CN112131664B - Optimization and design method for automobile chassis parts - Google Patents
Optimization and design method for automobile chassis parts Download PDFInfo
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Abstract
The invention discloses an optimization and design method of automobile chassis parts, which comprises the following steps: firstly, carrying out parameterization modeling on chassis parts, and establishing a finite element model of the chassis parts; step two, carrying out forming analysis on the technological steps of the die forging process of the chassis part, and checking the performance of the chassis part; thirdly, topological optimization is carried out by taking the flexibility of the chassis under a specific working condition as an optimization target; step four, according to the topological optimization result, the shape of the removed material part is regulated, and the initial values and the variation ranges of the structural parameters and the forging technological parameters are respectively determined, wherein the maximum stress value is used as a response in the structural optimization, the equivalent strain value is used as a response in the technological optimization, and an optimization model of the structural parameters and the forging technological parameters is established; step five, optimizing the multi-objective shape; and step six, selecting a proper optimization algorithm to perform iterative computation. The invention comprehensively considers the structure and the technological parameters, and can obtain the optimization and design parameters of the automobile chassis part which takes the light design as the main aim.
Description
Technical Field
The invention relates to the field of computer-aided optimization design in the automobile industry, in particular to an optimization and design method of automobile chassis parts.
Background
In recent years, there have been many studies on the weight reduction of automobile bodies, but there have been few studies on the weight reduction of automobile chassis. The weight of the automobile chassis accounts for about 1/3 of the weight of the whole automobile, and the automobile chassis is light, so that energy conservation and emission reduction can be realized, and meanwhile, the operability and stability of the whole automobile can be improved. And the weight reduction of automobile chassis parts is an important way for realizing the weight reduction of the chassis.
However, due to the complicated structure of chassis parts such as steering knuckles, control arms, etc., the formation quality may be poor if structural optimization is performed alone without taking process parameters into consideration. The related researches at present are only developed on a certain aspect of the structure and the technological parameters, and the structure and the technological parameters are not combined, so that scientific optimization and design results cannot be obtained effectively.
Disclosure of Invention
The invention aims to provide an optimization and design method for an automobile chassis part which comprehensively considers structural and technological parameters and takes lightweight design as a main target, and the structural parameters and the technological parameters of the final chassis part are obtained by comprehensively considering the technological parameters and the structural parameters of a forging process.
The invention is realized in the following way:
an optimization and design method of an automobile chassis part comprises the following steps:
firstly, carrying out parameterization modeling on chassis parts, and establishing a finite element model of the chassis parts;
step two, carrying out forming analysis on the technological steps of the die forging process of the chassis part, and checking the performance of the chassis part;
thirdly, topological optimization is carried out by taking the flexibility of the chassis under a specific working condition as an optimization target;
step four, according to the topological optimization result, the shape of the removed material part is regulated, and the initial values and the variation ranges of the structural parameters and the forging technological parameters are respectively determined, wherein the maximum stress value is used as a response in the structural optimization, the equivalent strain value is used as a response in the technological optimization, and an optimization model of the structural parameters and the forging technological parameters is established;
step five, determining the weight of the target based on a gray correlation method to perform multi-target shape optimization;
and step six, selecting a proper optimization algorithm to perform iterative computation.
The further scheme is as follows:
in the first step, design variables of the chassis part are determined according to performance indexes of the chassis part, wherein the performance indexes comprise process performance indexes and structural performance indexes of the chassis part, the process performance indexes comprise equivalent strain values, temperatures and metal flow values of all working procedures, and the structural performance indexes comprise stress and strain values and modal and fatigue durability values of the steering knuckle under all working conditions.
The further scheme is as follows:
the process steps of the die forging process in the second step comprise four process steps of upsetting, bending, pre-forging and final forging; and checking the performance of the chassis part comprises checking the rigidity and strength performance of the chassis part.
