Automobile door outer plate digital structure optimization design method and system

Abstract

The invention relates to an optimization design method and system for a digital structure of an automobile door outer plate, belongs to the technical field of automobile door systems, and solves the problem that all performances of the automobile door outer plate cannot be considered and planned as a whole during design in the prior art. Comprising the following steps: constructing four groups of car door outer plate thickness-performance index digital arrays within a preset car door plate thickness range; comprising a thickness-rigidity digital array, a thickness-crashworthiness digital array, a thickness-manufacturing process digital array and a thickness-lightweight digital array; respectively carrying out data fitting on the four groups of car door outer plate thickness-performance index digital arrays to obtain four car door outer plate performance index functions; and taking the thickness of the vehicle door outer panel as a variable, constructing a vehicle door outer panel multi-objective optimization model based on the four vehicle door outer panel performance index functions, and solving to obtain the optimal thickness of the vehicle door outer panel. The research and development period of interactive discussion among design, performance and technology in the research and development process is shortened.

Description

Technical Field

[0001] This invention relates to the field of automotive door system technology, and in particular to a digital structural optimization design method and system for automotive door outer panels. Background Technology

[0002] In the overall automotive system, car doors primarily serve to protect the safety of occupants and provide adequate isolation between the passenger compartment and external noise. As a large metal component within the door assembly, the structural performance, manufacturing process, and weight of the door outer panel significantly impact the vehicle's safety, stable production, and fuel economy. The structural rigidity and collision safety performance of the door outer panel greatly influence the safety and comfort of the driver within the passenger compartment, especially in pole impact tests, where the door's impact resistance directly affects the overall pole impact result. However, as one of the large, difficult-to-form thin-walled parts in automotive manufacturing, the door outer panel frequently suffers from stamping problems such as cracking and wrinkling, making its manufacturability quite challenging in actual manufacturing. Furthermore, as a large metal component within the door assembly, the door outer panel accounts for 5%-10% of the entire door assembly's weight; therefore, its weight and its reduction directly affect the vehicle's fuel consumption, driving range, and other aspects of its performance and economy. The structural rigidity, impact resistance, manufacturing process, and lightweight properties of the car door outer panel are interdependent and mutually restrictive. It is necessary to use appropriate lightweight technologies and methods to solve and balance these factors based on the actual situation of the car door.

[0003] The structural rigidity, impact resistance, manufacturing process performance, and lightweight performance of car door outer panels belong to different disciplines and are related to various aspects of performance and process. These include linear structural rigidity issues, nonlinear large structural deformation issues, forming process issues closely related to materials, and lightweighting issues from multiple disciplines. The four major performance characteristics of car doors are generally studied and discussed separately by each professional direction and technical method. In particular, the manufacturability is often considered separately from the usability and used as a verification indicator. However, in actual engineering applications, designers often need to balance the above performance characteristics and seek the optimal design value. Conventional analysis methods such as topology optimization and sensitivity analysis are no longer sufficient to solve optimization problems involving multiple objectives and multiple disciplines. Summary of the Invention

[0004] Based on the above analysis, the embodiments of the present invention aim to provide a digital structural optimization design method and system for automotive door outer panels, in order to solve the problem that the various performance characteristics of existing automotive door outer panels cannot be taken into account and coordinated during the design process.

[0005] The objective of this invention is mainly achieved through the following technical solutions:

[0006] This invention provides a digital structural optimization design method for automotive door outer panels, comprising the following steps:

[0007] Construct four sets of digital arrays of door outer panel thickness and performance indicators within a preset door panel thickness range; wherein, the four sets of digital arrays of door outer panel thickness and performance indicators are: thickness-rigidity digital array, thickness-crash resistance digital array, thickness-manufacturing process digital array, and thickness-lightweight digital array;

[0008] Four door outer panel performance index functions were obtained by fitting data to the four sets of digital arrays of door outer panel thickness and performance index.

[0009] Using the thickness of the outer door panel as a variable, a multi-objective optimization model for the outer door panel is constructed based on four performance index functions of the outer door panel, and the optimal outer door panel thickness is obtained by solving the model.

