CN112131664A - Optimization and design method of automobile chassis part - Google Patents
Optimization and design method of automobile chassis part 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 parametric modeling on a chassis part, and establishing a finite element model of the chassis part; step two, performing forming analysis on the technological steps of the die forging process of the chassis part, and checking the performance of the chassis part; thirdly, performing topology optimization by using the flexibility minimization of the chassis under a specific working condition as an optimization target; fourthly, according to a 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 process 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 process optimization, and optimization models of the structural parameters and the forging process parameters are established; fifthly, performing multi-target shape optimization; and step six, selecting a proper optimization algorithm to perform iterative calculation. The invention comprehensively considers the structure and the process parameters, and can obtain the optimization and design parameters of the automobile chassis parts which take lightweight design as the main target.
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, many studies have been made on the weight reduction of automobile bodies, and few studies have been made 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 light weight of the automobile chassis not only can save energy and reduce emission, but also can increase the maneuverability and the stability of the whole automobile. The light weight of the automobile chassis parts is an important way for realizing the light weight of the chassis.
However, due to the complicated structure of chassis parts such as steering knuckle and control arm, the molding quality may be poor if the structure is optimized independently without taking process parameters into consideration. However, the current related research is only carried out on one aspect of the structure and the process parameters, and the structure and the process parameters are not combined, so that scientific optimization and design results cannot be effectively obtained.
Disclosure of Invention
The invention aims to provide an optimization and design method of an automobile chassis part, which takes a structure and technological parameters into comprehensive consideration and aims at light weight design.
The invention is realized by the following steps:
a method for optimizing and designing automobile chassis parts comprises the following steps:
firstly, carrying out parametric modeling on a chassis part, and establishing a finite element model of the chassis part;
step two, performing forming analysis on the technological steps of the die forging process of the chassis part, and checking the performance of the chassis part;
thirdly, performing topology optimization by using the flexibility minimization of the chassis under a specific working condition as an optimization target;
fourthly, according to a 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 process 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 process optimization, and optimization models of the structural parameters and the forging process parameters are established;
determining the weight of the target based on a grey correlation method to perform multi-target shape optimization;
and step six, selecting a proper optimization algorithm to perform iterative calculation.
The further scheme is as follows:
in the first step, the design variables of the chassis parts are determined according to performance indexes of the chassis parts, the performance indexes comprise process performance indexes and structural performance indexes of the chassis parts, the process performance indexes comprise equivalent strain values, temperatures and metal flow values of all working procedures, and the structural performance indexes comprise stress values, strain values, modal values 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 step two comprise four process steps of upsetting, bending, pre-forging and finish forging; and checking the performance of the chassis part, including 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 the static load working condition, wherein the static load working condition comprises the maximum vertical force working condition, the 0.4g steering working condition and the 0.6g braking working condition.
The further scheme is as follows:
in the third step, the topological optimization takes the compromise treatment of the rigidity under three working conditions as the optimization target, and the optimization model is
Where C (x) is a compliance function with density as a design variable, ωiThe weights under three working conditions are sequentially 0.4, 0.3 and Ci(x) Is the softness value at iteration number i, V (x) is the volume of the nth iteration, V0Denotes the initial volume, xiRepresenting the relative density of cells for the ith iteration.
The further scheme is as follows:
selecting key parameters of the chassis part as design variables in the result optimization process in the third step, performing factor screening on the key parameters to obtain fewer design variables, wherein the design variables are changed within a range of +/-10%, performing multiple times of simulation analysis according to the established sample points, and establishing an optimization model 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:
Smax(xi) Represents that the relative density of the unit is x at the ith iterationiThe maximum stress value of time, Min indicates that the maximum stress value is to be minimized. VoptRepresenting the volume after optimization iteration, V0The initial volume is indicated.
And the technological parameter optimization model takes the forging temperature and the friction coefficient as design variables and the equivalent strain value as an optimization target, and carries out multiple times of simulation analysis to establish a final approximate model and then carries out optimization.
The further scheme is as follows:
and step four, integrating a plurality of independent optimization targets in the process and the structure, determining the weight coefficient of each optimization target by using a grey correlation method in step five, and then performing weighted calculation to obtain an integrated target function.
And after the comprehensive objective function is obtained, selecting a proper optimization algorithm for iterative calculation, thereby obtaining the final chassis part structure. The invention comprehensively considers the structure and the process parameters, and can obtain the optimization and design parameters of the automobile chassis parts which take lightweight design as the main target.
Drawings
FIG. 1 is a block diagram of the process flow of the present invention.
Fig. 2 is a schematic view of an original model of a knuckle.
FIG. 3 is a schematic diagram of a model after the knuckle topology optimization.
Detailed Description
The invention is further described with reference to the following figures and specific embodiments.