The further scheme is as follows:
and step two, carrying out finite element forming analysis through the finite element model of the chassis part established in the step one, and checking the performance of the chassis part under a static load working condition, wherein the static load working condition comprises a maximum vertical force working condition, a 0.4g steering working condition and a 0.6g braking working condition.
The further scheme is as follows:
in the third step, the topological optimization takes rigidity under three working conditions as an optimization target by carrying out compromise treatment, and an optimization model is as follows
Where C (x) is a flexibility function with density as a design variable, ω i The weight under three working conditions is 0.4,0.3 and C i (x) Is the flexibility value when the iteration number is i, V (x) is the volume of the nth iteration, V 0 Representing the initial volume x i Representing the relative density of cells for the ith iteration.
The further scheme is as follows:
in the result optimization process in the third step, key parameters of the chassis part are selected as design variables, the key parameters are subjected to factor screening to obtain fewer design variables, the design variables change within a range of +/-10%, multiple simulation analysis is carried out according to the established sample points, and an optimization model is established by taking the maximum stress value of the chassis part under dangerous working conditions as an optimization target, wherein the optimization model is as follows:
S max (x i ) Representing the relative density of the units x at the ith iteration i Maximum stress value at Min representsThe maximum stress value is minimized. V (V) opt Representing the volume after optimization iteration, V 0 Representing the initial volume.
And the process parameter optimization model takes forging temperature and friction coefficient as design variables and equivalent strain value as an optimization target, and performs multiple simulation analysis to establish a final approximate model for optimization.
The further scheme is as follows:
and step four, integrating a plurality of independent optimization targets in the process and the structure, and then determining the weight coefficient of each optimization target by using a gray correlation method and then carrying out weighted calculation to obtain an integrated target function.
And selecting a proper optimization algorithm to perform iterative calculation after the comprehensive objective function is obtained, so as to obtain a final chassis part structure. The invention comprehensively considers the structure and the technological parameters, and can obtain the optimization and design parameters of the automobile chassis part which takes the light design as the main aim.
Drawings
FIG. 1 is a block flow diagram of the method of the present invention.
Fig. 2 is a schematic diagram of an original model of a steering knuckle.
FIG. 3 is a schematic diagram of a model of a knuckle topology after optimization.
Detailed Description
The invention will be further described with reference to the drawings and the specific examples.
The chassis part of the automobile for which the present embodiment is directed is a knuckle. As shown in fig. 1, the optimization and design method of the automobile aluminum alloy steering knuckle provided by the invention comprises the following steps:
step one, an initial structure of the knuckle is shown in fig. 2, a finite element model of the knuckle is established, simulation analysis is carried out from two aspects of structure and process, and in the aspect of structure, in order to realize strength check of the knuckle, three aspects of static strength, modal analysis and fatigue performance are developed, wherein three typical working conditions are mainly considered for the static strength: steering condition, maximum vertical force condition and emergency braking of 0.6 g. The modal analysis is mainly free modal analysis, and the front ten-order frequency and the vibration mode of the steering knuckle are extracted. The fatigue strength is based on the above two, and the knuckle fatigue life value of the B-stage road surface is predicted in consideration of the material characteristics. In the strength checking results, the maximum stress value of the knuckle under the three working conditions is the steering working condition, the maximum stress value is 181Mpa, the yield strength of the knuckle is less than 300Mpa, the lowest frequency is far less than the resonance frequency, and the fatigue life value is greater than a specified value. Therefore, the steering knuckle has a certain optimization space, and can be further optimally designed.
And step two, performing forming analysis on the knuckle die forging process including upsetting, bending, pre-forging and final forging, and after setting simulation parameters, simulating the forging process and obtaining the results of metal flow, temperature, stress, strain and the like representing the quality index after forging. In the pre-forging process, the metal deformation is large, the die shape is complex, the influence on the final forming quality is large, and the stress strain and the like of the process can be selected as the optimization targets.