[0010] Furthermore, four sets of digital arrays of door outer panel thickness and performance indicators are constructed within a preset door panel thickness range, including:

[0011] The thickness of the outer door panel is divided into several values ​​within a preset range;

[0012] Based on the thickness of each of the door outer panels after equalization, simulation analysis software is used to simulate and obtain the maximum sinking displacement, maximum intrusion displacement, maximum thinning rate, and maximum total weight of the door outer panel under each of the aforementioned door outer panel thicknesses.

[0013] Based on the thickness of each of the aforementioned outer door panels and the corresponding maximum downward displacement, maximum intrusion displacement, maximum thinning rate, and maximum total weight of the outer door panels, thickness-rigidity digital arrays, thickness-crash resistance digital arrays, thickness-manufacturing process digital arrays, and thickness-lightweight digital arrays are constructed respectively.

[0014] Furthermore, the four door outer panel performance index functions include the door outer panel sinking displacement function, the pillar impact intrusion displacement function, the door outer panel thinning rate function, and the door outer panel total weight function; the four door outer panel performance index functions are obtained by fitting the data of the four sets of door outer panel thickness-performance index digitized arrays respectively, including:

[0015] Based on the thickness and maximum sinking displacement of the outer door panel in the thickness-stiffness digitized array, the sinking displacement function of the outer door panel is obtained by fitting using the least squares method.

[0016] Based on the thickness of the outer door panel and the maximum intrusion displacement in the thickness-crash resistance digitized array, the pole impact intrusion displacement function is obtained by fitting using the least squares method.

[0017] Based on the thickness and maximum thinning rate of the outer door panel in the thickness-manufacturing process digit array, the thinning rate function of the outer door panel is obtained by fitting using the least squares method.

[0018] Based on the thickness and maximum total weight of the door outer panel in the thickness-lightweight digitized array, the total weight function of the door outer panel is obtained by fitting using the least squares method.

[0019] Furthermore, using the downward displacement function of the outer door panel as a constraint, and the pole impact intrusion displacement function, the thinning rate function of the outer door panel, and the total weight function of the outer door panel as objective functions, a multi-objective optimization model for the outer door panel is constructed.

[0020] Furthermore, the optimization objectives of the multi-objective optimization model for the outer door panel include: minimizing the pole impact intrusion displacement, minimizing the thinning rate of the outer door panel, and minimizing the total weight of the outer door panel, all under the constraint that the sinking displacement is less than the maximum sinking displacement under a predetermined vertical load.

[0021] Furthermore, the multi-objective optimization model for the car door outer panel uses an adaptive process second-generation genetic algorithm to obtain the Pareto solution front, and selects the optimal car door outer panel thickness as the final solution from the Pareto solution front, including:

[0022] The thickness of each of the equally divided outer door panels is used as the initial population and coded accordingly;

[0023] Based on the objective functions of pole collision intrusion displacement, door outer panel thinning rate, and total weight of door outer panel, the dominance level and crowding distance of each coded entity are calculated, and the fitness value of each entity is obtained based on the dominance level and crowding distance of each entity.

[0024] Based on the fitness values ​​of each individual, the Pareto solution front is obtained by performing selection, crossover, and mutation operations on each individual using an elite strategy.

[0025] Furthermore, linear calculation analysis software was used to calculate the maximum downward displacement of the outer door panel and the maximum total weight of the outer door panel corresponding to the thickness of each outer door panel.

[0026] Furthermore, the maximum intrusion displacement of the outer door panel corresponding to the thickness of each outer door panel was calculated using nonlinear large deformation dynamic analysis software.

[0027] Furthermore, the maximum thinning rate of the outer door panel corresponding to the thickness of each of the aforementioned outer door panels was calculated using stamping process analysis software.

[0028] On the other hand, the present invention provides a digital structure optimization system for automotive door outer panels, comprising:

[0029] The performance index digital extraction module is used to simulate and obtain the maximum sinking displacement, maximum intrusion displacement, maximum thinning rate, and maximum total weight of the outer door panel under each thickness within the preset door panel thickness range using simulation analysis software. It constructs digital arrays of thickness-rigidity, thickness-crash resistance, thickness-manufacturing process, and thickness-lightweight respectively.

