Hood design method, device and equipment and storage medium

Abstract

The invention discloses a hood design method, device and equipment and a storage medium, and relates to the technical field of vehicle design, and the hood design method comprises the steps of obtaining design parameter data, inputting a quadratic Bezier fitting carbon fiber curve model according to the design parameter data to obtain a fiber angle, and designing a hood according to the fiber angle to obtain a design result. And on the basis of a quadratic Bezier curve fitting fiber angle, a multi-objective algorithm optimization design is adopted, and hood lightweight and modal performance improvement are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle design, and in particular to a hood design method, device, equipment and storage medium. Background Art

[0002] With the rapid development of the automobile industry, the requirements for automobile performance are getting higher and higher. Lightweighting, as a key means to improve automobile fuel efficiency, reduce emissions and enhance handling performance, has become an important trend in automobile design. In this context, carbon fiber composite materials are widely used in the field of automobile manufacturing due to their excellent specific strength and specific stiffness, especially in the design of non-load-bearing structural parts such as hoods.

[0003] At present, the design methods of carbon fiber composite hoods mainly include the following: by adjusting the parameters such as the ply angle, ply thickness and core material thickness of the single-layer carbon fiber composite material, the structural optimization design is carried out to achieve the lightweight of the hood, or the modal analysis of the hood is carried out through finite element analysis and other means to ensure that its dynamic performance under different working conditions meets the design requirements, and the mechanical properties of the composite material are predicted using the laminate theory to guide the structural design of the hood.

[0004] Although the existing design methods can achieve lightweight and performance optimization of carbon fiber composite hoods to a certain extent, there are still defects. Traditional design methods require a lot of iterative calculations and experimental verifications, with long design cycles and low efficiency. Moreover, the fiber angles of carbon fiber composites are usually fixed, making it difficult to adjust the local stiffness of the hood, limiting the realization of multiple performance objectives. Existing optimization algorithms can only optimize for a single goal, and it is difficult to simultaneously meet multiple performance requirements such as lightweight, high modal frequency, and high stiffness. Traditional design methods are difficult to take into account the dual needs of lightweight and structural performance. Therefore, a design method based on multi-objective optimization is developed to improve the efficiency and accuracy of hood design. Summary of the invention

[0005] The main purpose of this application is to provide a hood design method, device, equipment and storage medium, aiming to solve the technical problem of how to improve the accuracy and performance of the hood.

[0006] To achieve the above objectives, the present application proposes a hood design method, the method comprising:

[0007] Obtain design parameter data;

[0008] Input a quadratic Bezier fitting carbon fiber curve model according to the design parameter data to obtain a fiber angle, wherein the quadratic Bezier fitting carbon fiber curve model is a model obtained by an optimization algorithm according to the design parameter data;

[0009] The hood is designed according to the fiber angle to obtain a design result.

[0010] In one embodiment, before the step of inputting a quadratic Bezier fitting carbon fiber curve model according to the design parameter data to obtain the fiber angle, the step includes:

[0011] Acquire design parameter sample data and establish an initial quadratic Bezier fitting carbon fiber curve model, wherein the design parameter sample data includes hood weight, modal frequency, and mechanical performance requirements under static and dynamic conditions;

[0012] The initial quadratic Bezier fitting carbon fiber curve model is trained according to the design parameter sample data to obtain a quadratic Bezier fitting carbon fiber curve model.

[0013] In one embodiment, the step of training the initial quadratic Bezier fitting carbon fiber curve model according to the design parameter sample data to obtain the quadratic Bezier fitting carbon fiber curve model includes:

[0014] Get input data;

[0015] According to the input data, the starting point of the curve, the starting angle of the fiber, the end point of the curve and the end point angle of the fiber are obtained;

[0016] Obtaining an actual fiber angle according to the starting point of the curve, the fiber starting angle, the end point of the curve and the fiber end point angle;

[0017] Inputting the input data into the initial quadratic Bezier fitting carbon fiber curve model to obtain a predicted fiber angle;

[0018] According to the loss function calculation, the error value between the predicted fiber angle and the actual fiber angle is obtained;

[0019] The fiber angle is iteratively updated through an optimization algorithm until a maximum number of iterations is reached or an error value calculated by a loss function converges to a preset threshold, thereby obtaining a quadratic Bezier fitting carbon fiber curve model.

