CN110348088A - Lightweight body structure Multipurpose Optimal Method based on agent model - Google Patents
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Abstract
The present invention discloses a kind of lightweight body structure Multipurpose Optimal Method based on agent model, comprising the following steps: (10) finite element model is established: establishing white body finite element model；(20) model validation: static test is carried out to white body, verifies the validity of finite element model；(30) multi-objective optimization design of power model samples: establishing multi-objective optimization design of power mathematical model, samples；(40) objective function agent model efficiency evaluation: constructing the agent model of objective function, carries out efficiency evaluation；(50) model optimization solves: being optimized using agent model of the multi-objective genetic algorithm to objective function, obtains multiple Pareto solutions；(60) robustness evaluation: the robustness of evaluation Pareto solution；(70) prioritization scheme exports: output prioritization scheme.Lightweight body structure Multipurpose Optimal Method of the invention, is capable of the structure optimization scheme of output integrated better performances.
Description
Technical field
The present invention relates to vehicle structure design optimizing field, especially a kind of lightweight vehicle body based on agent model
Structure Multipurpose Optimal Method.
Background technique
With the fast development of domestic automobile industry, the popularity rate of automobile is higher and higher, and the product of major Automobile Enterprises is opened
Hair ability also achieves huge advance.Currently, how to shorten the development cycle of new model, development cost is reduced, improves exploitation matter
Amount is the project that each Automobile Enterprises need to solve.Automotive light weight technology design have become current automobile industry developing direction it
One, and body structure light-weight design must assure that mode, rigidity, intensity and fatigue, NVH and the crashworthiness of body structure
The punch forming performance of energy and part does not deteriorate.For multi-objective optimization question as body structure light-weight design, pass
The method for by multiple target converting single-object problem by weighted array, goal programming, efficiency coefficient etc. to handle of system
It is required that there is very strong priori knowledge.This method not only has a higher requirement to the working experience of designer, but also due to
This processing method is larger by artificial subjective impact, therefore has very big floating in precision.In conclusion existing method is not
Body structure light-weight design problem can be efficiently solved.
After searching and discovering the prior art, Chinese patent literature CN102938004A, publication date are 2013 years 02
The moon 20, a kind of body in white light weight optimal design method is disclosed, comprising steps of establishing discretization material parameter；It chooses white
Bodywork parts carry out loss of weight；Whether part meets performance requirement after judging loss of weight, chooses qualified part and becomes as design
Amount；Free Modal Analysis is carried out to the white body before loss of weight, acquires its basic frequency, single order torsional frequency and first-order flexure frequency
Rate；Using basic frequency, single order torsional frequency and first-order flexure frequency as the constraint condition of design variable, with quality most gently for mesh
Scalar functions optimize each part, obtain new white body.
But this method, only using quality as objective function, there is no consider rigidity and collision safety performance.And in body of a motor car
In structure design, rigidity and collision safety performance are two mostly important factors.Therefore its design method is unsatisfactory for multiple
Optimal case is found on the basis of target.
In short, problem of the existing technology is: when lightweight Body Optimal Design, only considering under multiple constraint conditions
Single target is optimized.This can not meet the common need in body-in-white structure optimization design to multiple performance objectives
It asks, therefore the comprehensive performance of optimizing design scheme hardly results in guarantee.
Summary of the invention
The lightweight body structure Multipurpose Optimal Method based on agent model that the purpose of the present invention is to provide a kind of, makes
It can meet the response under multiple constraint conditions to multiple objective functions, final energy in body-in-white structure design process
The structure optimization scheme of enough output integrated better performances.
Realize the technical solution of the object of the invention are as follows:
A kind of lightweight body structure Multipurpose Optimal Method based on agent model, comprising the following steps:
(10) finite element model is established: establishing white body finite element model, including static analysis according to the CAD data of vehicle body
Finite element model, complete automobile collision finite element model；
(20) model validation: static analysis test is carried out to white body and complete automobile collision is tested, by test result
It is compared with white body FEM Numerical Simulation, verifies the validity of finite element model；
(30) multi-objective optimization design of power model samples: establishing multi-objective optimization design of power according to body-in-white structure and mechanical characteristic
Mathematical model, and sampled in design domain using uniform Latin square test design method；
(40) objective function agent model efficiency evaluation: constructing the agent model of objective function according to test result, and
Its validity is evaluated using residual sum of squares (RSS)；
(50) model optimization solves: it is optimized using agent model of the multi-objective genetic algorithm to objective function,
Obtain multiple Pareto solutions；
(60) robustness evaluation: the Pareto robustness solved is evaluated using Monte Carlo simulation technology；
(70) prioritization scheme exports: output meets the prioritization scheme of technique requirement.
