An optimization method for cab swing arm guide mechanism based on equivalent stiffness theory

Abstract

The invention discloses an optimization method for a cab swing arm guide mechanism based on an equivalent stiffness theory. The method establishes a three-dimensional model of a cab suspension system, and establishes a corresponding simulation model according to the established three-dimensional model; establishes an equivalent stiffness simulation analysis system for the cab suspension system according to the established simulation model, and obtains the equivalent stiffness of the cab suspension system by simulation; analyzes the main structures that affect the equivalent stiffness due to the additional stiffness obtained according to the obtained equivalent stiffness, and selects a swing arm guide mechanism that reduces the deflection amplitude as an optimized design structure; comprehensively analyzes the structural parameters of the guide swing arm in the swing arm guide mechanism, uses a design variable screening method to sort the importance of the influence of each parameter on the equivalent stiffness, and plans the horizontal interval of each design variable based on the sorting result; establishes an equivalent stiffness simulation approximate model through an approximate model construction method to replace the original complex simulation model of the commercial vehicle cab suspension system; uses the residual sum of squares of the equivalent stiffness obtained by simulation of the approximate model and the design stiffness as an evaluation index, and uses a non-sequential quadratic programming algorithm to optimize and analyze the swing arm guide mechanism.

Description

Technical Field

[0001] The invention relates to the technical field of vibration isolation optimization of a commercial vehicle cab, and in particular to an optimization method for a cab swing arm guide mechanism based on an equivalent stiffness theory. Background Art

[0002] In recent years, my country's transportation industry has ushered in a period of vigorous development. As the demand for commercial vehicles increases day by day, automobile companies have gradually realized that the NVH (Noise Vibration and Harshness) performance of the whole vehicle has an increasingly important position in market competition, and the vibration isolation performance of the cab is one of the important indicators that determine the NVH performance of the whole vehicle, and its quality directly affects the driver's riding comfort. The ISO 2631-2003 document points out that the human body is more sensitive to vibrations within 0.5 to 12.5 Hz, and compared with vertical vibrations, pitch and roll movements have a more serious impact on the driver's subjective comfort.

[0003] The stiffness of the cab suspension system is one of the key parameters that affect the vibration isolation performance of the cab, and is mainly composed of the suspension spring stiffness and the rubber elastic element stiffness. The suspension spring stiffness is generally calculated according to the need for vibration isolation, with the aim of making the vertical deviation frequency of the cab avoid the chassis resonance frequency as much as possible to improve the vibration isolation effect. Therefore, the stiffness of the system is largely determined by the suspension spring stiffness. In comparison, the stiffness of the rubber elastic element accounts for a very small proportion of the stiffness of the system. At the same time, the rubber element itself has the characteristics of stiffness nonlinearity, stiffness dispersion, and structural asymmetry, which makes its stiffness difficult to measure during vehicle assembly. However, the stiffness of the rubber elastic element cannot be ignored, because the structural design of the swing arm guide mechanism in the cab suspension system is prone to cause severe deformation of the bushing at the key stress point, resulting in greater stiffness. When calculating the stiffness of the system, if the stiffness caused by the deformation of the elastic element is ignored, it will cause large errors in the subsequent cab smoothness analysis; if the stiffness of each rubber elastic element is measured separately and then the measured stiffness is added to the suspension spring stiffness, it will not only lead to error accumulation, but also greatly increase the measurement workload of technicians.

[0004] In order to solve the above problems, a new measurement method is needed to conveniently obtain the stiffness of the cab suspension system. At the same time, an optimization method with fewer human factors and strong objectivity is used to reduce the influence of the bushing stiffness at the swing arm guide mechanism on the stiffness of the cab suspension system, so that the deviation between the system stiffness value and the design stiffness value is reduced. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and to provide a method for optimizing the cab swing arm guide mechanism based on the equivalent stiffness theory. Under the current industry trend, this method can reduce the stiffness measurement cost of the cab suspension system for enterprises, and at the same time improve the vibration isolation performance of the cab by improving the consistency between the stiffness of the cab suspension system and the design stiffness.