[0020] In one embodiment, the step of obtaining the actual fiber angle according to the starting point of the curve, the fiber starting angle, the end point of the curve and the fiber end point angle comprises:

[0021] According to the starting point of the curve, the starting angle of the fiber, the end point of the curve and the end point angle of the fiber, a fast non-dominated sorting is performed through a multi-objective optimization algorithm to obtain a superiority or inferiority grade;

[0022] Calculate the congestion degree based on the merits and demerits to obtain the distribution density;

[0023] A crossover and a mutation operation are performed according to the distribution density to obtain the actual fiber angle.

[0024] In one embodiment, the step of inputting the input data into the initial quadratic Bezier fitting carbon fiber curve model to obtain a predicted fiber angle comprises:

[0025] Inputting the input data into the initial quadratic Bezier fitting carbon fiber curve model for modal analysis to obtain frequency difference and weight difference;

[0026] Performing fast non-dominated sorting by a multi-objective optimization algorithm according to the frequency difference and the weight difference to obtain a quality grade;

[0027] Calculate the congestion degree based on the merits and demerits to obtain the distribution density;

[0028] The predicted fiber angle is obtained based on the distribution density.

[0029] In one embodiment, after the step of training the initial quadratic Bezier fitting carbon fiber curve model according to the design parameter sample data to obtain the quadratic Bezier fitting carbon fiber curve model, the method further comprises:

[0030] Evaluating the quadratic Bezier fitting carbon fiber curve model to obtain an evaluation result;

[0031] If the evaluation result does not meet the control requirement, the quadratic Bezier fitting carbon fiber curve model is retrained until the control requirement is met.

[0032] In one embodiment, the step of designing the hood according to the fiber angle to obtain a design result comprises:

[0033] generating a three-dimensional model of the hood according to the fiber angle;

[0034] Performing finite element analysis on the three-dimensional model to obtain analysis results;

[0035] The hood design is adjusted according to the analysis results until the preset design requirements are met to obtain a design result, wherein the preset design requirements include hood weight, modal frequency and hood stiffness.

[0036] In addition, to achieve the above-mentioned purpose, the present application also proposes a hood design device, the hood design device comprising:

[0037] An acquisition module, used for acquiring design parameter data;

[0038] The acquisition module is also used to input a quadratic Bezier fitting carbon fiber curve model according to the design parameter data to obtain a fiber angle;

[0039] The result module is used to design the hood according to the fiber angle to obtain a design result.

[0040] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the hood design method described above are implemented.

[0041] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the hood design method described above are implemented.

[0042] This application obtains design parameter data, inputs a quadratic Bezier fitting carbon fiber curve model according to the design parameter data, obtains the fiber angle, designs the hood according to the fiber angle, and obtains the design result. Based on the quadratic Bezier curve fitting fiber angle, a multi-objective algorithm is used to optimize the design to achieve lightweight hood and improved modal performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0044] Figure 1 This is a schematic flow chart of a first embodiment of the hood design method of the present application;

[0045] Figure 2 This is a fiber angle distribution diagram of the first embodiment of the hood design method of this application;

[0046] Figure 3 This is a flow chart of a second embodiment of the hood design method of the present application;

[0047] Figure 4 A schematic diagram of the module structure of the hood design device according to an embodiment of the present application;

[0048] Figure 5 A schematic diagram of the device structure of the hardware operating environment involved in the hood design method in the embodiment of the present application;

[0049] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0050] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0051] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0052] The main solution of the embodiment of the present application is: obtain design parameter data, input the quadratic Bezier fitting carbon fiber curve model according to the design parameter data, obtain the fiber angle, design the hood according to the fiber angle, and obtain the design result.