Compared with prior art, remarkable advantage of the invention are as follows:
Bending property of the lightweight body structure under twisting conditions, collision are constructed by way of establishing agent model
The mathematical model between performance indicator and critical component quality and design parameter under operating condition, has fully considered between design parameter
Coupled relation and performance indicator between associate feature, using with elite retention strategy quick non-dominant multiple target it is excellent
Change algorithm (NSGA-II), realizes the response under multiple constraint conditions to multiple objective functions, it finally being capable of output integrated
It can preferable lightweight body-in-white structure prioritization scheme.
Detailed description of the invention
Fig. 1 is that the present invention is based on the main flow charts of the lightweight body structure Multipurpose Optimal Method of agent model.
Fig. 2 is the flow chart of finite element model establishment step in Fig. 1.
Fig. 3 is white body finite element model figure in embodiment.
Fig. 4 is the flow chart of multi-objective optimization design of power model sampling step in Fig. 1.
Fig. 5 is design variable distribution map in embodiment
Specific embodiment
As shown in Figure 1, the present invention is based on the lightweight body structure Multipurpose Optimal Method of agent model, including following step
It is rapid:
(10) finite element model is established: establishing white body finite element model, including static analysis according to the CAD data of vehicle body
Finite element model, complete automobile collision finite element model；
As shown in Fig. 2, (10) the finite element model establishment step includes:
(11) white body finite element model is established: establishing white body finite element model using HyperMesh software pre-treatment；
(12) vehicle body entity solder joint is simulated: using Cweld unit simulation vehicle body entity solder joint；
(13) FEM meshing grid dividing: is carried out using triangle and quadrilateral mesh unit；
In (13) the grid dividing step, mesh quality standard includes:
Length-width ratio<3, angularity<10, Jacobi>0.6,45 °<quadrangle Minimum Internal Angle<130 °, 20 °<triangle are minimum
Interior angle < 100 °.
(14) finite element model is established: by adding different boundary conditions, establishing static analysis finite element model respectively
With complete automobile collision finite element model.
(20) model validation: static analysis test is carried out to white body and complete automobile collision is tested, by test result
It is compared with white body FEM Numerical Simulation, verifies the validity of finite element model；
(30) multi-objective optimization design of power model samples: establishing multi-objective optimization design of power according to body-in-white structure and mechanical characteristic
Mathematical model, and sampled in design domain using uniform Latin square test design method；
As shown in figure 3, (30) the multi-objective optimization design of power model sampling step includes:
(31) optimization design variable is chosen: according to white body static analysis test and complete automobile collision test result, selection pair
The thickness for several individual components that bus body strength is affected determines its variation range as optimization design variable；
(32) objective function determines: by the mean effort in white body torsion test, the energy absorption in impact test
It is set to objective function with the quality as design variable structural member；
(33) multiple-objection optimization mathematical model is established: establishing body structure multiple-objection optimization mathematical model；
In (33) the multiple-objection optimization mathematical model establishment step, multiple target cooperates with optimized mathematical model expression formula are as follows:
Wherein,
Design vector x={ x1, x1... xm, wherein x1, x1... xmIt is sub- design variable, m is of sub- design variable
Number,
V-min indicates vector minimization, i.e. object vector f (x)=[f1(x), f2, (x) ... fp(x)]TIn all sons
Objective function must all reach minimum as far as possible, wherein f1(x), f2(x) ... fpIt (x) is specific item scalar functions, p is specific item scalar functions
Number,
gi(x)≤0 it is inequality constraints condition, is boundary condition bound variable, wherein i is the number of bound variable.
(34) design domain sample point determines: being based on uniform Latin hypercube experimental design strategy, chooses suitable sample point
Number, determines the sample point in optimization problem design domain.