The present embodiment is directed to an automotive chassis part that is a knuckle. As shown in the attached figure 1, the optimization and design method of the automobile aluminum alloy steering knuckle provided by the invention comprises the following steps:
step one, establishing a finite element model of the steering knuckle as shown in fig. 2, performing simulation analysis from two aspects of structure and process, and developing from three aspects of static strength, modal analysis and fatigue performance in order to realize strength check of the steering knuckle in the aspect of structure, wherein the static strength mainly considers three typical working conditions: 0.6g steering working condition, maximum vertical force working condition and emergency braking. 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 predicted from the above both in consideration of the material characteristics, and the knuckle fatigue life value of the B-class road surface is predicted. In the strength checking results, the maximum stress value of the steering knuckle under three working conditions is the steering working condition, the maximum stress value is 181Mpa and is smaller than the yield strength of a 6082 aluminum alloy material used for the steering knuckle by 300Mpa, and the modal analysis result shows that the lowest frequency is far smaller than the resonance frequency and the fatigue life value is larger than a specified value. Therefore, the steering knuckle has a certain optimization space, and further optimization design can be carried out.
And step two, performing forming analysis on the knuckle die forging process including four steps of upsetting, bending, pre-forging and final forging, simulating a forging process after setting simulation parameters, and obtaining results of metal flow, temperature, stress, strain and the like representing quality indexes after forging. In the pre-forging process, because the metal deformation is large and the shape of the die is complex, the influence on the final forming quality is large, and therefore the stress strain of the process can be selected as an optimization target in the subsequent process.
And step three, carrying out topology optimization by using the flexibility minimization of the steering knuckle as an optimization target, wherein the results of the independent topology optimization under the three working conditions are not completely consistent due to the existence of multiple working conditions by using a variable density optimization method, so that the weighted results of the stiffness values under the three working conditions are used as the optimization target during optimization by using a weighting method, and the optimization model is as follows:
where C (x) is a compliance function with density as a design variable, ωiThe weight under three working conditions is 0.4/0.4/0.3, Ci(x) Is the softness value when the number of iterations is i, and V (x) is the volume V (x) and the initial volume V of the nth iteration0The difference between them.
Aiming at the topology optimization problem, the maximum rigidity is taken as an optimization target. The rigidity and the flexibility are in inverse proportion under the conditions of no forced displacement and forced acceleration, so the flexibility can be minimized as an optimization target to facilitate calculation. Furthermore, volume fraction is often set as a constraint due to its insensitivity to design. The volume fraction is selected to be 0.45, and the obtained steering knuckle is reasonable in structure.
Meanwhile, according to the three working conditions determined in the foregoing, the optimization result and the importance degree of each working condition are comprehensively considered, and the weight w under the three working conditions of 0.4g of steering, the maximum vertical force and 0.6g of emergency braking is takeniThe sizes are 0.4, 0.3 and 0.3, topology optimization calculation is carried out in ANSYS by using a criterion method, and an optimization result is obtained through iteration for a plurality of times.
And step four, respectively determining initial values and variation ranges of the structural parameters and the forging process parameters according to the topological optimization result, 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 process optimization, and an optimization model of the structural parameters and the forging process parameters is established. In the structure optimization process, 11 parameters at the long arm of the steering knuckle are selected as design variables. The shape change of the long arm is controlled by controlling the radius of the circular arc at the long arm. And (3) obtaining 3 design variables after factor screening, carrying out simulation analysis for a plurality of times according to the established sample points after the design variables are changed within the range of +/-10%, and establishing an optimization model by taking the maximum stress value of the steering knuckle under the steering condition as an optimization target. The optimization model is as follows:
and the technological parameter optimization model takes the forging temperature and the friction coefficient as design variables and the equivalent strain value as an optimization target, and carries out multiple times of simulation analysis to establish a final approximate model and then carries out optimization.
And fifthly, determining the weight of the target based on a grey correlation method to perform multi-target shape optimization, wherein in the multi-target problem, the numerical values of the sub-targets in any state are taken as a sequence, and when a certain sub-target is optimized, other sub-targets in the sequence can be increased or decreased. During optimization, the equivalent strain value and the maximum stress value in the die forging process are used as a single optimization target, and firstly, a subsequence generated during optimization of each sub-target is obtained through single target optimization and is used as an associated sequence XiForming an optimal sequence by the optimal values of the sub-targets as an associated sequence XjAnd performing grey comprehensive correlation analysis on the correlation sequence and the correlated sequence to obtain comprehensive correlation 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 calculation so as to obtain the optimal steering knuckle structural parameters and process parameters.
The model after final topological optimization of the knuckle is shown in fig. 3.
