CN104166774A - Multi-working-condition and multi-target design method for automobile seat framework - Google Patents

Abstract

The invention relates to a multi-working-condition and multi-objective design method for a car seat frame, which includes: selecting design variables of the car seat frame; taking the stiffness of the car seat frame under static and dynamic working conditions as constraint conditions, and The structural quality of the car seat frame and the maximum impact contact force are objective functions, in conjunction with the design variables, the mathematical model of the car seat frame is established; the mathematical model of the car seat frame is calculated with a multi-objective genetic algorithm Carry out the solution to obtain the solution set of the car seat frame; select the structural quality of the car seat frame and the optimal solution of the maximum impact contact force in the solution set of the car seat frame; according to the corresponding optimal The value of the design variable of the frame of the car seat is solved, and the structural members of the frame of the car seat are set. The design method of the invention solves the problems of low accuracy and poor light weight effect existing in the conventional design of car seat frames by experience and analogy.

Description

Multi-condition and multi-objective design method for automobile seat frame

technical field

The invention relates to a manufacturing method of a product, in particular to a multi-working-condition and multi-objective design method for an automobile seat frame.

Background technique

The reliability, comfort and economy of car seats mainly depend on the internal skeleton structure. The seat frame is the main structure that bears the weight of passengers during driving, and is also an important device to protect the occupants in the car in the event of a traffic accident. Therefore, the safety of the seat frame under dynamic and static conditions is an important criterion for frame design. At the same time, the car seat frame is the main part of the seat quality. A reasonable seat frame structure must achieve light weight as much as possible on the premise of meeting safety, so as to obtain good economy and fuel economy.

At present, the design of the car seat frame is mostly based on empirical analogy design. Due to the complexity of the working conditions and usage requirements of the seat frame, it is necessary to comprehensively consider the safety issues of multiple working conditions and achieve multi-objective optimal design. The accuracy of the analog design is not high, and the weight reduction effect is not good, so there is a lot of room for improvement.

Contents of the invention

The purpose of the present invention is to overcome the defects of the prior art, provide a multi-working-condition and multi-objective design method for the car seat frame, and solve the problem of low accuracy and light weight of the existing car seat frame design structure using empirical analogy design Problem with poor performance.

The technical scheme for realizing the above-mentioned purpose is:

The present invention relates to a multi-working-condition and multi-objective design method for an automobile seat frame, comprising:

Taking the structural quality of the car seat frame and the minimum maximum impact contact force under dynamic conditions as the optimal design objective function, the displacement of the car seat frame structure under dynamic and static conditions as constraints, and the key components of the car seat frame structure The geometric dimension is a design variable, and an optimized mathematical model of the car seat frame is established;

Solving the optimized mathematical model of the car seat frame with a multi-objective genetic algorithm to obtain a solution set of the car seat frame;

Establishing an evaluation function, selecting the structural quality M of the car seat frame and the optimal solution of the maximum impact contact force F from the solution set of the car seat frame;

According to the design variable value X of the car seat frame corresponding to the optimal solution, the structural members of the car seat frame are set.

By establishing a mathematical model and a multi-objective genetic algorithm, the structural quality of the car seat frame and the optimal solution of the maximum impact contact force are calculated, and the structural parts of the car seat frame are designed so that the car seat frame can have a light structure. , The advantage of the maximum impact contact force is small. In addition, multi-working conditions, namely static tension and dynamic collision conditions, are considered comprehensively to ensure the safety performance of the designed car seat frame. The design method of the invention solves the problems of low precision and poor light weight effect existing in the conventional design of car seat frames by experience and analogy.

The further improvement of the multi-working-condition and multi-objective design method of the car seat frame of the present invention is that the optimized mathematical model of the car seat frame is:

Find X＝(x ₁ ,..., _xi ,...,x _n ) ^T

Minimize M and F

$\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; .</span>{\mathrm{<span\; class="notranslate">\; \&delta;</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; \&delta;</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; \&delta;</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; \&delta;</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; u</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1,2</span>}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}$

In the formula: M is the mass of the car seat frame structure, F is the maximum impact contact force under dynamic conditions; δ _s and δ _d are the displacements of key points under static and dynamic conditions, respectively, δ ^* _s and δ ^* _d are the displacement limit values of key points under static and dynamic conditions, respectively; X is the design variable, n is the number of design variables, and x _i ^L and x _i ^U are the upper and lower limits of the design variables, respectively.