[0053] Based on this, the embodiment of the present application provides a hood design method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the hood design method of the present application.

[0054] In this embodiment, the hood design method includes steps S10 to S30:

[0055] Step S10, obtaining design parameter data.

[0056] It should be noted that when designing a carbon fiber hood, a series of key design parameter data must be obtained first, including but not limited to the expected hood weight, required modal frequency, and mechanical performance requirements under static and dynamic conditions. The weight of the hood directly affects the overall weight of the car. A lightweight hood helps reduce the total weight of the car, thereby improving fuel efficiency and reducing emissions. The modal frequency of the hood determines its natural frequency in vibration. A high modal frequency means that the hood is less likely to resonate during vehicle operation, thereby reducing noise and vibration and improving ride comfort. Under static loads, the stiffness of the hood determines its ability to resist deformation. High stiffness means that the hood is not easily deformed when under pressure and maintains its shape and function. Performance under static conditions also involves strength, that is, the maximum stress that the material can withstand without damage. High static strength ensures the integrity of the hood when it is impacted or pressed. The performance requirements under dynamic conditions take into account the fatigue strength of the hood under repeated loads, that is, how many cyclic loads the material can withstand without fatigue damage. Dynamic performance also involves the hood's ability to absorb and dissipate energy during an impact, which is critical to protecting the vehicle's interior components and passenger safety.

[0057] These parameters are determined based on the specific needs and usage conditions of the vehicle to ensure that the final design can meet the various challenges in practical applications. Next, based on these design parameters, the quadratic Bezier curve model is used to fit the fiber path in the carbon fiber composite material. By adjusting the fiber orientation angle and vertex position at the starting and end points, the change in fiber angle can be precisely controlled, thereby affecting the stiffness distribution of the entire hood structure.

[0058] Step S20, inputting a quadratic Bezier fitting carbon fiber curve model according to the design parameter data to obtain a fiber angle, wherein the quadratic Bezier fitting carbon fiber curve model is a model obtained by an optimization algorithm according to the design parameter data.

[0059] It should be noted that according to the design parameter data input quadratic Bezier fitting carbon fiber curve model, it is first necessary to determine the key points in the model, including the starting point, end point, and the position and direction of the control vertex. The selection of these points directly affects the distribution of fiber angles, and thus affects the stiffness characteristics of the entire hood. After determining the starting point and end point, the shape of the fiber path can be finely adjusted by adjusting the position of the control vertex, so that the fiber angle can change with the position, thereby achieving the purpose of adjustable local stiffness. This variable stiffness design method overcomes the limitations caused by the fixed fiber angle in traditional composite structures, and provides the possibility of achieving optimization under multiple performance objectives. Specifically, the corresponding parameters are input into the model, such as the fiber orientation angles at the starting point and the end point, and the position of the control point, and then the quadratic Bezier curve equation is used to calculate the fiber angle at any point on the fiber curve. By solving this equation, a continuously changing fiber angle distribution diagram on the entire fiber path can be obtained, such as Figure 2 Fiber angle distribution diagram shown.

[0060] Furthermore, before obtaining the fiber angle, it includes: obtaining design parameter sample data, establishing an initial quadratic Bezier fitting carbon fiber curve model, training the initial quadratic Bezier fitting carbon fiber curve model according to the design parameter sample data, and obtaining a quadratic Bezier fitting carbon fiber curve model. The training process obtains that the starting point and end point of the fiber curve are P0 and P1 respectively, the fiber direction angles at the starting point and end point are α0 and α1 respectively, the shape of the fiber curve changes with the vertex P2, and the fiber path of the quadratic Bezier curve can be expressed as:

[0061]

[0062] Among them, n is the vertex parameter, vertex P2 is between the starting point P0 and the end point P1, so 0 <n<1。