(40) objective function agent model efficiency evaluation: constructing the agent model of objective function according to test result, and
Its validity is evaluated using residual sum of squares (RSS)；
(40) the objective function agent model efficiency evaluation step specifically:
Select agent model type for response surface model, and simultaneously using the method for successive Regression to the base letter of agent model
Number is screened, and test number (TN) is further reduced, by carrying out residual sum of squares (RSS) analysis, the essence of auth response surface model to model
Degree.
(50) model optimization solves: it is optimized using agent model of the multi-objective genetic algorithm to objective function,
Obtain multiple Pareto solutions；
(60) robustness evaluation: the Pareto robustness solved is evaluated using Monte Carlo simulation technology；
(60) the robustness evaluation step specifically:
Multiple groups design variable is obtained by the descriptive sampling in Monte Carlo, carries it into response surface approximate function, calculates
The variance of objective function response out, to verify design variable fluctuation to the susceptibility of target response.
(70) prioritization scheme exports: output meets the prioritization scheme of technique requirement.
(70) prioritization scheme exports step specifically:
By the multiple-objection optimization to agent model, the multiple lightweight body structure schemes for meeting target response are obtained,
It fully considers its technological factor and manufacturing cost, exports best design.
Elaborate below with reference to the embodiment of the present invention, the present embodiment under the premise of the technical scheme of the present invention into
Row is implemented, and the detailed implementation method and specific operation process are given, but protection scope of the present invention is not limited to following realities
Apply example.
Embodiment
As shown in Figure 1, a kind of lightweight body structure Multipurpose Optimal Method based on agent model, specifically includes following
Step:
(10) finite element model is established: white body finite element model is established according to the CAD data of vehicle body, as shown in Fig. 2, its
In include unit sum be 664469, wherein quadrilateral units 630941, triangular element 26710 (accounts for unit sum
4%).Corresponding boundary condition is added on white body finite element model, constructs static analysis finite element model, analyzes operating condition packet
Include model analysis and torsion stiffness analysis.Wherein model analysis is Free Modal Analysis, when torsion stiffness is analyzed, damping after constraint
Device installs the x, y, z of hole seat to translational degree of freedom, and applying size in left and right two front dampers installation hole seat is 1356Nm around x
The torque of axis；Corresponding position adds 244kg additional mass to replace dummy and luggage on white body finite element model, and setting front is touched
The boundary condition hit constructs complete automobile collision finite element model.
(20) model validation: the Modal Analysis and test in white body static analysis operating condition are carried out, as a result such as table
Shown in 1, it can be seen that global bending and Torsion mode frequency is almost the same, while Modal Test has more localized modes
State, therefore the precision of white body Static Analysis Model meets the requirements.
1 Modal Analysis of table and test frequency comparative analysis table
Complete automobile collision emulation and test are carried out, can be obtained by Comparative result, the deformation pattern and motion process of body structure
It is substantially consistent, therefore the precision of complete automobile collision model meets the requirements.
(30) multi-objective optimization design of power model samples: according to body-in-white structure and mechanical characteristic and according to white body static state
Analysis test and complete automobile collision test result, choose the thickness conduct for the several individual components being affected to bus body strength
Optimization design variable, the component this time chosen are headstock lower end stringer, headstock right-hand stringer connector, headstock right-hand stringer, vehicle
Head right side crossbeam and headstock left side beams, are respectively defined as δ for its thickness1、δ2、δ3、δ4、δ5, as shown in Figure 5.Consider white body
Torsion stiffness k and maximal impact FmaxTwo constraint conditions, by the mean effort F in white body torsion test15, collision examination
Energy absorption E in testing and the gross mass m as design variable structural member are set to objective function；It is excellent to establish body structure multiple target
Change mathematical model, expression formula are as follows:
Based on uniform Latin hypercube experimental design strategy, 15 sample points are chosen, lightweight body structure is obtained
Assembled scheme in 15.For the convenience being uniformly processed, data have all carried out coded treatment, with minimum value in testing program and maximum
The midpoint of value is 0, is transformed into [- 1,1] section.Each design parameter range distribution it is as follows: the range of thickness δ for [1.0,
2.5]mm,FmaxRange be [39076,112110] N, F15Range be [728.971,1627.138] Ns, the model of ENERGY E
It encloses for [30.306520,51284670] mJ, the range of quality m is [10.629,18.203] kg, and the range of torsion stiffness k is
[13657.108,13801.795] Nm/ (°).