The further improvement of the multi-working-condition multi-objective design method of the automobile seat frame of the present invention is that the evaluation function is:

$\mathrm{<span\; class="notranslate">\; min</span>}<span\; class="notranslate">\; :</span>\mathrm{<span\; class="notranslate">\; z</span>}<span\; class="notranslate">\; =</span>\sqrt{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; m</span>}}^{<span\; class="notranslate">\; *</span>}}{{\mathrm{<span\; class="notranslate">\; m</span>}}^{<span\; class="notranslate">\; *</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&Center\; Dot;</span>{<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; f</span>}}^{<span\; class="notranslate">\; *</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}^{<span\; class="notranslate">\; *</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}$

In the formula: z is the evaluation factor, M ^* is the ideal value of the car seat frame mass M, F ^* is the ideal value of the maximum impact contact force F; λ is a weight factor related to the seat frame mass M.

The further improvement of the multi-working-condition and multi-objective design method of the automobile seat frame of the present invention is to set the weight factors in the evaluation function based on the fuzzy preference method.

The further improvement of the multi-working-condition and multi-objective design method of the car seat frame of the present invention is that the method for selecting the optimal solution of the structural quality and the maximum impact contact force of the car seat frame includes:

Screening the structural mass M and the maximum impact contact force F of the car seat frame in the solution set of the car seat frame to obtain a frontier set;

Substituting the values of the structural mass M and the maximum impact contact force F of the car seat frame in the front set into the evaluation function to solve, obtain the structural mass M and the maximum impact contact force of the car seat frame The evaluation factor corresponding to the value of force F;

The structural quality and maximum impact contact force of the car seat frame corresponding to the minimum value of the evaluation factor are selected as the optimal solution.

Description of drawings

Fig. 1 is the schematic structural view of the car rear seat skeleton;

Fig. 2 is a schematic diagram of stretching seat belts in rear seats of a car;

Figure 3 is a schematic diagram of the impact of the trunk of the rear seat of the car;

Fig. 4 is the solution set of the structural mass and the maximum impact contact force of the car seat frame;

Fig. 5 is the frontier solution set of the structure quality and the maximum impact contact force of the car seat frame;

Figure 6 is a comparison diagram of the displacement in the X direction before and after the optimization of the car seat frame under static conditions;

Figure 7 is a comparison diagram of the displacement in the Y direction before and after the optimization of the car seat frame under static conditions;

Fig. 8 is a graph showing the variation of the distance between the car seat frame and the surface A before and after optimization under dynamic working conditions;

Figure 9 is a comparison diagram before and after optimization of the maximum impact contact force of the car seat frame under dynamic working conditions.

Detailed ways

The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

The present invention proposes a car seat frame optimization design method based on a multi-objective evaluation mechanism in consideration of dynamic and static multi-working conditions. Establish a multi-objective optimization mathematical model of the seat frame structure, with the goal of the lightest frame structure and the smallest maximum impact contact force, where the maximum impact contact force refers to the contact force on the car seat frame when the entire car is subjected to the maximum impact force; The improved multi-objective genetic algorithm is used to obtain the Pareto frontier solution set, the weight factors of the sub-objectives are determined by the fuzzy preference method, and the multi-objective evaluation function is established to obtain the best comprehensive satisfaction scheme in the Pareto frontier solution set. According to the arrangement of the structural parts of the car seat frame, the car seat frame can achieve the goal of light weight under the premise of satisfying the safety of multiple working conditions, and can obtain good product economy and fuel economy. The multi-working-condition and multi-objective design method of the automobile seat frame of the present invention will be described below in conjunction with the accompanying drawings.

The multi-working-condition and multi-objective design method of the automobile seat frame of the present invention comprehensively considers the design requirements of the safety of the structural dynamic and static working conditions and the lightweight structure, and takes the structural quality and the minimum maximum impact contact force as the optimal design objective function, and the structure is dynamic and static. The stiffness under the working condition is the constraint condition, and the geometric dimensions of the key components are used as the design variables to seek the optimal solution. The design variables of the car seat frame are selected, combined with the objective function and constraints, an optimized mathematical model of the car seat frame is established as shown in formula (1).