[0030] The performance index function generation module is used to perform data fitting on the thickness-rigidity digital array, thickness-crash resistance digital array, thickness-manufacturing process digital array, and thickness-lightweight digital array to obtain the door outer panel sink displacement function, pole impact intrusion displacement function, door outer panel thinning rate function, and door outer panel total weight function, respectively.

[0031] The multi-objective optimization model construction and solution module is used to construct a multi-objective optimization model for the outer door panel, with the thickness of the outer door panel as a variable, the downward displacement function of the outer door panel as a constraint, and the pole impact intrusion displacement function, the thinning rate function of the outer door panel, and the total weight function of the outer door panel as objective functions. The optimization objectives are to minimize the pole impact intrusion displacement, the thinning rate of the outer door panel, and the total weight of the outer door panel. The optimal outer door panel thickness is obtained by using a second-generation genetic algorithm with an adaptive process to obtain the Pareto solution front.

[0032] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0033] 1. The technical solution of the present invention takes into account both the structural performance and manufacturing process performance of the car door outer panel. It comprehensively considers four interdisciplinary performance issues that are related and mutually restrictive: excellent rigidity and strength performance, strong impact resistance, manufacturing process and lightweight performance of the car door outer panel.

[0034] 2. The technical solution of the present invention is highly feasible. In the process of developing car door assemblies, it can shorten the development cycle of interactive discussions among design, performance and process. At the same time, the technical solution of the present invention can be extended to other mechanical engineering structures, and has strong scalability and applicability.

[0035] 3. The technical solution of this invention ensures good manufacturability of the structure in the subsequent manufacturing process by using specific digital indicators as constraints during the design stage. At the same time, by incorporating structural weight factors into the performance factors, it balances and alleviates the conflicts and contradictions between structural usability, manufacturability and lightweight performance. Under the premise of taking into account the good rigidity and strength, excellent impact resistance and considerable manufacturability of the door outer panel, the weight of the door outer panel is reduced. This will indirectly provide a more effective implementation method for achieving the vehicle weight index and economic index in the development of the whole vehicle project.

[0036] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0037] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0038] Figure 1 This is a flowchart illustrating a digital structure optimization design method for an automotive door outer panel according to an embodiment of the present invention.

[0039] Figure 2 This is a schematic diagram of the displacement function of the column collision in an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram of the Pareto solution front in an embodiment of the present invention. Detailed Implementation

[0041] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0042] A specific embodiment of the present invention discloses a digital structural optimization design method for automotive door outer panels, such as... Figure 1 As shown, it includes the following steps S1-S3:

[0043] Step S1: Construct four sets of digital arrays of door outer panel thickness and performance indicators within the preset door panel thickness range; wherein, the four sets of digital arrays of door outer panel thickness and performance indicators are: thickness-rigidity digital array, thickness-crash resistance digital array, thickness-manufacturing process digital array and thickness-lightweight digital array.

[0044] Specifically, digital indicators are extracted for the performance and manufacturing process of the car door outer panel, including:

[0045] Regarding the stiffness and strength performance of the outer door panel, the sag stiffness of the door is of particular concern. The most representative characteristic of sag stiffness is the maximum sag displacement of the door under a certain vertical load. The smaller this displacement, the stronger the door's ability to resist sag deformation and the stronger its sag stiffness. Here, the maximum sag displacement obtained by different doors under a predetermined vertical load will be used as a digital indicator to evaluate the stiffness and strength performance of the outer door panel.

[0046] The crashworthiness of a car door outer panel refers to the structural integrity and degree of deformation of the door upon impact. It can be assessed by measuring the amount of deformation during a standard crash test. This is typically determined by the door's pole impact resistance, with the maximum intrusion displacement during a pole impact reflecting the door's resistance to such impacts; a smaller maximum intrusion displacement indicates better pole impact resistance. Therefore, the maximum intrusion displacement of the door after a collision at a predetermined speed will be used as a digital indicator to evaluate the crashworthiness of the door outer panel.

