A property-driven blade design method and related products

Abstract

The application discloses a kind of attribute-driven blade design method and related products.The scheme, the dimensionless aerodynamic eigenparameter of each blade element section obtained by target blade spanwise discretization is mirror aligned with dimensionless structure eigenparameter, and corresponding aeroelastic blade element unit is obtained;According to the spanwise profile characteristic distribution of target blade, scale mapping is combined according to nonlinear scale physical reconstruction criterion Multiple aeroelastic blade element units are obtained to obtain solid aeroelastic model;Based on the solid aeroelastic model, a multi-objective function is constructed, and the independent optimization variable is updated under the preset constraint condition to complete the iterative optimization of the multi-objective function;Reverse layer deduction is carried out based on the optimization result of the multi-objective function, and the design scheme of the target blade is obtained;The design scheme includes composite material solid layer scheme.The application synchronously represents the aerodynamic and structural characteristics of the blade, optimizes and deduces the layer in reverse, breaks the serial design barrier of aerodynamics and structure, and improves the efficiency of blade design.

Description

Technical Field

[0001] This application relates to the field of wind turbine blade design technology, and in particular to an attribute-driven blade design method and related products. Background Technology

[0002] Because ultra-large blades have high structural flexibility, the dynamic interaction between aerodynamic forces and large structural deformations (i.e., the aeroelastic coupling effect) becomes increasingly significant. This requires that, in the early stages of blade design, aerodynamic shape design and structural dynamics design must be placed on an equal footing and iterated together.

[0003] Traditional blade design often relies on a sequential approach: on the aerodynamic side, the aerodynamic shape of the blade, such as chord length, twist angle, and relative thickness distribution, is typically determined first based on airfoil aerodynamic coefficients and blade element momentum theory. On the structural side, after the geometry is fully locked, detailed microscopic composite material layup information is defined using parametric tools, including specific materials, number of layers, layup angle, and core sandwich tangent location. Then, cross-sectional finite element analysis tools are used to solve for macroscopic cross-sectional properties, and finally, these macroscopic cross-sectional properties are converted into an aeroelastic model to complete dynamic response evaluation. This sequential design paradigm, which prioritizes aerodynamics over structure, has certain drawbacks: the design processes of the two disciplines are disconnected. If there is any minor adjustment to the aerodynamic shape or structure, the entire blade design process must be re-executed, resulting in long iteration cycles and significantly reducing the overall design efficiency of the blade.

[0004] How to design blades in a way that breaks down the barriers between aerodynamics and structure and improves the efficiency of blade design is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] To address the aforementioned issues, this application provides an attribute-driven blade design method and related products, aiming to break down the sequential design barriers between aerodynamics and structure and improve the efficiency of blade design.

[0006] The embodiments of this application disclose the following technical solutions: The first aspect of this application provides an attribute-driven blade design method, which includes: The target blade is discretized in the spanwise direction to obtain multiple blade element sections. The dimensionless aerodynamic intrinsic parameters of each blade element section are mirror-aligned with the dimensionless structural intrinsic parameters to obtain the corresponding aeroelastic blade element unit. Based on the spanwise shape feature distribution of the target blade, multiple aeroelastic blade element units are scale-mapped and merged according to the nonlinear scale physical reconstruction criterion to obtain the solid aeroelastic model of the target blade. A multi-objective function is constructed based on the physical aeroelastic model, and independent optimization variables are set. The independent optimization variables are updated under preset constraints to complete the iterative optimization of the multi-objective function until the multi-objective function converges, and the optimization result of the multi-objective function is obtained. Based on the optimization results of the multi-objective function, a reverse layup deduction is performed to obtain the design scheme of the target blade; the design scheme includes a composite material solid layup scheme.

[0007] Optionally, the method for obtaining the dimensionless structural eigenparameters includes: The dimensionless structural intrinsic parameters are obtained by matrix multiplication of the airfoil structure topological characteristic constants and the equivalent material structure operator; the airfoil structure topological characteristic constants are geometric characteristic constants obtained by performing weighted topological integration on the normalized airfoil profile; the equivalent material structure operator is the equivalent modulus constant determined based on the composite material system and the internal structural topological layout of the blade cross section.

[0008] Optionally, the method for obtaining the dimensionless aerodynamic eigenvalues ​​includes: Using the local relative thickness and characteristic flow field scale of each blade element section as interpolation control variables, the aerodynamic pole curves are reconstructed based on a reference aerodynamic database using a multivariate nonlinear interpolation algorithm to obtain the dimensionless aerodynamic pole curve vectors of each blade element section, which are used as the dimensionless aerodynamic intrinsic parameters of the corresponding blade element section.

[0009] Optionally, the nonlinear scale physical reconstruction criterion includes a geometric scale scaling equation, a nonlinear scale power law, and a mass similarity criterion. Based on the spanwise shape characteristics of the target blade, the multiple aeroelastic blade element units corresponding one-to-one with multiple blade element sections are scale-mapped and merged according to the nonlinear scale physical reconstruction criterion to obtain a solid aeroelastic model of the target blade, including: Based on the spanwise shape feature distribution of the target blade, the corresponding continuous spanwise geometric shape parameters are extracted; the continuous spanwise geometric shape parameters include chord length, absolute thickness, twist angle distribution, pre-bending distribution, and sweep distribution; For each aeroelastic blade element, the continuous spanwise geometric shape parameters are substituted into the geometric scale scaling equation to obtain the true size reference of the corresponding blade element cross section; the aeroelastic blade element is a standardized unit with a unit chord length that corresponds one-to-one with the blade element cross section. Substituting the actual size reference into the structural scale scaling equation, and solving for the structural physical parameter field of the target blade according to the nonlinear scale power law and mass similarity criterion, the structural physical parameter field includes the stiffness field, mass field, and spatial intrinsic axis distribution. The structural scale scaling equation is constructed based on the nonlinear scale power law and mass similarity criterion and is used to map the dimensionless structural intrinsic parameters to the structural physical parameters under the actual size. Based on the true size benchmark, the scale-dependent flow factor of each blade element section is determined, and the dimensionless aerodynamic coefficient of each blade element section is nonlinearly mapped according to the scale-dependent flow factor to obtain the aerodynamic parameter field of the target blade. By integrating the aerodynamic parameter field and the structural physical parameter field, a solid aeroelastic model of the target blade is obtained.