Find X＝(x ₁ ,..., _xi ,...,x _n ) ^T

Minimize M and F

$\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; .</span>{\mathrm{<span\; class="notranslate">\; \&delta;</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; \&delta;</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; \&delta;</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; \&delta;</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{\mathrm{<span\; class="notranslate">\; u</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1,2</span>}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}$

In the formula: M is the mass of the car seat frame, F is the maximum impact contact force under dynamic conditions; δ _s and δ _d are the displacements of key points under static and dynamic conditions, respectively, δ ^* _s and δ ^* _d are the displacement limit values of key points under static and dynamic conditions, respectively; X is the design variable, n is the number of design variables, x _i ^L and x _i ^U are the upper and lower limits of the design variables, respectively.

Multi-objective genetic algorithm is used to solve the multi-objective optimization problem, so as to obtain the Pareto frontier solution set of the problem. That is, the solution set corresponding to each variable in Equation 1, the solution set of the car seat frame, including multiple sets of design variable values.

An appropriate evaluation function is constructed to obtain the optimal solution in the car seat skeleton solution set. By establishing an evaluation function, an ideal solution can be obtained from the Pareto solution set that can repeatedly reflect that the designer has different emphasis on the goal, and the evaluation function shown in formula (2) is used:

$\mathrm{<span\; class="notranslate">\; min</span>}<span\; class="notranslate">\; :</span>\mathrm{<span\; class="notranslate">\; z</span>}<span\; class="notranslate">\; =</span>\sqrt{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; m</span>}}^{<span\; class="notranslate">\; *</span>}}{{\mathrm{<span\; class="notranslate">\; m</span>}}^{<span\; class="notranslate">\; *</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&Center\; Dot;</span>{<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; f</span>}}^{<span\; class="notranslate">\; *</span>}}{{\mathrm{<span\; class="notranslate">\; f</span>}}^{<span\; class="notranslate">\; *</span>}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

In formula (2), z is the evaluation factor, and the smaller the value of z, the better the corresponding solution; M ^* is the ideal value of the car seat frame mass M, F ^* is the ideal value of the maximum impact contact force F; A weighting factor related to the skeleton mass M. Because weight factors are added to the evaluation function, it is easier to obtain an effective solution approved by the designer.

The invention is based on a fuzzy preference method, and calculates the weight factors of each sub-objective according to the designer's preference for different objective functions.

Substituting the objective function of the car seat skeleton solution set, that is, the structural quality and the maximum impact contact force into formula (2), the corresponding evaluation factor values are obtained, and the smallest value of the evaluation factor z is the optimal solution. The structure quality and maximum impact contact force corresponding to the minimum z value are optimal, and then the design variable value corresponding to the maximum impact contact force can also be easily found out, and the structural parts of the car seat frame are set with the design variable value, The lightweight design of the car seat frame under the condition of multiple working conditions and multiple objectives is realized.

As a preferred embodiment of the present invention, the method for selecting the optimal solution of structural mass and maximum impact contact force includes:

Filter the structural quality and maximum impact contact force of the car seat frame in the solution set of the car seat frame to obtain the frontier set;

Establish the structural quality of the car seat frame and the evaluation function of the maximum impact contact force, such as formula (2), set the weight factor in the evaluation function;

Substituting the structural quality of the car seat frame in the frontier set and the value of the maximum impact contact force into the evaluation function for solution, and obtaining the evaluation factor corresponding to the structural quality of the car seat frame and the value of the maximum impact contact force ;

The structural quality of the car seat frame and the maximum impact contact force corresponding to the minimum value of the evaluation factor are selected as the optimal solution.

Taking the rear seat frame of an automobile as an example below, the design method of the present invention will be described in detail in conjunction with the accompanying drawings.

Referring to Fig. 1 , it shows a schematic structural diagram of a car rear seat frame. Below in conjunction with FIG. 1 , the multi-working-condition and multi-objective design method for the automobile seat frame of the present invention will be described.