[0063] Then the curve fiber angle θ(x) at any point on the fiber curve of the initial quadratic Bessel fitting carbon fiber curve model is calculated as:

[0064]

[0065] Furthermore, the training process also includes: obtaining input data, obtaining the curve starting point, fiber starting angle, curve end point and fiber end point angle according to the input data, and then obtaining the actual fiber angle according to the curve starting point, fiber starting angle, curve end point and fiber end point angle. Specifically, firstly, a fast non-dominated sorting is performed by a multi-objective optimization algorithm according to the curve starting point, fiber starting angle, curve end point and fiber end point angle to obtain a good or bad grade. Fast non-dominated sorting is performed by the multi-objective optimization algorithm NSGA-II. In this process, the algorithm will evaluate all possible fiber angle combinations according to their influence on multiple design goals (such as lightweight and modal performance), and divide them into different levels, i.e., good or bad grades. The individuals in each level are non-dominated solutions, which means that they are better than individuals in other levels in at least one goal, and are not completely surpassed by any other individuals in other goals.

[0066] Furthermore, the process of obtaining the actual fiber angle also includes: calculating the crowding degree based on the superiority and inferiority grades to obtain the distribution density. It should be understood that after determining these superiority and inferiority grades, the crowding degree between individuals within each grade, that is, the distribution density, is further calculated. The crowding degree reflects the distribution of individuals in their grades, specifically the distance between the individual and its nearest neighbor, which is used to measure the diversity and uniformity of the solution set. A high crowding value indicates that the area around the individual is relatively empty, while a low crowding value indicates that the area is more crowded. Based on the calculation results of the crowding degree, the selection operation will give priority to retaining those individuals with higher crowding degrees, so as to maintain population diversity and prevent premature convergence.

[0067] Furthermore, the process of obtaining the actual fiber angle also includes: performing crossover and mutation operations according to the distribution density to obtain the actual fiber angle. Subsequently, the selected individuals are operated using the two genetic operators of crossover and mutation to generate new fiber angle combinations. The crossover operation simulates the process of gene recombination in nature. It randomly selects two parent individuals and mixes some of their characteristics to produce offspring; while mutation is to increase the exploration range of the search space by randomly changing the specific parameters of certain individuals to introduce new changes. After this step, the actual fiber angle set is obtained.

[0068] Furthermore, the training process also includes: inputting the input data into the initial quadratic Bezier fitting carbon fiber curve model to obtain the predicted fiber angle. Specifically, the input data is input into the initial quadratic Bezier fitting carbon fiber curve model for modal analysis to obtain the frequency difference and weight difference, which is implemented by finite element simulation software to evaluate the frequency response and weight characteristics of the hood under the current design, and compared with the preset target value to obtain the frequency difference and weight difference. Then, a fast non-dominated sorting is performed according to the frequency difference and weight difference through a multi-objective optimization algorithm to obtain the superiority level, and the crowding degree is calculated based on the superiority level to obtain the distribution density. Specifically, the multi-objective optimization algorithm NSGA-II is used to perform a fast non-dominated sorting of all possible design schemes according to their corresponding frequency difference and weight difference, so as to determine the relative superiority level of each design scheme in the overall solution set. On this basis, the crowding degree between individuals within each level, that is, the distribution density, is further calculated to quantify the dispersion degree of different solutions in the target space. A high crowding degree means that the solutions in the area are relatively sparse, while a low crowding degree indicates that the solutions in the area are very dense. Based on the size of the crowding degree, those individuals with higher crowding degrees are selected to enter the next generation, ensuring the diversity of the population while also promoting the exploration of the global optimal solution. Finally, the predicted fiber angle is obtained based on the distribution density, and new predicted fiber angle combinations are generated through genetic operators such as crossover and mutation. The crossover operation creates a new individual by combining partial features of two or more parent individuals, while mutation randomly changes the specific attributes of certain individuals to increase the breadth of the search space. After a series of iterations, a set of predicted fiber angles is finally obtained from the optimization process.

