Optimization Method for Body Frame Structure Model

Abstract

The present invention discloses an optimization method for a body frame structure model. The main design concept of the present invention is to determine the true positions of body components through the peripheral frame, divide long grids and square grids, and then perform topology optimization through an iterative algorithm and control the dimensions, avoiding the rough positioning of designing structural components through a single grid in traditional topology, being able to solve the problem that the structural frame exists on one side of the topological space, and being able to accurately reflect the positions and characteristic dimensions of body components, that is, the topological frame finally provided by the present invention can reflect the structural cross-section performance, and the final model is consistent with the true body characteristics. Specifically, in the solution of the present invention, if a certain position is a non-important structure, the cross-section size is reduced, but the complete frame is still retained; moreover, the present invention retains the outer frame, that is, retains the necessary connections of the body structure, ensures that the overall structure is not distorted, and eliminates serious inconsistent phenomena such as structural interruption or intersection.

Description

Technical Field

[0001] The present invention relates to the field of automobile manufacturing, and particularly to a method for optimizing a body frame structure model. Background Art

[0002] In the design and development of electric vehicles, due to the continuous increase in the weight of the battery, the lightweight index of the body has become the most important index in body development and design.

[0003] In addition to applying lightweight materials such as aluminum and carbon fiber, how to design the body frame has also become the key to body lightweight design. In existing preliminary designs, generally, the force transmission path of the body frame is found through the topology of the entire body-in-white, and design is carried out based on this.

[0004] Traditional topology optimization: Build a topology frame model based on a benchmark vehicle. Adopt the variable density method, and by defining density variables, find the positions that have the greatest impact on performance such as stiffness and mode. For positions with little impact, delete the topology space. Finally, obtain the topology frame of the body, and determine the position of the structural beam based on this.

[0005] However, through analysis, the existing topology methods have the following drawbacks:

[0006] 1. The frame after topology may be interrupted or have various bends, which is seriously inconsistent with the straight beam structure of the actual design.

[0007] 2. The frame after topology may only exist at one edge position of the topology space, which is inconsistent with the characteristics of the body thin-walled beam.

[0008] 3. There is currently no good method for how to convert the topology frame into a thin-walled beam. It is only judged by the experience of engineers.

[0009] 4. The topology frame can only reflect the position of the thin-walled beam and cannot reflect its characteristic dimensions. Therefore, thin-walled beams of different sizes will also have a very large impact on performance, which is also one of the key problems why topology cannot be converted into an actual thin-walled beam structure. Summary of the Invention

[0010] In view of the above, the present invention aims to provide a method for optimizing a body frame structure model to solve the aforementioned technical problems.

[0011] The technical solution adopted by the present invention is as follows:

[0012] The present invention provides a method for optimizing a body frame structure model, which includes:

[0013] Build a spatial frame model according to the cross-sectional structural dimensions of the vehicle body components, including that the internal topology consists of several square grids, the peripheral topology is surrounded by several long grids, and the material parameters of the internal topology and the peripheral topology are respectively selected, and the overall cross-sectional dimensions are defined;

[0014] Find the main path representing the first force transmission point inside the spatial frame model, and obtain the surface corresponding to the main path through the iterative optimization algorithm to determine the unilateral surface;

[0015] Take the unilateral surface as known, analyze and calculate the second force transmission point, and determine the position of the opposite surface through the iterative optimization algorithm;

[0016] Take the obtained unilateral surface and the opposite surface as known quantities, and iteratively optimize the two surfaces beside the cross-section to obtain the target overall frame structure.

[0017] In at least one possible implementation manner, the material parameters are: select the corresponding elastic modulus and density based on the material thickness of the original vehicle body component cross-section.

[0018] In at least one possible implementation manner, when the range of the cross-sectional dimensions changes, add square grids row by row or column by column inside the spatial frame model.

[0019] In at least one possible implementation manner, the iterative optimization includes: performing initial analysis and optimization using the variable density method to obtain the main path under this cross-section.