[0047] Regarding the manufacturing process performance of car door outer panels, thinning rate and wrinkles are two commonly used indicators for measuring the stamping performance of car door outer panels. Thinning rate refers to the change in material thickness during the stamping or stretching process of metal sheets; it is the proportion or amount by which the material's thickness is reduced relative to its original thickness after processing. Controlling the thinning rate is crucial in design and manufacturing, as excessive thinning can lead to decreased material strength and even cracks or fractures. Wrinkles, on the other hand, refer to a series of uneven folds or creases formed on the material surface during metal processing. These wrinkles are usually caused by uneven stretching or compression in localized areas when the material is subjected to external forces. However, since wrinkles lack quantifiable characteristics, the maximum thinning rate of the car door outer panel after stamping is used as a quantifiable indicator of its manufacturing process performance. A higher maximum thinning rate indicates a greater likelihood of stamping cracks or wrinkles, and a poorer manufacturing process.

[0048] Regarding the lightweight performance of the outer door panels, the total weight of the outer door panels is used as a digital indicator to evaluate the lightweight performance of the outer door panels. The smaller the weight, the better the lightweight effect.

[0049] Furthermore, four sets of digital arrays of door outer panel thickness and performance indicators are constructed within a preset door panel thickness range, including:

[0050] The thickness of the outer door panel is divided into several values ​​within a preset range;

[0051] Specifically, the thickness of the outer door panel is used as a design variable in the optimization model. The uniform design method is used to uniformly divide the thickness of the outer door panel within a preset range. For example, the preset range of the outer door panel thickness is 0.55-0.8 cm. The outer door panel thickness is uniformly divided at intervals of 0.008 cm to obtain the segmented outer door panel thickness array.

[0052] Based on the thickness of each of the door outer panels after equalization, simulation analysis software is used to simulate and obtain the maximum sinking displacement, maximum intrusion displacement, maximum thinning rate, and maximum total weight of the door outer panel under each of the aforementioned door outer panel thicknesses.

[0053] Furthermore, since the thickness of the outer door panel is linearly related to the maximum downward displacement and the maximum total weight of the outer door panel, that is, the thicker the outer door panel, the smaller the downward displacement of the outer door panel under a fixed vertical load; and the thicker the outer door panel, the greater the total weight of the outer door panel, the maximum downward displacement and the maximum total weight of the outer door panel corresponding to each of the aforementioned outer door panel thicknesses can be calculated using linear calculation analysis software.

[0054] For example, the maximum downward displacement of the outer door panel and the maximum total weight of the outer door panel are obtained by simulation using ABAQUS finite element analysis software.

[0055] Furthermore, the maximum intrusion displacement of the outer door panel corresponding to the thickness of each outer door panel was calculated using nonlinear large deformation dynamic analysis software.

[0056] Specifically, a car collision is an instantaneous dynamic process in which the structure and materials involved in the collision area undergo dynamic large deformation in a very short time. It involves multiple nonlinear characteristics of structure and materials, and belongs to nonlinear dynamic contact problems. The nonlinear large deformation dynamic display finite element method is suitable for analyzing its collision process. For example, LS-DYNA or PAM-CRASH can be used to simulate the maximum intrusion displacement of the car door outer panel.

[0057] Furthermore, the maximum thinning rate of the outer door panel corresponding to the thickness of each of the aforementioned outer door panels was calculated using stamping process analysis software.

[0058] Specifically, thinning rate simulation analysis software is mainly used to simulate and analyze the thickness changes of materials during processing, such as stamping, stretching, and bending. Stamping process analysis software is used to simulate and analyze various physical phenomena in the stamping process of metal sheets, adjusting process parameters to obtain thinning rate results. For example, analysis tools such as AutoForm or Ansys Forming can be used.

[0059] Based on the thickness of each of the aforementioned outer door panels and the corresponding maximum downward displacement, maximum intrusion displacement, maximum thinning rate, and maximum total weight of the outer door panels, thickness-rigidity digital arrays, thickness-crash resistance digital arrays, thickness-manufacturing process digital arrays, and thickness-lightweight digital arrays are constructed respectively.

[0060] Specifically, the thickness-stiffness digitized array is a two-dimensional array composed of the segmented door outer panel thickness array and the maximum downward displacement of the door outer panel corresponding to each segmented door outer panel thickness obtained by simulation analysis software; for example, the thickness-stiffness digitized array is represented as follows: {[0.550,5.0],[0.558,4.9],……,[0.800,3.0]}; where the first number in each array represents the door outer panel thickness (unit: mm), and the second number represents the maximum downward displacement of the door outer panel (unit: mm).