(40) objective function agent model efficiency evaluation: the corresponding finite element model of 15 sample points is established, is turned round
Turn rigidity simulation analysis and complete automobile collision simulation analysis, obtains experimental design scheme and simulation result table is as shown in table 2.
2 experimental design scheme of table and simulation result table
Finally it is fitted obtained response surface expression formula are as follows:
K=0.2114+0.0039 δ3+0.2299δ4+1.066δ3+0.0162δ3 2―0.0215δ4 2― 0.2623δ5 2―
0.0183δ3δ4+0.0093δ3δ5―0.0082δ4δ5
Fmax=0.529 δ2 2+0.244δ3 2―0.245δ4 2―0.191δ1δ2+0.071δ1δ5+0.022δ1―0.108δ2+
0.301δ4+0.989δ5―0.155
F15=-0.176 δ3 2―0.275δ5 2+0.163δ1δ2―0.162δ1δ3―0.148δ1+ 0.060δ2―0.173δ3
+0.616δ4+1.007δ5+0.069
E=0.109 δ2 2―0.159δ5 2+0.418δ1δ2―0.105δ1δ3+0.438δ1δ5+ 0.118δ1+0.189δ2+
0.231δ4+0.676δ5―0.360
M=0.076 δ1 2+0.059δ2 2+0.088δ1δ4―0.043δ1δ5+0.352δ1+0.143δ2+0.183δ3+0.418δ4
+0.575δ5―0.079
Agent model foundation finishes, and the verifying of model accuracy is carried out using residual sum of squares (RSS), and the value of residual sum of squares (RSS) is smaller,
Illustrate that the fitting precision of response surface model is better.Table 3 lists the residual sum of squares (RSS) result of the present embodiment.
3 residual sum of squares (RSS) of table analyzes result
From the data in table 3, it can be seen that each response surface model has reached very high precision, subsequent optimization can satisfy completely
It needs.
(50) model optimization solves: using quick non-dominant multi-objective optimization algorithm (NSGA-II), to optimization design mathematics
Model is solved.The basic parameter configuration of NSGA-II algorithm is as follows: initial population takes 10, and evolutionary generation took for 700 generations, intersects
The factor is 0.9, and cross-distribution index is 20, and variation profile exponent is 100.Multiple feasible multiple targets are obtained by iteration
Pareto optimal solution is as shown in table 4.
4 Pareto optimal solution result table of table
Pareto optimal solution set provides a variety of possible selection schemes for designer
(60) robustness evaluation: Pareto optimal solution set provides a variety of possible selection schemes for designer, and synthesis is examined
Under worry, temporarily selecting No. 5 schemes is optimal case.In order to evaluate the fluctuation of design variable under certainty optimal conditions to target letter
The robustness of number response obtains 100 groups of design variables by the descriptive sampling in Monte Carlo, 100 groups of design variables is substituted into and are rung
It answers in the approximate function of face, calculates the variance of objective function response, i.e. susceptibility of the fluctuation of design variable to target response.Table
5 provide the performance indicator comparative situation of former design scheme and No. 5 schemes, it can be seen that and the standard variance of objective function is very small,
I.e. the robustness of design parameter is very good.
The former design of table 5 and reliability optimization solution calculated result contrast table
(70) prioritization scheme exports: fully considering the technological factor and manufacturing cost of No. 5 schemes, finally determines No. 5 schemes
For optimal case.Scheme after the optimization front longitudinal beam deformation pattern in collision process is more reasonable, and collision safety performance is mentioned
Height, torsion stiffness increase substantially, while vehicle body gross mass is reduced.In conclusion the lightweight vehicle based on agent model
Body structure Multipurpose Optimal Method can significantly improve the comprehensive performance of lightweight vehicle body, and optimization process and final result be all can
Letter, there is preferable engineer application.