[0069] Furthermore, the training process also includes: according to the loss function calculation, the error value between the predicted fiber angle and the actual fiber angle is obtained, and the fiber angle is iteratively updated by the optimization algorithm until the maximum number of iterations is reached or the error value obtained by the loss function calculation converges to a preset threshold value, thereby obtaining a quadratic Bezier fitting carbon fiber curve model. After obtaining the model, the quadratic Bezier fitting carbon fiber curve model needs to be evaluated to obtain an evaluation result. If the evaluation result does not meet the control requirements, the quadratic Bezier fitting carbon fiber curve model is retrained until the control requirements are met.

[0070] Step S30, designing the hood according to the fiber angle to obtain a design result.

[0071] It should be understood that to design the hood based on the optimized fiber angle, it is first necessary to apply these angle data to the specific carbon fiber composite material layer structure. This step involves determining the specific laying direction and position of each layer of fiber to ensure that the entire hood can achieve the expected change in local stiffness. In the specific implementation process, the computer-aided design (CAD) software can intuitively display the angle distribution of each layer of fiber, and generate detailed manufacturing drawings based on this. Then, the design scheme based on the optimized fiber angle is comprehensively evaluated by finite element analysis (FEA) software, including but not limited to modal analysis, static analysis, and fatigue life prediction, so as to verify whether the design scheme meets the predetermined performance requirements, such as minimizing weight and maximizing modal frequency. In addition, the process feasibility in actual production needs to be considered, such as the complexity of operations during the layering process, curing conditions, etc., to ensure that the designed hood is not only feasible in theory, but also can be smoothly realized in the actual manufacturing process. Once the simulation results show that all performance indicators are in line with expectations, it can be further advanced to the prototype stage. During this period, it may also be necessary to work closely with the manufacturer to adjust the production process parameters, such as the selection of prepregs, mold design, and hot pressing molding temperature and pressure control, to ensure that the final product can reach the optimal state. After a series of rigorous test verifications, if all test results show that the newly designed hood meets the requirements of lightweight and high performance, it can enter the mass production preparation stage.

[0072] This embodiment provides a hood design method, which obtains design parameter data, inputs a quadratic Bezier fitting carbon fiber curve model according to the design parameter data, obtains a fiber angle, designs the hood according to the fiber angle, and obtains a design result. Based on the quadratic Bezier curve fitting fiber angle, a multi-objective algorithm is used to optimize the design to achieve lightweight hood and improved modal performance.

[0073] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can refer to the above introduction, and will not be repeated later. Figure 3 The hood design method step S30 further includes steps S301 to S303:

[0074] Step S301, generating a three-dimensional model of the hood according to the fiber angle.

[0075] It should be noted that these fiber angle data need to be imported into professional 3D modeling software, such as CATIA, SolidWorks or Fusion 360. In the software, a detailed 3D model can be constructed based on the basic geometry of the hood and the specific laying direction of each layer of carbon fiber composite material. This step not only includes the change of fiber angle, but also covers the design of material thickness, ply sequence and any necessary reinforcement structure. By accurately setting the angle and position of each layer of fiber, it is ensured that the entire hood can achieve the adjustment of local stiffness as expected. In addition, the requirements of the actual manufacturing process, such as the cutting size of prepreg, mold design and potential problems in the molding process, must also be considered during the modeling process. After completing the preliminary modeling, virtual verification is performed using simulation tools, including static strength analysis, dynamic response testing, and thermomechanical performance evaluation, to ensure that the 3D model meets all design goals. Finally, a 3D model that meets the mechanical performance requirements and is easy to produce is generated.

[0076] Step S302: perform finite element analysis on the three-dimensional model to obtain analysis results.

