one of claims 1-2 includes: The blade model module is used to adjust the airfoil geometry parameters of the blade to be optimized, and obtain blade models with several different airfoil geometry parameters. The flow field model module is used to construct a 3D flow field model around a blade model with several different airfoil geometric parameters based on the blade models with several different airfoil geometric parameters. The simulation analysis module is used to perform gas-solid two-phase flow simulation analysis on the 3D flow field model of several blade models with different airfoil geometric parameters, and to obtain the critical Stokes number of airfoil wear under different airfoil geometric parameters. The results output module obtains the optimal design results of the airfoil geometry parameters of the blade to be optimized based on the critical Stokes number of airfoil wear under different airfoil geometry parameters.

4. A wind turbine blade airfoil optimization design device, characterized in that, include Memory, used to store computer programs; A processor is configured to execute the computer program to implement the steps of the wind turbine blade airfoil optimization design method as described in any one of claims 1-2.

5. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the wind turbine blade airfoil optimization design method as described in any one of claims 1-2.

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