As shown in Figure 1, in the design process of the car seat frame multi-working condition multi-objective design method of the present invention, according to the optimized mathematical model of formula (1), determine the relevant limit value in the design variable and constraint condition:

Identify Design Variables

In the rear seat frame of the car, according to the contribution of each structural part to the objective function (ie, the structural quality of the car seat frame and the maximum impact contact force) and constraint conditions (stiffness under dynamic and static conditions), the selected Design variables, select the thickness of 60% frame square tube T72, 60% intermediate support tube T73, back plate T75, 40% frame round tube T76, and 60% frame round tube T77 as design variables, see Table 1, which shows the design The upper and lower bounds of the variable.

Table 1 Design variable name, initial value, and upper and lower limit value correspondence table to determine the relevant limit values of constraints

According to the relevant requirements of the regulations of GB14167-2006 "Automobile Seat Belt Installation Fixing Points", first of all, the relative displacement of the seat belt fixing point must be within the specified range. As shown in Figure 2, point K is the seat belt fixing point, point R is the reference point for seat design, and point C is the reference point located at 450mm in the vertical direction of point R. The plane P passing through the two points R and C is the reference plane for displacement in the X direction, and the plane Q passing through point C and perpendicular to the plane P is the reference plane for displacement in the Y direction.

According to the test requirements of "Automotive Seat Belt Installation Fixing Points", the criteria for the lightweight design of the seat frame structure under static conditions are:

1) The lateral (X direction) displacement of the fixed point on the three-point safety belt cannot exceed the plane P;

2) The longitudinal (Y direction) displacement of the fixed point on the three-point safety belt cannot exceed the plane Q;

3) After the test, the seat back and its fasteners are allowed to deform to a certain extent, but large-scale tearing or large-area peeling off of solder joints cannot occur.

According to the requirements of GB15083-2006 "Requirements and Test Methods for Car Seats and Seat Fixing Devices", as shown in Figure 3, when the trunk module 20 on the vehicle body floor 30 is impacted by the collision of the car, the trunk module 20 will collide. As for the seat frame 10, the backrest of the seat frame 10 cannot exceed the surface A during a collision. Referring to Table 2, the initial values of the optimization objectives and reference variables are given.

Table 2 Initial and limit values of optimization objectives and reference variables

Multi-condition multi-objective optimization problem solving

In the optimization process, the dynamic and static loads required by the regulations are applied, and the relevant design variables and dynamic and static reference quantities are set in the optimization software, and the multi-objective genetic algorithm is used to solve the problem, and the Pareto solution set of the multi-objective optimization problem is obtained, as shown in Figure 4. The boundary set was screened out from the Pareto solution set to form the Pareto frontier solution set for the mass-maximum impact contact force two targets. As shown in Figure 5, the six groups of solutions were obtained by numbering from top to bottom.

Selection of multi-objective optimization scheme

Weight factor determination

Based on the fuzzy preference method, the weight factors of each sub-objective are calculated according to the designer's preference for different objective functions. Let n be the number of design variables, k be the number of objective functions, and l=n+k. Assume that the set of important elements that affect the weight factor is Ra={r1, r2,...,rl}, and at the same time set the matrix R for initializing the l×l order normalization index, and the definition rules of the elements in the matrix R are shown in Table 3.

$\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; =</span>\left[\begin{array}{cccc}{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 11</span>}}& {\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 12</span>}}& <span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>& {\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; l</span>}}\\ {\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; twenty\; one</span>}}& {\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; twenty\; two</span>}}& <span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>& {\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; l</span>}}\\ <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>\\ {\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}& {\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}& <span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span>& {\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; ll</span>}}\end{array}\right]$

Table 3 Definition rules of elements in matrix R

Table 3 shows: if r _i and r _j are equally important, it is expressed as λ(r _i )～λ(r _j ); if r _i is not as important as r _j , it is expressed as λ(r _i )<λ(r _j ); if r _i is far less important than rj, it is expressed as λ(r _i )<<λ(r _j ). If λ(r _i )～λ(r _j ), then set r _ij =r _ji =0.5; if λ(r _i )<λ(r _j ), then set r _ij =α, r _ji =β; if λ (r _i )<<λ(r _j ), then r _ij =μ, r _ji =ν, where α, β, μ and ν are any real numbers within the interval (0,1), μ<α<1/ 2<β<ν, and α+β=μ+ν=1.