[0077] It should be understood that to perform finite element analysis on the generated three-dimensional model, it is first necessary to establish an analysis model in professional simulation software, such as ANSYS, Abaqus or HyperWorks. After setting the material properties and boundary conditions, the hood model is discretized into a large number of small units by dividing the grid, so as to more accurately simulate the mechanical behavior under the actual working state. Next, different load conditions are set according to the design requirements, including static load, dynamic load and vibration analysis, to comprehensively evaluate the performance of the hood under various use conditions. Finite element analysis can provide detailed key data such as stress distribution, displacement, modal frequency, etc., to help engineers identify potential weak links and make targeted optimizations. In addition, fatigue life prediction can be performed to ensure that the hood will not fail during long-term use. By carefully reviewing the analysis results, it can be verified whether the hood meets the predetermined design goals, such as the balance between lightweight and high strength. If it is found that some areas have insufficient performance, it is necessary to return to the design stage to adjust the fiber angle or other structural parameters until all performance indicators meet the preset design requirements.

[0078] Step S303, adjusting the hood design according to the analysis results until the preset design requirements are met to obtain a design result, wherein the preset design requirements include hood weight, modal frequency and hood stiffness.

[0079] It should be noted that, according to the results of finite element analysis, the hood design is adjusted until the preset design requirements are met. First, for the stress concentration areas or parts with insufficient stiffness found in the analysis, the performance is improved by adjusting the fiber angle, adding local reinforcement structure or optimizing the ply order. For example, if the stiffness of a certain area is lower than expected, its stiffness can be enhanced by increasing the fiber density in that area or changing the fiber direction; if the modal frequency does not meet the standard, the fiber path needs to be reset to increase the overall stiffness, thereby improving the frequency response. At the same time, in order to ensure that the weight of the hood meets the lightweight goal, while ensuring the structural strength and stiffness, the use of unnecessary materials is reduced as much as possible, such as optimizing the thickness of non-critical areas or using a more efficient combination of composite materials. After each adjustment, a finite element analysis needs to be repeated to verify the improvement effect and compare it with the preset design requirements such as weight, modal frequency and stiffness. This iterative process will continue until all performance indicators meet the preset design requirements.

[0080] In this embodiment, a three-dimensional model of the hood is generated according to the fiber angle, and a finite element analysis is performed on the three-dimensional model to obtain an analysis result. The hood design is adjusted according to the analysis result until the preset design requirements are met to obtain a design result. A three-dimensional model is generated based on the fiber angle, and finite element analysis and iterative optimization are performed to ensure that the hood meets the weight, modal frequency and stiffness requirements, thereby achieving high-precision and high-performance design of the hood.

[0081] This application also provides a hood design device, please refer to Figure 4 , the device comprises:

[0082] The acquisition module 10 is used to acquire design parameter data.

[0083] The acquisition module 10 is also used to input the quadratic Bezier fitting carbon fiber curve model according to the design parameter data to obtain the fiber angle. The quadratic Bezier fitting carbon fiber curve model is a model obtained by an optimization algorithm according to the design parameter data.

[0084] The result module 20 is used to design the hood according to the fiber angle and obtain the design result.

[0085] The hood design device provided by the present application adopts the hood design method in the above embodiment, which can solve the technical problem of how to improve the accuracy and performance of the hood. Compared with the prior art, the beneficial effects of the hood design device provided by the present application are the same as the beneficial effects of the hood design method provided by the above embodiment, and the other technical features in the hood design device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0086] In one embodiment, the acquisition module 10 is also used to acquire design parameter sample data and establish an initial quadratic Bezier fitting carbon fiber curve model; the initial quadratic Bezier fitting carbon fiber curve model is trained according to the design parameter sample data to obtain a quadratic Bezier fitting carbon fiber curve model.

[0087] In one embodiment, the acquisition module 10 is also used to obtain input data; based on the input data, the starting point of the curve, the fiber starting angle, the end point of the curve and the fiber end point angle are obtained; based on the starting point of the curve, the fiber starting angle, the end point of the curve and the fiber end point angle, the actual fiber angle is obtained; the input data is input into the initial quadratic Bezier fitting carbon fiber curve model to obtain the predicted fiber angle; according to the loss function calculation, the error value between the predicted fiber angle and the actual fiber angle is obtained; the fiber angle is iteratively updated through the optimization algorithm until the maximum number of iterations is reached or the error value calculated by the loss function converges to a preset threshold, thereby obtaining the quadratic Bezier fitting carbon fiber curve model.