Step three, topological optimization is carried out by taking the knuckle flexibility minimization as an optimization target, the result of topological optimization carried out under three working conditions independently is not completely consistent due to the existence of multiple working conditions by utilizing a variable density optimization method, and therefore, the weighted result of the rigidity values under the three working conditions is taken as the optimization target during optimization by utilizing a weighted method, and an optimization model is as follows:
where C (x) is a flexibility function with density as a design variable, ω i The weight is 0.4/0.4/0.3 under three working conditions, and C is the weight of 0.4/0.4/0.3 i (x) Is the flexibility value when the iteration number is i, and V (x) is the volume V (x) of the nth iteration and the initial volume V 0 And (3) a difference.
Aiming at the topology optimization problem, the maximum rigidity is taken as an optimization target. Under the condition of no forced displacement and forced acceleration, the rigidity is inversely proportional to the flexibility, so that the flexibility can be minimized as an optimization target to facilitate calculation. Furthermore, the volume fraction is often set as a constraint because of its insensitivity to design. The volume fraction is selected to be 0.45, and the steering knuckle obtained at the moment has a reasonable structure.
Meanwhile, under the three working conditions determined in the foregoing, comprehensively considering the optimization result and the importance degree of each working condition, and taking the weight w under the three working conditions of 0.4g steering, maximum vertical force and 0.6g emergency braking i The size is 0.4,0.3,0.3, topology optimization calculation is carried out in ANSYS by using a criterion method, and an optimization result is obtained after a plurality of iterations.
And step four, respectively determining initial values and variation ranges of the structural parameters and the forging process parameters according to topology optimization results, wherein the maximum stress value is used as a response in the structural optimization, and the equivalent strain value is used as a response in the process optimization, so as to establish an optimization model of the structural parameters and the forging process parameters. 11 parameters at the long arm of the knuckle are selected as design variables in the structure optimization process. The shape change is controlled by controlling the radius of the arc at the long arm. And (3) obtaining 3 design variables after factor screening, wherein the design variables change within the range of +/-10%, performing multiple simulation analysis according to the established sample points, and establishing an optimization model by taking the maximum stress value of the steering knuckle under the steering working condition as an optimization target. The optimization model is as follows:
and the process parameter optimization model takes forging temperature and friction coefficient as design variables and equivalent strain value as an optimization target, and performs multiple simulation analysis to establish a final approximate model for optimization.
Step five, determining the weight of the target based on a gray correlation method to perform multi-target shape optimization, wherein in the multi-target problem, the numerical value of the sub-target in any state is used as a sequence, and when one sub-target is optimized, the other sub-targets in the sequence are used as the other sub-targets in the sequenceThe sub-target may increase or decrease. During optimization, the equivalent strain value and the maximum stress value in the die forging process are used as single optimization targets, and the subsequence generated during optimization of each sub-target is obtained through single target optimization and is used as an associated sequence X i Forming optimal values of all sub-targets into an optimal sequence as an associated sequence X j And carrying out gray comprehensive association analysis on the association sequence and the associated sequence to obtain comprehensive association degree so as to obtain the weight coefficient of each single target, thereby obtaining the final optimization target according to a weighting method.
And step six, selecting a proper optimization algorithm to perform iterative computation so as to obtain the optimal knuckle structure parameters and process parameters.
The final model of the steering knuckle after topological optimization is shown in fig. 3.
In order to verify that the strength of the sub-frame after optimization meets the use requirement, the knuckle before and after optimization is subjected to equivalent static finite element analysis to obtain the knuckle equivalent stress comparison condition before and after optimization as shown in the table
| Working conditions of | Steering of 0.4g | Maximum vertical force | Emergency braking |
| Maximum value of equivalent stress before optimization | 181MPa | 167MPa | 108MPa |
| Maximum value of equivalent stress after topological optimization | 185MPa | 167MPa | 108MPa |
| Maximum value of equivalent stress after shape optimization | 171MPa | 163MPa | 106MPa |
Before optimization, the mass of the aluminum alloy auxiliary frame is 6.792kg, after optimization, the mass is 6.312kg, and the optimization mass is 0.48kg.