[0010] Optionally, the construction of a multi-objective function based on the physical aeroelastic model includes: Based on the aforementioned solid aeroelastic model, aeroelastic simulation is performed under flexible deformation to obtain quantified parameters. These quantified parameters include annual power generation, power coefficient, blade weight, blade root load, blade modal frequency, modal damping, and blade tip deflection. The blade modal frequency, modal damping, and blade tip deflection are used to construct preset constraint conditions. A multi-objective function is constructed with the optimization objectives of maximizing annual power generation, maximizing power coefficient, minimizing blade weight, and minimizing blade root load.

[0011] Optionally, the step of setting independent optimization variables and updating the independent optimization variables under preset constraints to complete the iterative optimization of the multi-objective function until the multi-objective function converges and the multi-objective function optimization result is obtained includes: Set independent optimization variables; the independent optimization variables include spanwise shape control point coordinates and structural topology template ratio weights; the spanwise shape control point coordinates are obtained by discretizing the continuous spanwise geometric shape parameters corresponding to the spanwise shape feature distribution of the target blade; The independent optimization variables are updated under preset constraints, and a new solid aeroelastic model is generated based on the updated independent optimization variables according to the nonlinear scale physical reconstruction criterion; the preset constraints include limit characteristic strain, blade tip deflection and frequency avoidance. The new solid aeroelastic model was subjected to aeroelastic simulation under flexible deformation state to obtain new quantitative parameters; The multi-objective function is updated based on the new quantization parameters, and the optimization is continuously iterated until the multi-objective function converges, thus obtaining the optimization result of the multi-objective function; the optimization result of the multi-objective function includes the optimal one-dimensional continuous structural property distribution and the optimal spanwise shape control point.

[0012] Optionally, the reverse layup deduction based on the multi-objective function optimization results yields the design scheme of the target blade; the design scheme includes a composite material solid layup scheme, comprising: Using the inverse decoupling equation of classical laminate theory, and based on the optimization results of the multi-objective function, a reverse layup deduction is performed to obtain the design scheme of the target blade; the design scheme includes a composite material solid layup scheme.

[0013] A second aspect of this application provides an attribute-driven blade design apparatus, the apparatus comprising: The aeroelastic blade element determination module is used to discretize the spanwise direction of the target blade to obtain multiple blade element cross sections, and to mirror-align the dimensionless aerodynamic intrinsic parameters of each blade element cross section with the dimensionless structural intrinsic parameters to obtain the corresponding aeroelastic blade element. The solid aeroelastic model determination module is used to perform scale mapping and merging of multiple aeroelastic blade element units according to the spanwise shape feature distribution of the target blade and the nonlinear scale physical reconstruction criterion to obtain the solid aeroelastic model of the target blade. The iterative optimization module is used to construct a multi-objective function based on the physical aeroelastic model, set independent optimization variables, and update the independent optimization variables under preset constraints to complete the iterative optimization of the multi-objective function until the multi-objective function converges, thereby obtaining the optimization result of the multi-objective function. The scheme determination module is used to perform reverse layup deduction based on the multi-objective function optimization results to obtain the design scheme of the target blade; the design scheme includes a composite material solid layup scheme.

[0014] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements an attribute-driven blade design method as provided in any implementation of the first aspect.

[0015] The fourth aspect of this application provides a processor for running a computer program that, when running, executes a property-driven blade design method as provided in any implementation of the first aspect.

[0016] Compared with the prior art, this application has the following advantages: The attribute-driven blade design method provided in this application discretizes the spanwise direction of the target blade to obtain multiple blade element sections. The dimensionless aerodynamic intrinsic parameters of each blade element section are mirror-aligned with the dimensionless structural intrinsic parameters to obtain corresponding aeroelastic blade element units. Based on the spanwise shape feature distribution of the target blade, the multiple aeroelastic blade element units are scale-mapped and merged according to a nonlinear scale physical reconstruction criterion to obtain a solid aeroelastic model of the target blade. A multi-objective function is constructed based on the solid aeroelastic model, and independent optimization variables are set. These independent optimization variables are updated under preset constraints to complete the iterative optimization of the multi-objective function until it converges, yielding the multi-objective function optimization result. Based on the multi-objective function optimization result, a reverse layup deduction is performed to obtain the design scheme of the target blade. The design scheme includes a composite material solid layup scheme.