[0088] In one embodiment, the acquisition module 10 is also used to perform fast non-dominated sorting according to the curve starting point, the fiber starting point angle, the curve end point and the fiber end point angle through a multi-objective optimization algorithm to obtain a quality grade; calculate the congestion degree based on the quality grade to obtain the distribution density; perform crossover and mutation operations according to the distribution density to obtain the actual fiber angle.

[0089] In one embodiment, the acquisition module 10 is also used to input the input data into the initial quadratic Bezier fitting carbon fiber curve model for modal analysis to obtain frequency difference and weight difference; perform fast non-dominated sorting through a multi-objective optimization algorithm based on the frequency difference and weight difference to obtain a grade of excellence; calculate the degree of congestion based on the grade of excellence to obtain the distribution density; and obtain the predicted fiber angle based on the distribution density.

[0090] In one embodiment, the acquisition module 10 is further used to evaluate the quadratic Bezier fitting carbon fiber curve model to obtain an evaluation result; if the evaluation result does not meet the control requirements, the quadratic Bezier fitting carbon fiber curve model is retrained until the control requirements are met.

[0091] In one embodiment, the result module 20 is also used to generate a three-dimensional model of the hood according to the fiber angle; perform finite element analysis on the three-dimensional model to obtain analysis results; adjust the hood design according to the analysis results until the preset design requirements are met to obtain design results, wherein the preset design requirements include hood weight, modal frequency and hood stiffness.

[0092] The present application provides a hood design device, which includes: at least one processor; and a memory that is communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the hood design method in the above-mentioned embodiment one.

[0093] Reference below Figure 5 , which shows a schematic diagram of the structure of a hood design device suitable for implementing the embodiment of the present application. The hood design device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The hood design device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0094] like Figure 5 As shown, the hood design device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the hood design device are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the hood design device to communicate with other devices wirelessly or wired to exchange data. Although the hood design device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0095] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through a communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0096] The hood design device provided by the present application adopts the hood design method in the above embodiment, which can solve the technical problem of how to improve the accuracy and performance of the hood. Compared with the prior art, the beneficial effects of the hood design device provided by the present application are the same as the beneficial effects of the hood design method provided by the above embodiment, and the other technical features in the hood design device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0097] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0098] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0099] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the hood design method in the above-mentioned embodiment.

[0100] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible storage medium that contains or stores a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate storage medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0101] The computer-readable storage medium may be included in the hood design device; or may exist independently without being assembled into the hood design device.

[0102] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the hood design device, the hood design device can write computer program codes for performing the operations of the present application in one or more programming languages ​​or a combination thereof. The programming languages ​​include object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0103] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0104] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0105] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned hood design method, and can solve the technical problem of how to improve the accuracy and performance of the hood. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the hood design method provided by the above-mentioned embodiment, and will not be repeated here.

[0106] The present application also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the hood design method as described above are implemented.

[0107] The computer program product provided by the present application can solve the technical problem of how to improve the accuracy and performance of the hood. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the hood design method provided by the above embodiment, which will not be repeated here.

[0108] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A hood design method, characterized in that: The method comprises: Obtain design parameter data; Input a quadratic Bezier fitting carbon fiber curve model according to the design parameter data to obtain a fiber angle, wherein the quadratic Bezier fitting carbon fiber curve model is a model obtained by an optimization algorithm according to the design parameter data; The hood is designed according to the fiber angle to obtain a design result.