In order to verify that the strength of the optimized rear auxiliary frame meets the use requirements, equivalent static finite element analysis is carried out on the steering knuckle before and after optimization, and the comparison condition of the equivalent stress of the steering knuckle before and after optimization is obtained and shown in the table
| Working conditions | 0.4g turn | Maximum vertical force | Emergency brake |
| 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 aluminum alloy auxiliary frame has the mass of 6.792kg, after optimization, the mass is 6.312kg, and the optimized mass is 0.48 kg.
Although the present invention has been described herein with reference to the illustrated embodiments thereof, which are intended to be preferred embodiments of the present invention, it is to be understood that the invention is not limited thereto, and that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure.
Claims (7)
1. A method for optimizing and designing automobile chassis parts is characterized by comprising the following steps:
firstly, carrying out parametric modeling on a chassis part, and establishing a finite element model of the chassis part;
step two, performing forming analysis on the technological steps of the die forging process of the chassis part, and checking the performance of the chassis part;
thirdly, performing topology optimization by using the flexibility minimization of the chassis under a specific working condition as an optimization target;
fourthly, according to a 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 process 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 process optimization, and optimization models of the structural parameters and the forging process parameters are established;
determining the weight of the target based on a grey correlation method to perform multi-target shape optimization;
and step six, selecting a proper optimization algorithm to perform iterative calculation.
2. The method for optimizing and designing an automobile chassis part according to claim 1, wherein:
in the first step, the design variables of the chassis parts are determined according to performance indexes of the chassis parts, the performance indexes comprise process performance indexes and structural performance indexes of the chassis parts, the process performance indexes comprise equivalent strain values, temperatures and metal flow values of all working procedures, and the structural performance indexes comprise stress values, strain values, modal values 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 step two comprise four process steps of upsetting, bending, pre-forging and finish forging; and checking the performance of the chassis part, including checking the rigidity and strength performance of the chassis part.
4. A method for optimizing and designing an automobile chassis part according to claim 3, wherein:
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 the static load working condition, wherein the static load working condition comprises the maximum vertical force working condition, the 0.4g steering working condition and the 0.6g braking working condition.
5. The method for optimizing and designing an automobile chassis part according to claim 4, wherein:
in the third step, the topological optimization takes the compromise treatment of the rigidity under three working conditions as the optimization target, and the optimization model is
Where C (x) is a compliance function with density as a design variable, ωiThe weights under three working conditions are sequentially 0.4, 0.3 and Ci(x) Is the softness value at iteration number i, and V (x) is the volume V of the nth iteration0Denotes the initial volume, xiRepresenting the relative density of cells for the ith iteration.
6. The method for optimizing and designing an automobile chassis part according to claim 5, wherein:
selecting key parameters of the chassis part as design variables in the result optimization process in the third step, performing factor screening on the key parameters to obtain fewer design variables, wherein the design variables are changed within a range of +/-10%, performing multiple times of simulation analysis according to the established sample points, and establishing an optimization model 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:
and the technological parameter optimization model takes the forging temperature and the friction coefficient as design variables and the equivalent strain value as an optimization target, and carries out multiple times of simulation analysis to establish a final approximate model and then carries out optimization.
7. The method for optimizing and designing an automobile chassis part according to claim 6, wherein:
and step four, integrating a plurality of independent optimization targets in the process and the structure, determining the weight coefficient of each optimization target by using a grey correlation method in step five, and then performing weighted calculation to obtain an integrated target function.
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| CN105478679A (en) * | 2015-12-15 | 2016-04-13 | 南通明诺机械有限公司 | Manufacturing method of lightweight automobile chassis parts based on rigidity and deformation analysis |
| CN107145663A (en) * | 2017-05-04 | 2017-09-08 | 吉林大学 | Wheel multi-objective optimization design of power method |
| CN108856418A (en) * | 2018-05-29 | 2018-11-23 | 南京六和普什机械有限公司 | A kind of Robust Optimization method of auto parts aluminium sheet Sheet Metal Forming Technology |
| CN110990944A (en) * | 2019-11-15 | 2020-04-10 | 武汉理工大学 | Frame multi-target topology optimization method based on weight ratio calculation |
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- 2020-09-22 CN CN202011004560.6A patent/CN112131664B/en active Active
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 |
| CN103612688A (en) * | 2013-11-28 | 2014-03-05 | 宁波跃进汽车前桥有限公司 | Automobile chassis part weight reduction method based on multi-body dynamics and topological optimization technology |
| CN104765912A (en) * | 2015-03-25 | 2015-07-08 | 湖南大学 | Robustness optimizing method of aluminum plate punching process |
| CN105478679A (en) * | 2015-12-15 | 2016-04-13 | 南通明诺机械有限公司 | Manufacturing method of lightweight automobile chassis parts based on rigidity and deformation analysis |
| CN107145663A (en) * | 2017-05-04 | 2017-09-08 | 吉林大学 | Wheel multi-objective optimization design of power method |
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