[0017] In the above method, aeroelastic blade element units are constructed by discretizing the blade spanwise. This unifies and synchronously represents the dimensionless aerodynamic intrinsic parameters of the blade element cross-section with the structural intrinsic parameters. It eliminates the traditional sequential design mode of separately modeling aerodynamic shape and structural performance, thus removing the disciplinary barriers between aerodynamic and structural design. This lays the foundation for integrated aerodynamic-structural parallel design and reduces the number of subsequent interdisciplinary matching iterations. A solid aeroelastic model is obtained by uniformly mapping and merging the aeroelastic blade element units using a nonlinear scale physical reconstruction criterion. This eliminates the need to build separate aerodynamic and structural models, enabling rapid integrated generation of the aerodynamic-structural model and effectively shortening the blade modeling cycle. Based on this integrated model, multi-objective iterative optimization is directly carried out, completing the collaborative optimization of aerodynamic and structural coupling performance in one go. Finally, the composite material layup scheme is directly derived from the optimization results through reverse deduction, eliminating the need for forward layup trial-and-error iterations. This significantly reduces the number of interdisciplinary iterations and the cost of manual trial-and-error, effectively breaking down the sequential design barriers between aerodynamics and structure and significantly improving the overall design efficiency of wind turbine blades. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating an attribute-driven blade design method provided in an embodiment of this application; Figure 2 A schematic diagram of mirror-image leaf element properties of a blade aeroelastic leaf element unit provided in an embodiment of this application; Figure 3 A schematic diagram of a leaf element cross-section structure topology template provided in an embodiment of this application; Figure 4 A schematic diagram of the aerodynamic-structural property-driven multi-objective optimization process for blades provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of an attribute-driven blade design device provided in an embodiment of this application. Detailed Implementation

[0020] As described earlier, current blade design largely relies on a bottom-up sequential approach. On the aerodynamic side, the blade's aerodynamic shape, such as chord length, twist angle, and relative thickness distribution, is typically determined first based on airfoil aerodynamic coefficients and blade element momentum theory. On the structural side, after the geometry is fully locked, detailed microscopic composite material layup information is defined using parametric tools, including specific materials, number of layers, layup angle, and core sandwich tangent location. Then, cross-sectional finite element analysis tools are used to solve for macroscopic cross-sectional properties, and finally, these macroscopic cross-sectional properties are converted into an aeroelastic model to complete dynamic response evaluation. This aerodynamic-first-structural sequential design paradigm has certain drawbacks: the design processes of the two disciplines are disconnected. If there is any minor adjustment to the aerodynamic shape or structure, the entire bottom-up blade design process must be re-executed, resulting in long iteration cycles and severely reducing the overall design efficiency of the blade.

[0021] In view of the above problems, this application proposes an attribute-driven blade design method and related products. The method discretizes the spanwise direction of the target blade to obtain multiple blade element sections. The dimensionless aerodynamic intrinsic parameters of each blade element section are mirror-aligned with the dimensionless structural intrinsic parameters to obtain corresponding aeroelastic blade element units. Based on the spanwise shape characteristics of the target blade, the multiple aeroelastic blade element units are scale-mapped and merged according to a nonlinear scale physical reconstruction criterion to obtain a solid aeroelastic model of the target blade. A multi-objective function is constructed based on the solid aeroelastic model, and independent optimization variables are set. These independent optimization variables are updated under preset constraints to complete the iterative optimization of the multi-objective function until it converges, yielding the multi-objective function optimization result. Based on the multi-objective function optimization result, a reverse layup derivation is performed to obtain the design scheme of the target blade. The design scheme includes a composite material solid layup scheme.

[0022] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0023] See Figure 1 This figure is a flowchart of an attribute-driven blade design method provided in an embodiment of this application. Figure 1 As shown, the method includes the following steps: S101. Discretize the target blade spanwise to obtain multiple blade element sections, and mirror-align the dimensionless aerodynamic intrinsic parameters of each blade element section with the dimensionless structural intrinsic parameters to obtain the corresponding aeroelastic blade element unit.

[0024] Here, the target blade spanwise is discretized into N blade element spatial coordinate nodes that represent the blade element segments. For each blade element spatial coordinate node, the corresponding airfoil profile is generated by interpolation based on the relative thickness distribution at the node position, forming the blade element section specific to that node.

[0025] In one feasible implementation, the method for obtaining the dimensionless structural eigenparameters includes: The dimensionless structural intrinsic parameters are obtained by matrix multiplication of the airfoil structure topological characteristic constants and the equivalent material structure operator; the airfoil structure topological characteristic constants are geometric characteristic constants obtained by performing weighted topological integration on the normalized airfoil profile; the equivalent material structure operator is the equivalent modulus constant determined based on the composite material system and the internal structural topological layout of the blade cross section.

[0026] The equivalent material structure operator here can be obtained through numerical simulation or mechanical performance testing. Numerical simulation: Based on classical laminated plate theory and combined with thin-walled beam theory, a finite element section solver is used to apply a unit load to a two-dimensional structural feature template, inversely extracting the flapping, oscillation, and torsional equivalent mechanical modulus constants independent of the absolute size of the section, and extracting related mass linear density characteristics, etc. Mechanical performance testing: Through standard mechanical experiments such as axial tension, bending, and shear on standard components or material samples of typical structural topologies of the reference airfoil, the macroscopic equivalent modulus constant under this specific layout is measured and calibrated.

[0027] In one feasible implementation, the method for obtaining the dimensionless aerodynamic eigenvalues ​​includes: Using the local relative thickness and characteristic flow field scale of each blade element section as interpolation control variables, the aerodynamic pole curves are reconstructed based on a reference aerodynamic database using a multivariate nonlinear interpolation algorithm to obtain the dimensionless aerodynamic pole curve vectors of each blade element section, which are used as the dimensionless aerodynamic intrinsic parameters of the corresponding blade element section.

[0028] The baseline aerodynamic database pre-stores complete aerodynamic pole curves of airfoils under different relative thicknesses and flow field conditions. Unlike linear interpolation, multivariate nonlinear interpolation can accurately fit the nonlinear variation of airfoil aerodynamic coefficients with thickness and flow field, avoiding aerodynamic parameter distortion caused by linear approximation.

[0029] Dimensionless aerodynamic intrinsic parameters include lift coefficient, drag coefficient, moment coefficient, and aerodynamic center.