For any r∈R, the normalized weight factor calculation formula is:

$\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; \&Sigma;S</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; R</span>}<span\; class="notranslate">\; )</span>}$

Among them, S _i (ri _ii , R) represents the sum of other elements in the i-th row of the matrix R except for the elements of rii; ∑S(ri _ii , R) represents the sum of all elements in the matrix R except for the elements on the diagonal and.

Using the above calculation method, we can get λ(M)=0.5811, λ(F)=0.4189.

Determination of the optimal solution

According to the single-objective optimization results, assuming that the ideal solution of the first objective is M ^* = 95.35kg, and the ideal solution of the second objective is F ^* = 17355N, determine the evaluation factors of the 6 groups of optimized solutions in Table 4 according to formula (2) z, as shown in Table 4.

serial number M/kg F/N evaluation factor 1 96.0678 15821.6 5.3925 2 95.7090 15678.5 4.5635

3 95.9709 15325.8 2.5196 4 96.2328 14973.2 0.4752 5 95.8598 14913.8 0.1330 6 96.5602 14937.3 0.2708

Table 4 The z value of the multi-objective optimization solution set

According to the calculation results in Table 4, it is easy to find that the evaluation factor z of the fifth set of solutions is the smallest, so this set of solutions is selected as the optimal solution of multi-objective optimization, that is, M=95.8598kg, F=14913.8N.

After optimizing the car seat frame, the structure of related design variables is shown in Table 5. The weight of the optimized seat frame is reduced from 17.9kg to 15.82kg, which is 9.45% lower. And the optimized structure is substituted into the seat static seat belt tensile finite element model and the dynamic trunk impact finite element model respectively, and recalculated and analyzed.

name ID Before optimization/mm After optimization/mm After rounding/mm 60% frame square tube T72 1.5 1.3369 1.4 60% middle support tube T73 1.6 1.2 1.2 back panel T75 0.7 0.5843 0.6 40% frame round tube T76 1.5 1.1895 1.2 60% frame round tube T77 2.0 1.6701 1.8

Table 5 Optimization results

Under the condition of static seat belt stretching, the change of the distance between the measuring point and the first quadrant of the two reference planes before and after optimization, the results are shown in Figure 6 and Figure 7, the solid line is the change curve before optimization, and the dotted line is the optimization subsequent change curves. The deformation of the backrest increased, from 277.14mm to 294.87mm in the X direction, and from 1.13mm to 2.34mm in the Y direction, but did not exceed the reference surface specified by the regulations, and all met the static test requirements.

The displacement changes of the measuring points after seat optimization under dynamic working conditions are shown in Figure 8. The solid line is the curve of the distance of the measuring points before optimization, and the dotted line is after optimization. The deformation of the headrest measurement point increased from 358.19mm before optimization to 381.79mm, an increase of 6.59%, and the backrest measurement point changed from 382.4mm before optimization to 423.68mm after optimization, an increase of 10.79%; but it did not exceed the regulations The specified reference surface meets the requirements of the regulations.

As shown in Figure 9, the impact load curve of the 60% side of the rear seat during the dynamic collision process, the solid line is the impact contact force curve before optimization, and the dotted line is the impact contact force curve after optimization; from the analysis of the impact curve, it can be seen that The maximum impact contact force dropped from 17355.1N before optimization to 14913.8N, a decrease of 14.07%.

Comprehensive verification analysis, the result design of multi-objective optimization of static and dynamic multi-working conditions car seats all meet the requirements of GB14167 and GB15083 relevant regulations, and the detailed parameters of each state variable before and after optimization are compared as shown in Table 6, which proves the advantages of the present invention correctness and feasibility.