Although the invention has been described herein with reference to the above-described illustrative embodiments thereof, the above-described embodiments are merely preferred embodiments of the present invention, and the embodiments of the present invention are not limited by the above-described embodiments, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the scope and spirit of the principles of this disclosure.
Claims (6)
1. The optimization and design method of the automobile chassis part is characterized by comprising the following steps:
firstly, carrying out parameterization modeling on chassis parts, and establishing a finite element model of the chassis parts;
step two, carrying out forming analysis on the technological steps of the die forging process of the chassis part, and checking the performance of the chassis part;
thirdly, topological optimization is carried out by taking the flexibility of the chassis under a specific working condition as an optimization target;
step four, according to the topological optimization result, the shape of the removed material part is regulated, and the initial values and the variation ranges of the structural parameters and the forging technological parameters are respectively determined, wherein the maximum stress value is used as a response in the structural optimization, the equivalent strain value is used as a response in the technological optimization, and an optimization model of the structural parameters and the forging technological parameters is established;
step five, determining the weight of the target based on a gray correlation method to perform multi-target shape optimization;
step six, selecting a proper optimization algorithm to perform iterative computation;
in the third step, the topological optimization takes rigidity under three working conditions as an optimization target by carrying out compromise treatment, and an optimization model is as follows
Where C (x) is a flexibility function with density as a design variable, ω i The weight under three working conditions is 0.4,0.3 and C i (x) Is the flexibility value when the iteration number is i, and V (x) is the volume V of the nth iteration 0 Representing the initial volume x i Representing the relative density of cells for the ith iteration.
2. The method for optimizing and designing an automotive chassis part according to claim 1, characterized in that:
in the first step, design variables of the chassis part are determined according to performance indexes of the chassis part, wherein the performance indexes comprise process performance indexes and structural performance indexes of the chassis part, the process performance indexes comprise equivalent strain values, temperatures and metal flow values of all working procedures, and the structural performance indexes comprise stress and strain values and modal and fatigue durability values of the steering knuckle under all working conditions.
3. The method for optimizing and designing an automobile chassis part according to claim 2, wherein:
the process steps of the die forging process in the second step comprise four process steps of upsetting, bending, pre-forging and final forging; and checking the performance of the chassis part comprises checking the rigidity and strength performance of the chassis part.
4. A method of optimizing and designing an automotive chassis part according to claim 3, characterized in that:
and step two, carrying out finite element forming analysis through the finite element model of the chassis part established in the step one, and checking the performance of the chassis part under a static load working condition, wherein the static load working condition comprises a maximum vertical force working condition, a 0.4g steering working condition and a 0.6g braking working condition.
5. The method for optimizing and designing an automotive chassis part according to claim 4, wherein:
in the result optimization process in the third step, key parameters of the chassis part are selected as design variables, the key parameters are subjected to factor screening to obtain fewer design variables, the design variables change within a range of +/-10%, multiple simulation analysis is carried out according to the established sample points, and an optimization model is established by taking the maximum stress value of the chassis part under dangerous working conditions as an optimization target, wherein the optimization model is as follows:
S max (x i ) Representing the relative density of the units x at the ith iteration i Maximum stress value at the time Min represents a value to minimize the maximum stress value, V opt Representing the volume after optimization iteration, V 0 Representing an initial volume, n representing the number of iterations;
and the process parameter optimization model takes forging temperature and friction coefficient as design variables and equivalent strain value as an optimization target, and performs multiple simulation analysis to establish a final approximate model for optimization.
6. The method for optimizing and designing an automotive chassis part according to claim 5, characterized in that:
and step four, integrating a plurality of independent optimization targets in the process and the structure, and then determining the weight coefficient of each optimization target by using a gray correlation method and then carrying out weighted calculation to obtain an integrated target function.
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Patent Citations (7)
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| CN102945307A (en) * | 2012-11-27 | 2013-02-27 | 北京汽车股份有限公司 | Automobile chassis key structural member structure optimization design method |
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