[0020] In at least one possible implementation manner, if the obtained main path is a long grid after the previous round of optimization, perform topology optimization again using the variable density method, and take the long grid obtained from the previous round of topology optimization as a known parameter to optimize the remaining topological space to obtain other adjacent long grids;

[0021] When main paths appear on all four sides of the cross-section, determine the cross-sectional dimensions and mark the unprocessed long grids as optimized.

[0022] In at least one possible implementation manner, during each round of optimization, if long grids are optimized at other non-adjacent positions in the space, take them as known parameters in the next round of iterative optimization; if square grids are optimized in the space, shorten the size of the entire cross-sectional space by one column of grids and then perform iterative optimization calculation again until long grids appear in the main path again.

[0023] In at least one possible implementation manner, if long grids representing the main path still do not appear when the size of the cross-sectional space is shortened to the preset minimum size, mark the long grid on the side opposite to the obtained main path as the main path and perform the next round of iterative optimization.

[0024] In at least one possible implementation, if the obtained main path is a square grid after the previous round of optimization, the variable density method is used again for topology optimization. The square grid obtained from the first topology optimization is used as a known parameter to optimize the remaining topological space until a long grid appears in the optimization result;

[0025] And the optimized long grid is used as a known parameter, and the other optimized square grids are used as variables to perform an optimization cancellation operation.

[0026] In at least one possible implementation, the optimization cancellation operation includes:

[0027] If the object to be optimized and cancelled is a square grid adjacent to the long grid, then the entire row of this square grid is cancelled, the overall cross-sectional size is reduced, and the optimization cancellation is performed again;

[0028] If the object to be optimized and cancelled is not the long grid at the current position, the number of grids remains unchanged, all square grids are restored to topological variables, the long grid is used as a known parameter, and the remaining long grids are continuously optimized according to the long grid iterative optimization algorithm.

[0029] The main design concept of the present invention is to determine the true position of the body part structure through the surrounding frame, divide the long grid and the square grid, and then perform topology optimization and control the size through the iterative algorithm, avoiding the rough positioning of designing structural parts through a single grid in traditional topology, being able to solve the problem that the structural frame exists on one side of the topological space, and being able to accurately reflect the position and characteristic size of the body part, that is, the topological frame finally provided by the present invention can reflect the structural cross-sectional performance, and the final model is consistent with the true body characteristics. Specifically, in the solution of the present invention, if a certain position is a non-important structure, the cross-sectional size is reduced, but the complete frame is still retained; moreover, the present invention retains the outer frame, that is, retains the necessary connections of the body structure, ensures that the overall structure is not distorted, and eliminates serious inconsistent phenomena such as structural interruption or intersection. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] To make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described below in conjunction with the accompanying drawings, where:

[0031] Figure 1 It is a flowchart of the method for optimizing the body frame structure model provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] Embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are only used to explain the present invention and should not be construed as limiting the present invention.

[0033] An embodiment of a method for optimizing a body frame structure model is proposed by the present invention. Specifically, as Figure 1 shown, it includes:

[0034] Step S1: Build a spatial frame model according to the cross-sectional structure dimensions of the body components;

[0035] Step S2: Locate the main path representing the first force transmission point inside the spatial frame model, and obtain the surface corresponding to the main path through a divergence iteration algorithm to determine the unilateral surface;

[0036] Step S3: Take the unilateral surface as known, analyze and calculate the second force transmission point, and determine the position of the opposite surface through spatial iteration;

[0037] Step S4: Take the obtained unilateral surface and the opposite surface as known quantities, and iteratively optimize the two surfaces beside the cross-section to obtain the target overall frame structure.

[0038] The following is an example of size optimization of a thin-walled beam cross-section:

[0039] (1) First, divide the topological space frame according to the body of the benchmark vehicle.

[0040] In actual operation, the topological space should cover the entire thin-walled beam space. The size of each internal square grid is 20mm * 20mm. The size of the long grids around the perimeter is 8mm * 20mm.