[0061] The thickness-crash resistance digitized array is a two-dimensional array composed of the segmented door outer panel thickness array and the maximum intrusion displacement of the door outer panel corresponding to each segmented door outer panel thickness obtained by simulation analysis software; for example, the thickness-crash resistance digitized array is represented as follows: {[0.550,205.0],[0.558,198.0],……,[0.800,170.0]}; wherein, the first number in each array represents the door outer panel thickness (unit: mm), and the second number represents the maximum intrusion displacement of the door outer panel (unit: mm).

[0062] The thickness-manufacturing process digitization array is a two-dimensional array composed of the segmented door outer panel thickness array and the maximum thinning rate of the door outer panel corresponding to each segmented door outer panel thickness obtained by simulation analysis software; for example, the thickness-manufacturing process digitization array is represented as follows: {[0.550,20],[0.558,18],……,[0.800,5]}; where the first number in each array represents the door outer panel thickness (unit: mm), and the second number represents the maximum thinning rate of the door outer panel (unit: %).

[0063] The thickness-lightweight digitized array is a two-dimensional array composed of the segmented door outer panel thickness array and the maximum total weight of the door outer panel corresponding to each segmented door outer panel thickness obtained by simulation analysis software; for example, the thickness-lightweight digitized array is represented as follows: {[0.550,25],[0.558,27],……,[0.800,40]}; where the first number in each array represents the door outer panel thickness (unit: millimeters), and the second number represents the maximum total weight of the door outer panel (unit: kilograms).

[0064] Step S2: Perform data fitting on the four sets of digital arrays of door outer panel thickness-performance index to obtain four door outer panel performance index functions.

[0065] Furthermore, the four door outer panel performance index functions include the door outer panel sink displacement function, the pillar impact intrusion displacement function, the door outer panel thinning rate function, and the door outer panel total weight function.

[0066] Based on the thickness and maximum sinking displacement of the outer door panel in the thickness-stiffness digitized array, the sinking displacement function of the outer door panel is obtained by fitting using the least squares method.

[0067] like Figure 2 As shown, based on the thickness of the outer door panel and the maximum intrusion displacement in the thickness-crash resistance digitized array, the pole impact intrusion displacement function is obtained by fitting using the least squares method;

[0068] Based on the thickness and maximum thinning rate of the outer door panel in the thickness-manufacturing process digit array, the thinning rate function of the outer door panel is obtained by fitting using the least squares method.

[0069] Based on the thickness and maximum total weight of the door outer panel in the thickness-lightweight digitized array, the total weight function of the door outer panel is obtained by fitting using the least squares method.

[0070] Specifically, the least squares method is a commonly used linear regression fitting technique that finds the best function match for the data by minimizing the sum of squared errors.

[0071] Step S3: Using the thickness of the outer door panel as a variable, construct a multi-objective optimization model for the outer door panel based on four performance index functions of the outer door panel, and solve for the optimal outer door panel thickness.

[0072] Furthermore, using the downward displacement function of the outer door panel as a constraint, and the pole impact intrusion displacement function, the thinning rate function of the outer door panel, and the total weight function of the outer door panel as objective functions, a multi-objective optimization model for the outer door panel is constructed.

[0073] Specifically, the multi-objective optimization model is a mathematical model that considers multiple conflicting or independent optimization objectives simultaneously when optimizing a problem, and seeks the best trade-off solution among the optimization objectives.

[0074] Furthermore, the optimization objectives of the multi-objective optimization model for the outer door panel include: minimizing the pole impact intrusion displacement, minimizing the thinning rate of the outer door panel, and minimizing the total weight of the outer door panel, all under the constraint that the sinking displacement is less than the maximum sinking displacement under a predetermined vertical load.

[0075] Furthermore, when solving the multi-objective optimization model, an adaptive second-generation genetic algorithm is used to obtain the Pareto solution front, and the optimal door outer panel thickness is selected from the Pareto solution front as the final solution.