[0030] The target blade is discretized along its span to obtain several blade element sections. For each blade element section, dimensionless aerodynamic eigenparameters and dimensionless structural eigenparameters are solved separately. In a normalized dimensionless coordinate system, the two types of parameters are mirror-aligned in the same dimension and encapsulated to generate one-to-one corresponding aeroelastic blade element (BASE). Aerodynamics and structure share a single spanwise discrete mesh, achieving integrated and synchronous aerodynamic-structural characterization and eliminating barriers to multidisciplinary data interaction. The BASE element does not contain any absolute physical dimensions, only retaining the cross-sectional topology and dimensionless aerodynamic eigenvalues.

[0031] S102. Based on the spanwise shape feature distribution of the target blade, the multiple aeroelastic blade element units are scale-mapped and merged according to the nonlinear scale physical reconstruction criterion to obtain the solid aeroelastic model of the target blade.

[0032] The nonlinear scale physical reconstruction criteria include geometric scale scaling equations, nonlinear scale power laws, and quality similarity criteria.

[0033] In one feasible implementation: Based on the spanwise shape feature distribution of the target blade, the corresponding continuous spanwise geometric shape parameters are extracted; the continuous spanwise geometric shape parameters include chord length, absolute thickness, twist angle distribution, pre-bending distribution, and sweep distribution; For each aeroelastic blade element, the continuous spanwise geometric shape parameters are substituted into the geometric scale scaling equation to obtain the true size reference of the corresponding blade element cross section; the aeroelastic blade element is a standardized unit with a unit chord length that corresponds one-to-one with the blade element cross section. Substituting the actual size reference into the structural scale scaling equation, and solving for the structural physical parameter field of the target blade according to the nonlinear scale power law and mass similarity criterion, the structural physical parameter field includes the stiffness field, mass field, and spatial intrinsic axis distribution. The structural scale scaling equation is constructed based on the nonlinear scale power law and mass similarity criterion and is used to map the dimensionless structural intrinsic parameters to the structural physical parameters under the actual size. Based on the true size benchmark, the scale-dependent flow factor of each blade element section is determined, and the dimensionless aerodynamic coefficient of each blade element section is nonlinearly mapped according to the scale-dependent flow factor to obtain the aerodynamic parameter field of the target blade. By integrating the aerodynamic parameter field and the structural physical parameter field, a solid aeroelastic model of the target blade is obtained.

[0034] Among them, the stiffness field includes the composite flapping stiffness field, the oscillation stiffness field, and the torsional stiffness field; the mass field includes the composite continuous spanwise linear density field and the rotational moment of inertia field about the axis; the spatial intrinsic axis distribution includes the structural twist angle variation of each leaf element section, the absolute shear center trajectory and the absolute centroid trajectory, as well as the spanwise centroid-elastic axis eccentricity distribution vector.

[0035] The continuous spanwise geometric parameters can be obtained through parametric analytical equations; the parametric analytical equations include higher-order Bézier curves or polynomial parametric equations.

[0036] For example, such as Figure 2 As shown, Figure 2 This is a schematic diagram of the mirrored blade element properties of an aeroelastic blade element unit provided in an embodiment of this application. A blade element refers to a discretized blade element section along the blade span, serving as a unified carrier of geometric shape, aerodynamic properties, and structural properties. The aerodynamic element takes the design conditions and accessory configuration as input and outputs aerodynamic intrinsic parameters. The structural element refers to the blade element structural intrinsic property unit defined at the same spanwise node, taking the material system and load-bearing configuration as input. It outputs dimensionless structural intrinsic parameters by multiplying the structural characteristic constant representing the geometric topological efficiency of the section with the equivalent material operator representing the directional stiffness of the material. The aerodynamic and structural elements are spatially aligned in a one-to-one correspondence at each blade element, jointly encapsulated into a blade element-level aeroelastic integrated unit, i.e., an aeroelastic blade element unit. Each blade element node distributed along the blade span is bound to a corresponding aeroelastic blade element unit. The aeroelastic blade element unit, combined with absolute external dimensions (such as chord length, thickness, and twist angle along the spanwise distribution) as a geometric coupling factor, is reconstructed into a complete solid aeroelastic model by nonlinear scaling mapping, restoring the aerodynamic parameter field and structural parameter field at each blade element location. The solid aeroelastic model further outputs: aerodynamic response parameters (such as power generation, power coefficient, and characteristic load), aeroelastic response parameters (frequency and damping, etc.), and structural response parameters (weight, strain, and deflection, etc.), which correspond to the objective function and constraints in multi-objective optimization, respectively.

[0037] The structural and aerodynamic links share the same set of absolute blade spanwise geometry, and the structural stiffness field and aerodynamic load field are solved simultaneously. This eliminates the need for the traditional serial step-by-step process of first calculating aerodynamics and then separately modeling and calculating the structure, thus removing the barriers between disciplines and data.

[0038] The above-described implementation method integrates the aerodynamic and structural characteristics of the blade into a single spanwise parameter system for synchronous modeling and mapping through a unified aeroelastic blade element unit and nonlinear scale physical reconstruction criteria. This completely breaks down the traditional serial design barriers where aerodynamic shape design and structural performance design are separated and iterated step by step. It achieves integrated alignment of aerodynamic and structural parameters at the dimensionless intrinsic level, and then synchronously generates complete aerodynamic parameter fields and structural physical parameter fields through unified scale mapping. This eliminates the need for independent modeling and cross-iterative verification by disciplines, enabling the parallel and synchronous construction of aerodynamic and structural performance. This significantly simplifies the blade design process, greatly shortens the conceptual design and optimization iteration cycle, and fundamentally improves the overall efficiency and design consistency of multidisciplinary coupled design of flexible wind turbine blades. At the same time, it ensures the accuracy of aeroelastic coupling simulation and provides a highly adaptable integrated modeling carrier for subsequent multi-objective iterative optimization.