[0041] Specifically, the material parameters of the internal topology are: elastic modulus 52500MPa, density 2000kg / m3; the material parameters of the peripheral topology are: elastic modulus 150000 - 165000MPa, density 6000 - 6500kg / m3. Specifically, different elastic moduli and densities are selected according to the steel thickness of the original cross-section. For example, 0.7mm steel corresponds to an elastic modulus of 150000 and a density of 6000, 2.2mm steel corresponds to an elastic modulus of 165000 and a density of 6500, and others are linearly distributed. For the material part outside the range of 0.7 - 2.2, it can be configured according to the preset upper and lower limits.

[0042] Next, define the cross-sectional dimensions, which can vary within an acceptable range. For the topological space changes caused by the variation of the cross-sectional dimensions, one row or one column of 20*20 square grids can be added inside the space to achieve this (the outer side is still wrapped with 8*20 long grids).

[0043] (2) Iterative optimization:

[0044] First, use the variable density method for initial analysis and optimization to obtain the most important path under this cross-section. At this time, there are two situations: the grids of the most important path are the peripheral long grids of 8*20, or the middle square grids of 20*20.

[0045] (2.1) Iterative algorithm for peripheral long grids:

[0046] After obtaining the first long grid, use the variable density method for topological optimization again. Take the long grid obtained from the first topological optimization as a known parameter to optimize the remaining topological space. It should be noted here that the middle square grids adjacent to this long grid do not participate in the performance analysis.

[0047] After optimization, adjacent long grids are successively optimized. At this time, main paths may also appear in other positions in the space. If they belong to long grids, they will also be used as known parameters in the next round of iterative analysis; if they belong to square grids, shorten the cross-sectional dimensions by one column of grids and then perform iterative calculations again until the main path appears in the long grid. Based on this, if the cross-sectional dimensions are shortened to the preset minimum and no long grid representing the main path appears, at this time, mark the long grid on the side directly opposite to the known main path as the main path and perform the next round of iterative analysis.

[0048] When main paths appear on all four sides of the cross-section, the cross-sectional dimensions are determined. At this time, mark all the remaining long grids as optimized.

[0049] (2.2) Iterative algorithm for middle square grids:

[0050] After obtaining the first square grid, use the variable density method for topological optimization again. Take the square grid obtained from the first topological optimization as a known parameter to optimize the remaining topological space. Repeat the iterative optimization until long grids appear in the optimization results.

[0051] Take the optimized long grid as a known parameter and the other optimized square grids as variables for the cancellation optimization operation: If the object to be optimized is a square grid adjacent to this long grid, cancel an entire row of this square grid, that is, the overall cross-sectional dimensions decrease in the up and down directions. At the same time, the bottom row of long grids moves up accordingly and the cancellation optimization is performed again.

[0052] If the object to be optimized is not the long grid at the current position, the number of grids is kept unchanged, all square grids are restored to topological variables, the long grid is used as a known parameter, and the long grid iterative optimization algorithm is used to continue to optimize the remaining long grids.

[0053] It can also be supplemented with respect to the above examples that the core of the above examples is: first draw a frame of maximum size, and then use the optimization algorithm to determine whether the frame size is appropriate. If the most sensitive point is not in the outermost circle, shrink it inward and iterate the calculation again to finally get a fixed size. The previous examples are divided according to the characteristics of thin-walled beams. When the beam structure is made of materials such as aluminum alloy, several rows or columns of long grids can be added to the internal square grid to reflect the cross-sectional performance of the aluminum alloy. In addition, if the grid size in the above examples is large, resulting in an inaccurate optimized structure, it can also be reduced proportionally. The minimum value is preferably a 2mm*5mm long grid and a 5mm*5mm square grid, but the length-to-width ratio must remain unchanged. Understandably, reducing the grid size will increase the calculation time and the number of iterations, but the results will be clearer and more accurate.