[0076] Specifically, in this embodiment, the second-generation genetic algorithm for the adaptive process uses the NSGA-II optimization algorithm, including steps S31-S33:

[0077] It should be noted that the NSGA-II algorithm is a fast non-dominated multi-objective optimization algorithm with an elitist preservation strategy, and it is a genetic algorithm that generates Pareto solution fronts.

[0078] Step S31: The thickness of each of the equally divided car door outer panels is used as the initial population and encoded.

[0079] Specifically, the initial population obtained using a uniform distribution method has an equal probability of being selected for each possible value between the minimum and maximum thickness of the car door outer panel; the chromosomes of individuals are obtained by binary encoding of the initial population.

[0080] Step S32: Based on the objective function of pole collision intrusion displacement, the objective function of door outer panel thinning rate, and the objective function of total weight of door outer panel, calculate the dominance level and congestion distance of each body after encoding, and obtain the fitness value of each body based on the dominance level and congestion distance of each body.

[0081] Specifically, since all objective functions in this embodiment are minimization problems, the objective functions of pole collision intrusion displacement, door outer panel thinning rate, and total weight of door outer panel are respectively subjected to min-max standardization calculation. That is, the minimum and maximum values ​​of each objective function in the current population are calculated, and then the original values ​​are converted into standardized values ​​in the interval [0,1]. The standardized objective function values ​​are used to eliminate the influence of the dimensions and numerical ranges between different objective functions, and can be compared and comprehensively evaluated on the same scale.

[0082] Furthermore, due to the existence of multiple objective functions, and the inability to compare and rank feasible solutions (solutions that satisfy the optimization conditions) using traditional size comparisons, the inter-objective relationships in the multi-objective case are defined. Therefore, in the multi-objective optimization process, a dominance relationship is defined: a solution is considered to dominate another solution if it is no worse than the other solution in all objectives and is better than that solution in at least one objective. This means that the dominated solution cannot be better than the solution that dominates it in all objectives simultaneously.

[0083] First, initialize the dominance level of each individual in the population to 0, indicating that no individual is dominated. Next, iterate through each individual in the population. For each individual, check if it dominates other individuals. If individual A is no worse than individual B in all objectives and better than individual B in at least one objective, then individual A is considered to dominate individual B. Then, for individual B dominated by individual A, increment its dominance level by 1, meaning that individuals dominated by more individuals have a higher dominance level. For each individual, record how many other individuals it dominates; the more individuals it dominates, the better its position in the objective space. After completing the dominance sort, divide all individuals into different dominance levels. The first dominance level (Front 1) contains all solutions not dominated by any other solutions, and the second dominance level (Front 2) contains all solutions dominated only by solutions in the first dominance level (Front 1). The first dominance level, which represents the candidates for the Pareto optimal solution set, consists of individuals that are not dominated by any other individuals.

[0084] It should be noted that if two or more individuals belong to the same dominance hierarchy and there is no mutual dominance relationship between them, these solutions are called peer individuals. In this case, the crowding degree of the individuals is calculated to further distinguish these individuals; the greater the crowding degree of an individual, the lower its density in its dominance hierarchy and the higher its position in the dominance hierarchy.

[0085] Furthermore, the fitness value of each individual is calculated based on the individual's dominance level and crowding degree. For example, fitness value = w1 * dominance level + w2 * crowding degree; where w1 and w2 are weighting coefficients used to balance the importance of dominance level and crowding degree in fitness.

[0086] Step S33: Based on the fitness values ​​of each individual, use an elite strategy to perform selection, crossover, and mutation operations on each individual to obtain the Pareto solution front.

[0087] Specifically, the individual with the highest fitness value among all individuals is selected as the elite individual and directly enters the next generation; two individuals are selected from the remaining individuals using a roulette wheel method as parent individuals; improved crossover and mutation operations are performed on the parent individuals to generate offspring individuals.

[0088] It should be noted that the mutation operation can randomly change the door thickness value of an individual.

[0089] Ultimately, as Figure 3As shown, the Pareto solution front is obtained, which is the optimal set of design variables for the thickness of the outer panel of the car door, as well as the solutions for the pole impact intrusion displacement, thinning rate and total weight. In its front solution, the designer selects the optimal thickness dimension value, so that while ensuring stiffness, pole impact safety and good stamping formability, the structure is lightweight.