[0039] S103. Construct a multi-objective function based on the physical aeroelastic model, and set independent optimization variables. Update the independent optimization variables under preset constraints to complete the iterative optimization of the multi-objective function until the multi-objective function converges, and obtain the optimization result of the multi-objective function.

[0040] In one feasible implementation, a multi-objective function is constructed based on the physical gaseous model, including: Based on the aforementioned solid aeroelastic model, aeroelastic simulation is performed under flexible deformation to obtain quantified parameters. These quantified parameters include annual power generation, power coefficient, blade weight, blade root load, blade modal frequency, modal damping, and blade tip deflection. The blade modal frequency, modal damping, and blade tip deflection are used to construct preset constraint conditions. A multi-objective function is constructed with the optimization objectives of maximizing annual power generation, maximizing power coefficient, minimizing blade weight, and minimizing blade root load.

[0041] Annual power generation represents the total electrical energy that the blades can capture and convert within a year, reflecting the economic benefits of the blades; the higher the better. Power coefficient represents the efficiency ratio of the blades in converting wind energy into mechanical energy, reflecting the aerodynamic energy capture efficiency of the blades; the higher the better. Blade weight represents the overall structural mass of the blade itself. Root load represents the ultimate bending moment and fatigue load borne by the blade root during operation, reflecting the fatigue load transmitted to the hub and tower; the lower the better. Blade modal frequency represents the natural frequency of the blade during free vibration, a key parameter to avoid resonance. Modal damping represents the rate of decay of vibration energy over time; modal damping must be greater than the safety threshold to ensure aeroelastic stability. Tip deflection represents the total spatial displacement of the blade tip relative to the blade root under extreme wind conditions or normal operating conditions, including bending and torsional deformation; tip deflection must be less than the clearance distance from the blade tip to the tower, otherwise the blade will impact the tower, causing the wind turbine to collapse.

[0042] In one feasible implementation, independent optimization variables are set, and these variables are updated under preset constraints to complete the iterative optimization of the multi-objective function until the multi-objective function converges, thereby obtaining the multi-objective function optimization result, including: Set independent optimization variables; the independent optimization variables include spanwise shape control point coordinates and structural topology template ratio weights; the spanwise shape control point coordinates are obtained by discretizing the continuous spanwise geometric shape parameters corresponding to the spanwise shape feature distribution of the target blade; The independent optimization variables are updated under preset constraints, and a new solid aeroelastic model is generated based on the updated independent optimization variables according to the nonlinear scale physical reconstruction criterion; the preset constraints include limit characteristic strain, blade tip deflection and frequency avoidance. The new solid aeroelastic model was subjected to aeroelastic simulation under flexible deformation state to obtain new quantitative parameters; The multi-objective function is updated based on the new quantization parameters, and the optimization is continuously iterated until the multi-objective function converges, thus obtaining the optimization result of the multi-objective function; the optimization result of the multi-objective function includes the optimal one-dimensional continuous structural property distribution and the optimal spanwise shape control point.

[0043] The structural topology template ratio weight is used to control the distribution ratio of composite material regions such as skin, main beam, and web within the airfoil section. The structural topology template is a two-dimensional structural feature template pre-set for a selected reference airfoil, composed of typical material systems (such as carbon fiber pultruded plates and glass fiber pultruded plates) and typical internal load-bearing configurations (such as single main beam double web structure).

[0044] For example, such as Figure 3 As shown, Figure 3 This diagram illustrates a topology template for a blade element cross-section structure, as provided in an embodiment of this application. The standard airfoil outline in the diagram serves as the geometric datum for calculating the airfoil structure's topological characteristic constant (ASTC). The horizontal dashed line represents the airfoil chord length datum line; the vertical dashed line represents the local reference dividing line of the cross-section, used to distinguish the airfoil's leading edge, central main beam region, and trailing edge core material filling region. This topology template pre-divides the skin, main beam, web, and core material filling into independent functional zones, used to solve for the airfoil structure's topological characteristic constant and equivalent material structure operator. It also provides a cross-sectional geometric datum for multi-objective optimization of topology ratio weight variables and inverse ply calculation.

[0045] like Figure 4 As shown, Figure 4This diagram illustrates the multi-objective optimization process of a blade driven by aerodynamic and structural attributes, as provided in this application embodiment. Each vertical line in the diagram represents a blade design evaluation index, from left to right: flapping equivalent stiffness El_edge02, flaring equivalent stiffness El_flap02, section safety strain coefficient SC_y02, torsional equivalent stiffness Stf_Tor02, spanwise chord geometry chord02, annual power generation AEPinMWh, tip deflection BT_def_X, peak power coefficient CpMax, and root ultimate bending moment Mxy_ulti_BR. Infeasible solutions, although possessing some high performance, are eliminated because they do not meet structural safety constraints. Feasible solutions meet the constraints but are not economically optimal. The optimal solution achieves the best balance between multiple objectives such as power generation and structural weight. The Pareto solution set provides flexible alternatives under multi-objective conflicts. Figure 4 This demonstrates that the present application enables stable convergence of multi-objective iterative optimization and yields a conceptual design scheme that satisfies multidisciplinary constraints and exhibits excellent comprehensive performance, thus verifying the efficiency and engineering feasibility of the method in the conceptual design stage of ultra-large flexible blades.