[0054] In summary, the main design concept of the present invention is to determine the actual position of the body component structure through the peripheral frame, and divide it into long grids and square grids, and then perform topological optimization and control the size through an iterative algorithm, thereby avoiding the rough positioning of structural components designed by a grid in traditional topology, and being able to solve the problem that the structural frame exists on one side of the topological space, and can accurately reflect the position and characteristic size of the body components, that is, the topological frame finally provided by the present invention can reflect the structural cross-sectional performance, and the final model is consistent with the real body characteristics. Specifically, in the scheme of the present invention, if a certain position is a non-important structure, the cross-sectional size is reduced, but the complete frame is still retained; moreover, the present invention retains the outer frame, that is, the necessary connection of the body frame is retained, ensuring that the overall structure is not distorted, and eliminating serious inconsistencies such as structural interruptions or intersections.

[0055] In the embodiments of the present invention, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. A and B may be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c may represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c may be single or multiple.

[0056] The structure, features and effects of the present invention have been described in detail based on the embodiments shown in the drawings above. However, the above are only the preferred embodiments of the present invention. It should be noted that for the technical features involved in the above embodiments and their preferred modes, those skilled in the art can reasonably combine and match them into a variety of equivalent solutions without departing from and without changing the design concept and technical effects of the present invention. Therefore, the scope of implementation of the present invention is not limited by the drawings shown. Any changes made in accordance with the concept of the present invention, or equivalent embodiments modified into equivalent changes, should still be within the protection scope of the present invention as long as they do not exceed the spirit covered by the description and the drawings.

Claims

1. A method for optimizing a body frame structure model, characterized in that, Including: Build a spatial frame model according to the cross-sectional structure dimensions of the vehicle body components, including that the internal topology consists of several square grids, the peripheral topology is surrounded by several long grids, and the material parameters of the internal topology and the peripheral topology are respectively selected, and the overall cross-sectional dimensions are defined; Find the main path representing the first force transmission point inside the spatial frame model, and obtain the surface corresponding to the main path through the iterative optimization algorithm to determine the unilateral surface; Take the unilateral surface as known, analyze and calculate the second force transmission point, and determine the position of the opposite surface through the iterative optimization algorithm; Take the obtained unilateral surface and the opposite surface as known quantities, and iteratively optimize the two surfaces beside the cross-section to obtain the target overall frame structure; Among them, the process of iterative optimization includes: using the variable density method for initial analysis and optimization to obtain the main path under this cross-section; If the main path obtained after the previous round of optimization is a long grid, then use the variable density method for topology optimization again, and use the long grid obtained from the previous round of topology optimization as a known parameter to optimize the remaining topological space to obtain other adjacent long grids; When the main paths appear on all four sides of the cross-section, determine the cross-sectional dimensions and mark the unprocessed long grids as optimized; In each round of optimization process, if long grids are optimized at other non-adjacent positions in the space, then in the next round of iterative optimization, use them as known parameters; if square grids are optimized in the space, then shorten the size of the entire cross-sectional space by one column of grids and perform iterative optimization calculation again until long grids appear in the main path again; If long grids representing the main path do not appear when the size of the cross-sectional space is shortened to the preset minimum size, then mark the long grid on the side opposite to the obtained main path as the main path and perform the next round of iterative optimization; If the main path obtained after the previous round of optimization is a square grid, then use the variable density method for topology optimization again, use the square grid obtained from the first topology optimization as a known parameter, and optimize the remaining topological space until long grids appear in the optimization result; And use the optimized long grid as a known parameter, use the other optimized square grids as variables, and perform the cancel optimization operation.

2. The method for optimizing the body frame structure model according to claim 1, wherein The material parameters are: select the corresponding elastic modulus and density based on the material thickness of the original vehicle body component cross-section.

3. The method for optimizing the body frame structure model according to claim 1, characterized in that When the range of the cross-sectional dimensions changes, add square grids row by row or column by column inside the spatial frame model.

4. The method for optimizing the body frame structure model according to claim 1, wherein The cancel optimization operation includes: If the object of optimization cancellation is the square grid adjacent to this long grid, then cancel the entire row of this square grid, reduce the overall cross-sectional size and perform the cancel optimization again; If the object of optimization cancellation is not the long grid at the current position, then keep the number of grids unchanged, restore all the square grids to topological variables, use this long grid as a known parameter, and continue to optimize the remaining long grids according to the long grid iterative optimization algorithm.

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