[0090] Another embodiment of the present invention provides a digital structure optimization system for automotive door outer panels, comprising:

[0091] The performance index digital extraction module is used to simulate and obtain the maximum sinking displacement, maximum intrusion displacement, maximum thinning rate, and maximum total weight of the outer door panel under each thickness within the preset door panel thickness range using simulation analysis software. It constructs digital arrays of thickness-rigidity, thickness-crash resistance, thickness-manufacturing process, and thickness-lightweight respectively.

[0092] The performance index function generation module is used to perform data fitting on the thickness-rigidity digital array, thickness-crash resistance digital array, thickness-manufacturing process digital array, and thickness-lightweight digital array to obtain the door outer panel sink displacement function, pole impact intrusion displacement function, door outer panel thinning rate function, and door outer panel total weight function, respectively.

[0093] The multi-objective optimization model construction and solution module is used to construct a multi-objective optimization model for the outer door panel, with the thickness of the outer door panel as the design variable, the downward displacement function of the outer door panel as the constraint condition, and the pole impact intrusion displacement function, the thinning rate function of the outer door panel, and the total weight function of the outer door panel as the objective functions. The optimization objectives are to minimize the pole impact intrusion displacement, the thinning rate of the outer door panel, and the total weight of the outer door panel. The optimal outer door panel thickness is obtained by using a second-generation genetic algorithm with an adaptive process to obtain the Pareto solution front.

[0094] In summary, the digital structural optimization design method and system for automotive door outer panels according to embodiments of the present invention have the following beneficial effects:

[0095] 1. The technical solution of the present invention takes into account both the structural performance and manufacturing process performance of the car door outer panel. It comprehensively considers four interdisciplinary performance issues that are related and mutually restrictive: excellent rigidity and strength performance, strong impact resistance, manufacturing process and lightweight performance of the car door outer panel.

[0096] 2. The technical solution of the present invention is highly feasible. In the process of developing car door assemblies, it can shorten the development cycle of interactive discussions among design, performance and process. At the same time, the technical solution of the present invention can be extended to other mechanical engineering structures, and has strong scalability and applicability.

[0097] 3. The technical solution of this invention ensures good manufacturability of the structure in the subsequent manufacturing process by using specific digital indicators as constraints during the design stage. At the same time, by incorporating structural weight factors into the performance factors, it balances and alleviates the conflicts and contradictions between structural usability, manufacturability and lightweight performance. Under the premise of taking into account the good rigidity and strength, excellent impact resistance and considerable manufacturability of the door outer panel, the weight of the door outer panel is reduced. This will indirectly provide a more effective implementation method for achieving the vehicle weight index and economic index in the development of the whole vehicle project.

[0098] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A digital structural optimization design method for automobile door outer panels, characterized in that, Includes the following steps: Construct four sets of digital arrays of door outer panel thickness and performance indicators within a preset door panel thickness range; wherein, the four sets of digital arrays of door outer panel thickness and performance indicators are: thickness-rigidity digital array, thickness-crash resistance digital array, thickness-manufacturing process digital array, and thickness-lightweight digital array; Four door outer panel performance index functions were obtained by fitting data to the four sets of digital arrays of door outer panel thickness and performance index. Using the thickness of the outer door panel as a variable, a multi-objective optimization model for the outer door panel is constructed based on four performance index functions of the outer door panel, and the optimal outer door panel thickness is obtained by solving the model.

2. The method according to claim 1, characterized in that, Construct four sets of digital arrays of door outer panel thickness and performance indicators within a preset door panel thickness range, including: The thickness of the outer door panel is divided into several values ​​within a preset range; Based on the thickness of each of the door outer panels after equalization, simulation analysis software is used to simulate and obtain the maximum sinking displacement, maximum intrusion displacement, maximum thinning rate, and maximum total weight of the door outer panel under each of the aforementioned door outer panel thicknesses. Based on the thickness of each of the aforementioned outer door panels and the corresponding maximum downward displacement, maximum intrusion displacement, maximum thinning rate, and maximum total weight of the outer door panels, thickness-rigidity digital arrays, thickness-crash resistance digital arrays, thickness-manufacturing process digital arrays, and thickness-lightweight digital arrays are constructed respectively.