[0006] The technical solution for achieving the purpose of the present invention is:

[0007] A cab swing arm guide mechanism optimization method based on equivalent stiffness theory comprises the following steps:

[0008] 1) Establish a three-dimensional model of the cab suspension system, and establish a corresponding simulation model based on the established three-dimensional model;

[0009] 2) According to the simulation model established in step 1), an equivalent stiffness simulation analysis system of the cab suspension system is established to simulate and obtain the equivalent stiffness of the cab suspension system;

[0010] 3) According to the equivalent stiffness obtained in step 2), the main structures that affect the equivalent stiffness due to the additional stiffness are analyzed, and the swing arm guide mechanism that reduces the deflection amplitude is selected as the optimized design structure;

[0011] 4) Comprehensively analyze the structural parameters of the guide swing arm in the swing arm guide mechanism, use the design variable screening method to sort the importance of each parameter on the equivalent stiffness, and plan the level range of each design variable based on the sorting results;

[0012] 5) Through the approximate model construction method, an equivalent stiffness simulation approximate model is established to replace the original complex simulation model of the commercial vehicle cab suspension system;

[0013] 6) The residual sum of squares of the equivalent stiffness obtained by simulating the approximate model and the design stiffness is used as an evaluation index, and a non-sequential quadratic programming algorithm is used to optimize and analyze the swing arm guide mechanism.

[0014] In step 1), the cab suspension system includes a cab model, a cab front suspension model, a cab rear suspension model and a frame model.

[0015] In step 2), the equivalent stiffness simulation analysis system adds displacement excitation points to the cab simulation model to make the cab produce horizontal stage equal-distance displacement, obtains the reaction force value of each excitation point at each stage, and finally calculates the equivalent stiffness curve, wherein the calculation formula of the equivalent stiffness of the cab suspension system is:

[0016]

[0017] In formula (1), K Eis the equivalent stiffness of the cab suspension system; F i D is the force sensor measurement data at the i-th excitation point on the cab; i It is the displacement sensor measurement data of the i-th excitation point on the cab.

[0018] In step 4), the design variable screening method includes sensitivity analysis method and contribution analysis method.

[0019] In step 5), the approximate model construction method is to use the response surface method to fit the design space using multiple functions, and the specific fitting formula is:

[0020]

[0021] In formula (2), is the objective function; ij are polynomial coefficients; x i x j is the optimization variable.

[0022] In step 6), the design stiffness is calculated by simplifying the cab into a mass point during the cab parameter design stage, and calculating the total spring stiffness at the theoretical required modal frequency of the cab, that is, the design stiffness. Finally, the total spring stiffness is distributed to the front and rear suspensions according to the center of mass position. The specific calculation method is as follows:

[0023]

[0024] In formula (3), ω c is the vertical deflection frequency of the cab suspension; m is the total weight of the cab; K is the spring stiffness; N c is the gravity of the cab; d is the up and down movement of the cab suspension;

[0025] The residual sum of squares is calculated as follows:

[0026]

[0027] In formula (4), E RSS is the residual sum of squares, n is the number of equal-distance segments of the cab suspension system displacement stroke; K i is the equivalent stiffness value when the cab is lowered by a distance i; K a is the design stiffness value;

[0028] The sequential quadratic programming algorithm has the following steps:

[0029] 7-1) Given an initial point X 0 , convergence accuracy∈, let H 0 =I 0 , set k = 0;

[0030] Where X 0 represents the design variable value of the initial state; ∈=0.001; H 0 is the second-order derivative matrix of the initial state objective function; I 0 represents the constraints that play a role in the initial state inequality constraints; k represents the number of iterations;

[0031] 7-2) The objective function of the original problem is listed as:

[0032]

[0033] Where f(X) is the objective function of optimizing the hard point coordinates of the guide swing arm; g u (X) is the inequality constraint for optimizing the hard point coordinates of the guide swing arm; h v Optimize the equality constraints of hard point coordinates for the guided swing arm;