[0046] A multi-objective optimization system is constructed based on aeroelastic coupling simulation under flexible deformation, simultaneously maximizing annual power generation and power coefficient while minimizing blade weight and blade root load. This breaks the traditional design mode of sequential separation between aerodynamics and structure, and realizes integrated collaborative evaluation and optimization of multi-disciplinary performance. At the same time, a low-dimensional independent optimization variable with shape control points and structural topology ratio weights is adopted. A small number of control points characterize the smooth shape of the blade, and topology weights regulate the cross-sectional structural distribution. This abandons the traditional high-dimensional ply variable optimization method, significantly reduces the optimization dimension, and improves iteration efficiency and global optimization capability. The iteration process can automatically complete model reconstruction, aeroelastic simulation, and objective function update, forming a fully automated iterative closed loop, which greatly shortens the design cycle.

[0047] S104. Based on the optimization results of the multi-objective function, reverse layup deduction is performed to obtain the design scheme of the target blade.

[0048] The design scheme includes a composite material solid layup scheme.

[0049] In one feasible implementation: Using the inverse decoupling equation of classical laminate theory, and based on the optimization results of the multi-objective function, a reverse layup deduction is performed to obtain the design scheme of the target blade; the design scheme includes a composite material solid layup scheme.

[0050] The proposed scheme includes the number of pultruded plate layers in the main beam, the thickness of the fabric in each direction, and the distribution of the core material tangent points.

[0051] Based on the inverse decoupling equations of classical laminated plate theory, inverse plying derivation is carried out directly using the optimal continuous structural property distribution and optimal spanwise shape control points obtained from multi-objective optimization as inputs. This avoids the performance limitations and difficulty in achieving global optimization caused by the pre-fixation of plying parameters in traditional forward design. Simultaneously, the inverse decoupling equations can achieve precise decoupling and matching of multi-dimensional structural properties such as stiffness, mass, and inertia, ensuring that the plying parameters obtained from the derivation, such as the number of pultruded plates in the main beam, the thickness of each directional material, and the distribution of core material tangent points, are completely adapted to the optimal spanwise structural distribution, with no performance deviation and no need for secondary manual iteration verification. This effectively establishes a closed-loop design process from aeroelastic modeling to multidisciplinary optimization to engineering manufacturing, significantly improving the accuracy and efficiency of blade plying design and ensuring that the optimal solution can be fully implemented into a practical composite material manufacturing scheme.

[0052] The attribute-driven blade design method provided in this application discretizes the spanwise direction of the target blade to obtain multiple blade element sections. The dimensionless aerodynamic intrinsic parameters of each blade element section are mirror-aligned with the dimensionless structural intrinsic parameters to obtain corresponding aeroelastic blade element units. Based on the spanwise shape characteristics of the target blade, the multiple aeroelastic blade element units are scale-mapped and merged according to a nonlinear scale physical reconstruction criterion to obtain a solid aeroelastic model of the target blade. A multi-objective function is constructed based on the solid aeroelastic model, and independent optimization variables are set. These independent optimization variables are updated under preset constraints to complete the iterative optimization of the multi-objective function until it converges, yielding the multi-objective function optimization result. Based on the multi-objective function optimization result, a reverse layup deduction is performed to obtain the design scheme of the target blade. The design scheme includes a composite material solid layup scheme.

[0053] In the above method, aeroelastic blade element units are constructed by discretizing the blade spanwise. This unifies and synchronously represents the dimensionless aerodynamic intrinsic parameters of the blade element cross-section with the structural intrinsic parameters. It eliminates the traditional sequential design mode of separately modeling aerodynamic shape and structural performance, thus removing the disciplinary barriers between aerodynamic and structural design. This lays the foundation for integrated aerodynamic-structural parallel design and reduces the number of subsequent interdisciplinary matching iterations. A solid aeroelastic model is obtained by uniformly mapping and merging the aeroelastic blade element units using a nonlinear scale physical reconstruction criterion. This eliminates the need to build separate aerodynamic and structural models, enabling rapid integrated generation of the aerodynamic-structural model and effectively shortening the blade modeling cycle. Based on this integrated model, multi-objective iterative optimization is directly carried out, completing the collaborative optimization of aerodynamic and structural coupling performance in one go. Finally, the composite material layup scheme is directly derived from the optimization results through reverse deduction, eliminating the need for forward layup trial-and-error iterations. This significantly reduces the number of interdisciplinary iterations and the cost of manual trial-and-error, effectively breaking down the sequential design barriers between aerodynamics and structure and significantly improving the overall design efficiency of wind turbine blades.

[0054] Based on the attribute-driven blade design method described in the preceding embodiments, this application also provides an attribute-driven blade design apparatus. Figure 5 This is a schematic diagram of the device. Figure 5 As shown, the attribute-driven blade design device includes: The aeroelastic blade element determination module 501 is used to discretize the spanwise direction of the target blade to obtain multiple blade element sections, and to mirror-align the dimensionless aerodynamic intrinsic parameters of each blade element section with the dimensionless structural intrinsic parameters to obtain the corresponding aeroelastic blade element. The solid aeroelastic model determination module 502 is used to perform scale mapping and merging of multiple aeroelastic blade element units according to the spanwise shape feature distribution of the target blade and the nonlinear scale physical reconstruction criterion to obtain the solid aeroelastic model of the target blade. The iterative optimization module 503 is used to construct a multi-objective function based on the physical aeroelastic model, set independent optimization variables, and update the independent optimization variables under preset constraints to complete the iterative optimization of the multi-objective function until the multi-objective function converges and the multi-objective function optimization result is obtained. The scheme determination module 504 is used to perform reverse layup deduction based on the multi-objective function optimization results to obtain the design scheme of the target blade; the design scheme includes a composite material solid layup scheme.