3. The method according to claim 2, characterized in that, The four door outer panel performance index functions include the door outer panel sinking displacement function, the pillar impact intrusion displacement function, the door outer panel thinning rate function, and the door outer panel total weight function; the four door outer panel performance index functions are obtained by fitting data to the four sets of door outer panel thickness-performance index digitized arrays respectively, including: Based on the thickness and maximum sinking displacement of the outer door panel in the thickness-stiffness digitized array, the sinking displacement function of the outer door panel is obtained by fitting using the least squares method. Based on the thickness of the outer door panel and the maximum intrusion displacement in the thickness-crash resistance digitized array, the pole impact intrusion displacement function is obtained by fitting using the least squares method. Based on the thickness and maximum thinning rate of the outer door panel in the thickness-manufacturing process digit array, the thinning rate function of the outer door panel is obtained by fitting using the least squares method. Based on the thickness and maximum total weight of the door outer panel in the thickness-lightweight digitized array, the total weight function of the door outer panel is obtained by fitting using the least squares method.

4. The method according to claim 3, characterized in that, Using the downward displacement function of the outer door panel as a constraint, and the pole impact intrusion displacement function, the thinning rate function of the outer door panel, and the total weight function of the outer door panel as objective functions, a multi-objective optimization model for the outer door panel is constructed.

5. The method according to claim 4, characterized in that, The optimization objectives of the multi-objective optimization model for the outer door panel include: minimizing the pole impact intrusion displacement, minimizing the thinning rate of the outer door panel, and minimizing the total weight of the outer door panel, all under the constraint that the sinking displacement is less than the maximum sinking displacement under a predetermined vertical load.

6. The method according to claim 5, characterized in that, The multi-objective optimization model for the outer door panel uses an adaptive process second-generation genetic algorithm to obtain the Pareto solution front, and selects the optimal outer door panel thickness from the Pareto solution front as the final solution, including: The thickness of each of the equally divided outer door panels is used as the initial population and coded accordingly; Based on the objective functions of pole collision intrusion displacement, door outer panel thinning rate, and total weight of door outer panel, the dominance level and crowding distance of each coded entity are calculated, and the fitness value of each entity is obtained based on the dominance level and crowding distance of each entity. Based on the fitness values ​​of each individual, the Pareto solution front is obtained by performing selection, crossover, and mutation operations on each individual using an elite strategy.

7. The method according to claim 2, characterized in that, The maximum downward displacement and maximum total weight of the door outer panel corresponding to the thickness of each door outer panel were calculated using linear calculation and analysis software.

8. The method according to claim 2, characterized in that, The maximum intrusion displacement of the outer door panel corresponding to the thickness of each door panel was calculated using nonlinear large deformation dynamic analysis software.

9. The method according to claim 2, characterized in that, The maximum thinning rate of the outer door panel corresponding to the thickness of each door panel was calculated using stamping process analysis software.

10. A digital structure optimization system for automobile door outer panels, characterized in that, include: The performance index digital extraction module is used to simulate and obtain the maximum sinking displacement, maximum intrusion displacement, maximum thinning rate, and maximum total weight of the outer door panel under each thickness within the preset door panel thickness range using simulation analysis software. It constructs digital arrays of thickness-rigidity, thickness-crash resistance, thickness-manufacturing process, and thickness-lightweight respectively. The performance index function generation module is used to perform data fitting on the thickness-rigidity digital array, thickness-crash resistance digital array, thickness-manufacturing process digital array, and thickness-lightweight digital array to obtain the door outer panel sink displacement function, pole impact intrusion displacement function, door outer panel thinning rate function, and door outer panel total weight function, respectively. The multi-objective optimization model construction and solution module is used to construct a multi-objective optimization model for the outer door panel, with the thickness of the outer door panel as a variable, the downward displacement function of the outer door panel as a constraint, and the pole impact intrusion displacement function, the thinning rate function of the outer door panel, and the total weight function of the outer door panel as objective functions. The optimization objectives are to minimize the pole impact intrusion displacement, the thinning rate of the outer door panel, and the total weight of the outer door panel. The optimal outer door panel thickness is obtained by using a second-generation genetic algorithm with an adaptive process to obtain the Pareto solution front.

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