Claims (8)
1. a kind of lightweight body structure Multipurpose Optimal Method based on agent model, which comprises the following steps:
(10) finite element model is established: establishing white body finite element model according to the CAD data of vehicle body, including static analysis is limited
Meta-model, complete automobile collision finite element model；
(20) model validation: carrying out static analysis test and complete automobile collision to white body and test, by test result with it is white
Vehicle body FEM Numerical Simulation compares, and verifies the validity of finite element model；
(30) multi-objective optimization design of power model samples: establishing multi-objective optimization design of power mathematics according to body-in-white structure and mechanical characteristic
Model, and sampled in design domain using uniform Latin square test design method；
(40) objective function agent model efficiency evaluation: the agent model of objective function is constructed according to test result, and is used
Residual sum of squares (RSS) evaluates its validity；
(50) model optimization solves: being optimized, is obtained using agent model of the multi-objective genetic algorithm to objective function
Multiple Pareto solutions；
(60) robustness evaluation: the Pareto robustness solved is evaluated using Monte Carlo simulation technology；
(70) prioritization scheme exports: output meets the prioritization scheme of technique requirement.
2. Multipurpose Optimal Method according to claim 1, which is characterized in that (10) the finite element model establishment step
Include:
(11) white body finite element model is established: establishing white body finite element model using HyperMesh software pre-treatment；
(12) vehicle body entity solder joint is simulated: using Cweld unit simulation vehicle body entity solder joint；
(13) FEM meshing grid dividing: is carried out using triangle and quadrilateral mesh unit；
(14) finite element model is established: by adding different boundary condition, establish respectively static analysis finite element model with it is whole
Vehicle collides finite element model.
3. Multipurpose Optimal Method according to claim 2, which is characterized in that in (13) the grid dividing step, net
Lattice quality standard includes:
Length-width ratio<3, angularity<10, Jacobi>0.6,45 °<quadrangle Minimum Internal Angle<130 °, 20 °<triangle Minimum Internal Angle<
100°。
4. Multipurpose Optimal Method according to claim 1, which is characterized in that (30) the multi-objective optimization design of power model
Sampling step includes:
(31) optimization design variable is chosen: according to white body static analysis test and complete automobile collision test result, choosing to vehicle body
The thickness of the biggish several individual components of intensity effect determines its variation range as optimization design variable；
(32) objective function determines: by the mean effort in white body torsion test, the energy absorption in impact test and work
Quality for design variable structural member is set to objective function；
(33) multiple-objection optimization mathematical model is established: establishing body structure multiple-objection optimization mathematical model；
(34) design domain sample point determines: being based on uniform Latin hypercube experimental design strategy, chooses suitable sample points, really
Determine the sample point in optimization problem design domain.
5. Multipurpose Optimal Method according to claim 4, which is characterized in that (33) the multiple-objection optimization mathematical model
In establishment step, multiple target cooperates with optimized mathematical model expression formula are as follows:
Wherein,
Design vector x={ x1, x1... xm, wherein x1, x1... xmIt is sub- design variable, m is the number of sub- design variable,
V-min indicates vector minimization, i.e. object vector f (x)=[f1(x), f2(x) ... fp(x)]TIn all specific item offers of tender
Number must all reach minimum as far as possible, wherein f1(x), f2(x) ... fpIt (x) is specific item scalar functions, p is of specific item scalar functions
Number,
gi(x)≤0 it is inequality constraints condition, is boundary condition bound variable, wherein i is the number of bound variable.
6. Multipurpose Optimal Method according to claim 1, which is characterized in that (40) the objective function agent model has
Effect property evaluation procedure specifically:
Select agent model type for response surface model, and simultaneously using the method for successive Regression to the basic function of agent model into
Row screening, is further reduced test number (TN), by carrying out residual sum of squares (RSS) analysis, the precision of auth response surface model to model.
7. the Multipurpose Optimal Method according to claim 1 based on agent model, which is characterized in that (60) robust
Property evaluation procedure specifically:
Multiple groups design variable is obtained by the descriptive sampling in Monte Carlo, carries it into response surface approximate function, calculates mesh
The variance of scalar functions response, to verify design variable fluctuation to the susceptibility of target response.
8. the lightweight body structure Multipurpose Optimal Method according to claim 1 based on agent model, feature exist
In (70) prioritization scheme exports step specifically:
By the multiple-objection optimization to agent model, the multiple lightweight body structure schemes for meeting target response are obtained, sufficiently
Consider its technological factor and manufacturing cost, exports best design.
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Application publication date: 20191018 |