Table 6 Comparison table of state variable parameters before and after optimization

The beneficial effect of the multi-working-condition multi-objective design method of the automobile seat frame of the present invention is:

By establishing a mathematical model and a multi-objective genetic algorithm, the structural quality of the car seat frame and the optimal solution of the maximum impact contact force are calculated, and the structural parts of the car seat frame are designed so that the car seat frame can have a light structure. , The advantage of the maximum impact contact force is small. In addition, multi-working conditions, namely static tension and dynamic collision conditions, are considered comprehensively to ensure the safety performance of the designed car seat frame. The design method of the invention solves the problems of low precision and poor light weight effect existing in the conventional design of car seat frames by experience and analogy.

The present invention has been described in detail above with reference to the embodiments of the accompanying drawings, and those skilled in the art can make various changes to the present invention according to the above description. Therefore, some details in the embodiments should not be construed as limiting the present invention, and the present invention will take the scope defined by the appended claims as the protection scope of the present invention.

Claims (5)

1. the multiobject method for designing of automobile chair frame multi-state, is characterized in that, comprising:

Taking the maximum impact contact force minimum under automobile chair frame architecture quality and dynamic operation condition as optimal design objective function, the displacement of automobile chair frame structure under sound state operating mode is constraint condition, taking the physical dimension of automobile chair frame structural key member as design variable, set up the optimized mathematical model of described automobile chair frame;

With multi-objective genetic algorithm, the optimized mathematical model of described automobile chair frame is solved, obtain the disaggregation of described automobile chair frame;

Set up evaluation function, concentrate and select the architecture quality M of described automobile chair frame and the optimum solution of maximum impact contact force F from the solution of described automobile chair frame;

According to the design variable X value of the described automobile chair frame of the described optimum solution of correspondence, the structural member of described automobile chair frame is set.

2. the multiobject method for designing of automobile chair frame multi-state as claimed in claim 1, is characterized in that, the optimized mathematical model of described automobile chair frame is:

Find?X＝(x ₁，…，x _i，…，x _n) ^T

Minimize?M?and?F

$s.t.{\mathrm{\&delta;}}_s\left(X\right)\&le;{\mathrm{\&delta;}}_s^{*}\left(X\right)$

${\mathrm{\&delta;}}_d\left(X\right)\&le;{\mathrm{\&delta;}}_d^{*}\left(X\right)$

$x_i^L\&le;x_i\&le;x_i^U,i=\mathrm{1,2},...,n$

In formula: M is automobile chair frame architecture quality, F is the maximum impact contact force under dynamic operation condition; δ _sand δ _dbe respectively the displacement of key point under static operating mode and dynamic operation condition, δ ^* _sand δ ^* _dbe respectively the displacement limits value of key point under static operating mode and dynamic operation condition; X is design variable, the number that n is design variable, x _i ^land x _i ^ube respectively the bound of design variable.

3. the multiobject method for designing of automobile chair frame multi-state as claimed in claim 1, is characterized in that, described evaluation function is:

$\min :z=\sqrt{{\mathrm{\&lambda;}\left(\frac{M-M^{*}}{M^{*}}\right)}^2+(1-\mathrm{\&lambda;})\&CenterDot;{\left(\frac{F-F^{*}}{F^{*}}\right)}^2}$

In formula: z is for evaluating the factor, M ^*the ideal value of automobile chair frame mass M, F ^*it is the ideal value of maximum impact contact force F; λ is the weight factor relevant to chair framework mass M.

4. the multiobject method for designing of automobile chair frame multi-state as claimed in claim 3, is characterized in that, based on ambiguous preference method, sets the weight factor in described evaluation function.

5. the multiobject method for designing of automobile chair frame multi-state as claimed in claim 3, is characterized in that, selects the method for the architecture quality of described automobile chair frame and the optimum solution of maximum impact contact force to comprise:

Architecture quality M and the maximum impact contact force F of the described automobile chair frame that the solution of described automobile chair frame is concentrated screen, and obtain forward position set;

By solving in evaluation function described in the architecture quality M of described automobile chair frame in the set of described forward position and the value substitution of maximum impact contact force F, obtain the evaluation factor corresponding with the architecture quality M of described automobile chair frame and the value of maximum impact contact force F;

Selecting architecture quality and the maximum impact contact force of described automobile chair frame corresponding to the minimum value of the described evaluation factor is optimum solution.