2. The method according to claim 1, characterized in that Before the step of inputting the quadratic Bezier fitting carbon fiber curve model according to the design parameter data to obtain the fiber angle, the step includes: Acquire design parameter sample data and establish an initial quadratic Bezier fitting carbon fiber curve model, wherein the design parameter sample data includes hood weight, modal frequency, and mechanical performance requirements under static and dynamic conditions; The initial quadratic Bezier fitting carbon fiber curve model is trained according to the design parameter sample data to obtain a quadratic Bezier fitting carbon fiber curve model.

3. The method according to claim 2, characterized in that The step of training the initial quadratic Bezier fitting carbon fiber curve model according to the design parameter sample data to obtain the quadratic Bezier fitting carbon fiber curve model comprises: Get input data; According to the input data, the starting point of the curve, the starting angle of the fiber, the end point of the curve and the end point angle of the fiber are obtained; Obtaining an actual fiber angle according to the starting point of the curve, the fiber starting angle, the end point of the curve and the fiber end point angle; Inputting the input data into the initial quadratic Bezier fitting carbon fiber curve model to obtain a predicted fiber angle; According to the loss function calculation, the error value between the predicted fiber angle and the actual fiber angle is obtained; The fiber angle is iteratively updated through an optimization algorithm until a maximum number of iterations is reached or an error value calculated by a loss function converges to a preset threshold, thereby obtaining a quadratic Bezier fitting carbon fiber curve model.

4. The method according to claim 3, characterized in that The step of obtaining the actual fiber angle according to the starting point of the curve, the fiber starting angle, the end point of the curve and the fiber end point angle comprises: According to the starting point of the curve, the starting angle of the fiber, the end point of the curve and the end point angle of the fiber, a fast non-dominated sorting is performed through a multi-objective optimization algorithm to obtain a superiority or inferiority grade; Calculate the congestion degree based on the merits and demerits to obtain the distribution density; A crossover and a mutation operation are performed according to the distribution density to obtain the actual fiber angle.

5. The method according to claim 3, characterized in that The step of inputting the input data into the initial quadratic Bezier fitting carbon fiber curve model to obtain a predicted fiber angle comprises: Inputting the input data into the initial quadratic Bezier fitting carbon fiber curve model for modal analysis to obtain frequency difference and weight difference; Performing fast non-dominated sorting by a multi-objective optimization algorithm according to the frequency difference and the weight difference to obtain a quality grade; Calculate the congestion degree based on the merits and demerits to obtain the distribution density; The predicted fiber angle is obtained based on the distribution density.

6. The method according to claim 2, characterized in that After the step of training the initial quadratic Bezier fitting carbon fiber curve model according to the design parameter sample data to obtain the quadratic Bezier fitting carbon fiber curve model, the method further comprises: Evaluating the quadratic Bezier fitting carbon fiber curve model to obtain an evaluation result; If the evaluation result does not meet the control requirement, the quadratic Bezier fitting carbon fiber curve model is retrained until the control requirement is met.

7. The method according to claim 1, characterized in that The step of designing the hood according to the fiber angle to obtain a design result comprises: generating a three-dimensional model of the hood according to the fiber angle; Performing finite element analysis on the three-dimensional model to obtain analysis results; The hood design is adjusted according to the analysis results until the preset design requirements are met to obtain a design result, wherein the preset design requirements include hood weight, modal frequency and hood stiffness.

8. A hood design device, characterized in that: The device comprises: An acquisition module, used for acquiring design parameter data; The acquisition module is further used to input a quadratic Bezier fitting carbon fiber curve model according to the design parameter data to obtain a fiber angle, wherein the quadratic Bezier fitting carbon fiber curve model is a model obtained by an optimization algorithm according to the design parameter data; The result module is used to design the hood according to the fiber angle to obtain a design result.

9. A hood design device, characterized in that: The device comprises: a memory, a processor, and a hood design program stored in the memory and executable on the processor, wherein the hood design program is configured to implement the steps of the hood design method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a hood design program, and when the hood design program is executed by the processor, the steps of the hood design method according to any one of claims 1 to 7 are implemented.

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