[0055] Optionally, the method for obtaining the dimensionless structural eigenparameters includes: The dimensionless structural intrinsic parameters are obtained by matrix multiplication of the airfoil structure topological characteristic constants and the equivalent material structure operator; the airfoil structure topological characteristic constants are geometric characteristic constants obtained by performing weighted topological integration on the normalized airfoil profile; the equivalent material structure operator is the equivalent modulus constant determined based on the composite material system and the internal structural topological layout of the blade cross section.

[0056] Optionally, the method for obtaining the dimensionless aerodynamic eigenvalues ​​includes: Using the local relative thickness and characteristic flow field scale of each blade element section as interpolation control variables, the aerodynamic pole curves are reconstructed based on a reference aerodynamic database using a multivariate nonlinear interpolation algorithm to obtain the dimensionless aerodynamic pole curve vectors of each blade element section, which are used as the dimensionless aerodynamic intrinsic parameters of the corresponding blade element section.

[0057] Optionally, the solid aeroelastic model determination module is used for: Based on the spanwise shape feature distribution of the target blade, the corresponding continuous spanwise geometric shape parameters are extracted; the continuous spanwise geometric shape parameters include chord length, absolute thickness, twist angle distribution, pre-bending distribution, and sweep distribution; For each aeroelastic blade element, the continuous spanwise geometric shape parameters are substituted into the geometric scale scaling equation to obtain the true size reference of the corresponding blade element cross section; the aeroelastic blade element is a standardized unit with a unit chord length that corresponds one-to-one with the blade element cross section. Substituting the actual size reference into the structural scale scaling equation, and solving for the structural physical parameter field of the target blade according to the nonlinear scale power law and mass similarity criterion, the structural physical parameter field includes the stiffness field, mass field, and spatial intrinsic axis distribution. The structural scale scaling equation is constructed based on the nonlinear scale power law and mass similarity criterion and is used to map the dimensionless structural intrinsic parameters to the structural physical parameters under the actual size. Based on the true size benchmark, the scale-dependent flow factor of each blade element section is determined, and the dimensionless aerodynamic coefficient of each blade element section is nonlinearly mapped according to the scale-dependent flow factor to obtain the aerodynamic parameter field of the target blade. By integrating the aerodynamic parameter field and the structural physical parameter field, a solid aeroelastic model of the target blade is obtained.

[0058] Optionally, the iterative optimization module is used for: Based on the aforementioned solid aeroelastic model, aeroelastic simulation is performed under flexible deformation to obtain quantified parameters. These quantified parameters include annual power generation, power coefficient, blade weight, blade root load, blade modal frequency, modal damping, and blade tip deflection. The blade modal frequency, modal damping, and blade tip deflection are used to construct preset constraint conditions. A multi-objective function is constructed with the optimization objectives of maximizing annual power generation, maximizing power coefficient, minimizing blade weight, and minimizing blade root load.

[0059] Optionally, the iterative optimization module is used for: Set independent optimization variables; the independent optimization variables include spanwise shape control point coordinates and structural topology template ratio weights; the spanwise shape control point coordinates are obtained by discretizing the continuous spanwise geometric shape parameters corresponding to the spanwise shape feature distribution of the target blade; The independent optimization variables are updated under preset constraints, and a new solid aeroelastic model is generated based on the updated independent optimization variables according to the nonlinear scale physical reconstruction criterion; the preset constraints include limit characteristic strain, blade tip deflection and frequency avoidance. The new solid aeroelastic model was subjected to aeroelastic simulation under flexible deformation state to obtain new quantitative parameters; The multi-objective function is updated based on the new quantization parameters, and the optimization is continuously iterated until the multi-objective function converges, thus obtaining the optimization result of the multi-objective function; the optimization result of the multi-objective function includes the optimal one-dimensional continuous structural property distribution and the optimal spanwise shape control point.

[0060] Optionally, the scheme determination module is used for: Using the inverse decoupling equation of classical laminate theory, and based on the optimization results of the multi-objective function, a reverse layup deduction is performed to obtain the design scheme of the target blade; the design scheme includes a composite material solid layup scheme.

[0061] Furthermore, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the attribute-driven blade design method as described in any of the method embodiments.

[0062] Furthermore, this application embodiment also provides a processor for running a computer program, which executes the attribute-driven blade design method as described in any of the foregoing method embodiments.

[0063] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments. The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separate. The components indicated as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment solution according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0064] The above description is merely one specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An attribute-driven blade design method, characterized in that, include: The target blade is discretized in the spanwise direction to obtain multiple blade element sections. The dimensionless aerodynamic intrinsic parameters of each blade element section are mirror-aligned with the dimensionless structural intrinsic parameters to obtain the corresponding aeroelastic blade element unit. Based on the spanwise shape feature distribution of the target blade, multiple aeroelastic blade element units are scale-mapped and merged according to the nonlinear scale physical reconstruction criterion to obtain the solid aeroelastic model of the target blade. A multi-objective function is constructed based on the physical aeroelastic model, and independent optimization variables are set. The independent optimization variables are updated under preset constraints to complete the iterative optimization of the multi-objective function until the multi-objective function converges, and the optimization result of the multi-objective function is obtained. Based on the optimization results of the multi-objective function, a reverse layup deduction is performed to obtain the design scheme of the target blade; the design scheme includes a composite material solid layup scheme.

2. The method according to claim 1, characterized in that, The methods for obtaining the dimensionless structural intrinsic parameters include: The dimensionless structural intrinsic parameters are obtained by matrix multiplication of the airfoil structure topological characteristic constants and the equivalent material structure operator; the airfoil structure topological characteristic constants are geometric characteristic constants obtained by performing weighted topological integration on the normalized airfoil profile; the equivalent material structure operator is the equivalent modulus constant determined based on the composite material system and the internal structural topological layout of the blade cross section.

3. The method according to claim 1, characterized in that, The methods for obtaining the dimensionless aerodynamic intrinsic parameters include: Using the local relative thickness and characteristic flow field scale of each blade element section as interpolation control variables, the aerodynamic pole curves are reconstructed based on a reference aerodynamic database using a multivariate nonlinear interpolation algorithm to obtain the dimensionless aerodynamic pole curve vectors of each blade element section, which are used as the dimensionless aerodynamic intrinsic parameters of the corresponding blade element section.

4. The method according to claim 1, characterized in that, The nonlinear scale physical reconstruction criteria include geometric scale scaling equations, nonlinear scale power laws, and mass similarity criteria. The process involves merging multiple aeroelastic blade elements based on the spanwise shape characteristics of the target blade and following a nonlinear scale physical reconstruction criterion to obtain a solid aeroelastic model of the target blade, including: Based on the spanwise shape feature distribution of the target blade, the corresponding continuous spanwise geometric shape parameters are extracted; the continuous spanwise geometric shape parameters include chord length, absolute thickness, twist angle distribution, pre-bending distribution, and sweep distribution; For each aeroelastic blade element, the continuous spanwise geometric shape parameters are substituted into the geometric scale scaling equation to obtain the true size reference of the corresponding blade element cross section; the aeroelastic blade element is a standardized unit with a unit chord length that corresponds one-to-one with the blade element cross section. Substituting the actual size reference into the structural scale scaling equation, and solving for the structural physical parameter field of the target blade according to the nonlinear scale power law and mass similarity criterion, the structural physical parameter field includes the stiffness field, mass field, and spatial intrinsic axis distribution. The structural scale scaling equation is constructed based on the nonlinear scale power law and mass similarity criterion and is used to map the dimensionless structural intrinsic parameters to the structural physical parameters under the actual size. Based on the true size benchmark, the scale-dependent flow factor of each blade element section is determined, and the dimensionless aerodynamic coefficient of each blade element section is nonlinearly mapped according to the scale-dependent flow factor to obtain the aerodynamic parameter field of the target blade. By integrating the aerodynamic parameter field and the structural physical parameter field, a solid aeroelastic model of the target blade is obtained.

5. The method according to claim 1, characterized in that, The construction of the multi-objective function based on the physical aeroelastic model includes: Based on the aforementioned solid aeroelastic model, aeroelastic simulation is performed under flexible deformation to obtain quantified parameters. These quantified parameters include annual power generation, power coefficient, blade weight, blade root load, blade modal frequency, modal damping, and blade tip deflection. The blade modal frequency, modal damping, and blade tip deflection are used to construct preset constraint conditions. A multi-objective function is constructed with the optimization objectives of maximizing annual power generation, maximizing power coefficient, minimizing blade weight, and minimizing blade root load.

6. The method according to claim 5, characterized in that, The step of setting independent optimization variables and updating these variables under preset constraints to complete the iterative optimization of the multi-objective function until the multi-objective function converges, thereby obtaining the multi-objective function optimization result, includes: Set independent optimization variables; the independent optimization variables include spanwise shape control point coordinates and structural topology template ratio weights; the spanwise shape control point coordinates are obtained by discretizing the continuous spanwise geometric shape parameters corresponding to the spanwise shape feature distribution of the target blade; The independent optimization variables are updated under preset constraints, and a new solid aeroelastic model is generated based on the updated independent optimization variables according to the nonlinear scale physical reconstruction criterion; the preset constraints include limit characteristic strain, blade tip deflection and frequency avoidance. The new solid aeroelastic model was subjected to aeroelastic simulation under flexible deformation state to obtain new quantitative parameters; The multi-objective function is updated based on the new quantization parameters, and the optimization is continuously iterated until the multi-objective function converges, thus obtaining the optimization result of the multi-objective function; the optimization result of the multi-objective function includes the optimal one-dimensional continuous structural property distribution and the optimal spanwise shape control point.

7. The method according to claim 1, characterized in that, The reverse layup derivation based on the multi-objective function optimization results to obtain the design scheme of the target blade includes: Using the inverse decoupling equation of classical laminate theory, and based on the optimization results of the multi-objective function, a reverse layup deduction is performed to obtain the design scheme of the target blade; the design scheme includes a composite material solid layup scheme.

8. An attribute-driven blade design device, characterized in that, include: The aeroelastic blade element determination module is used to discretize the spanwise direction of the target blade to obtain multiple blade element cross sections, and to mirror-align the dimensionless aerodynamic intrinsic parameters of each blade element cross section with the dimensionless structural intrinsic parameters to obtain the corresponding aeroelastic blade element. The solid aeroelastic model determination module is used to perform scale mapping and merging of multiple aeroelastic blade element units according to the spanwise shape feature distribution of the target blade and the nonlinear scale physical reconstruction criterion to obtain the solid aeroelastic model of the target blade. The iterative optimization module is used to construct a multi-objective function based on the physical aeroelastic model, set independent optimization variables, and update the independent optimization variables under preset constraints to complete the iterative optimization of the multi-objective function until the multi-objective function converges, thereby obtaining the optimization result of the multi-objective function. The scheme determination module is used to perform reverse layup deduction based on the multi-objective function optimization results to obtain the design scheme of the target blade; the design scheme includes a composite material solid layup scheme.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the attribute-driven blade design method as described in any one of claims 1-7.

10. A processor, characterized in that, Used to run a computer program, which, when running, executes the attribute-driven blade design method as described in any one of claims 1-7.

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