[0034] At the kth iteration, the objective function is set at the iteration point X k Simplify it into a quadratic function and simplify the constraints into a linear function, then the general form of the quadratic programming problem is as follows:

[0035]

[0036] Where S represents the determination condition of the search direction S = X 0 -X k (k=1, 2, ...); X k (k=1, 2, ...) represents the design variable value at the kth iteration; H k represents the second-order derivative matrix of the objective function at the kth iteration; C represents the response variable value at the kth iteration; A represents the inequality constraint simplified to a linear function matrix expression; B represents the matrix expression of the inequality constraint; A eq The matrix expression that represents the equality constraint simplified to a linear function; B eq Matrix expressions representing equality constraints;

[0037] 7-3) Solve the above quadratic programming problem and let S k =S * ;

[0038] Where S k (k=1, 2, ...) represents the judgment condition at the kth iteration, S * represents the optimal decision condition;

[0039] 7-4) In direction S k Perform a constrained unique search on the original problem objective function to obtain the next iteration point X k+1 ;

[0040] Where Xk+1 represents the design variable value at the k+1th iteration;

[0041] 7-5) Termination judgment: If X k+1 If the termination criterion of the given precision is met, then X k+1 As the optimal solution, f(X k+1 ) as the optimal iteration of the objective function, terminate the calculation; otherwise, go to step 7-6);

[0042] 7-6) Modification of H according to DFP method k+1 , let k=k+1, go to step 7-2);

[0043] The DFP method represents the DFP correction method, and the iterative format of this method is

[0044] The present invention provides a cab swing arm guide mechanism optimization method based on equivalent stiffness theory. The method can optimize the guide swing arm structural parameters of the swing arm guide mechanism without changing the cab suspension spring stiffness and the stiffness of each elastic element, so that the stiffness of the system tends to the design stiffness value, and finally optimizes the vibration isolation performance of the cab. When optimizing the stiffness of the system, the method can avoid replacing the suspension spring and each elastic element, reduce the cost required for optimization, and also improve the accuracy of measuring stiffness. The method of the present invention can optimize the guide swing arm structural parameters without changing the cab suspension spring stiffness and the rubber elastic element stiffness, so that the equivalent stiffness of the cab suspension system tends to the design stiffness value. After the optimization is completed, the relative error between the equivalent stiffness curve of the cab suspension system and the design stiffness curve is reduced by 28.4%, and the equivalent stiffness optimization effect of the cab suspension system is better. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a schematic diagram of a three-dimensional model in an embodiment;

[0046] Figure 2 It is a schematic diagram of a simulation model of an embodiment;

[0047] Figure 3 Schematic diagram of an equivalent stiffness simulation analysis system for a cab suspension system of an embodiment;

[0048] Figure 4 Schematic diagram of equivalent stiffness curve of the embodiment;

[0049] Figure 5 It is a schematic diagram of the sensitivity analysis results of the embodiment;

[0050] Figure 6 It is a schematic diagram of the approximate model fitting accuracy of the embodiment;

[0051] Figure 7 It is a schematic diagram for comparing the NLPQL algorithm optimization result curves of the embodiment. DETAILED DESCRIPTION

[0052] The present invention is further described below with reference to the accompanying drawings and embodiments, but the present invention is not limited thereto.

[0053] Example:

[0054] In the embodiment of the present invention, there is design directional knowledge (such as X direction, Y direction, Z direction...), then the directional indication is only used to explain the relative position relationship, movement status, etc. between various components, various forces and objects of action, and various sensors and identification objects in the global coordinate system given by the simulation software. If the posture of the global coordinate system changes, the directional indication will also change accordingly.

[0055] A cab swing arm guide mechanism optimization method based on equivalent stiffness theory comprises the following steps:

[0056] 1) Establish a three-dimensional model of the cab suspension system. The established three-dimensional model is as follows: Figure 1 As shown;

[0057] 2) According to the established 3D model, establish the required simulation model, which includes: cab, cab front suspension, cab rear suspension and frame. The established simulation model is as follows Figure 2 shown.

[0058] 3) According to the established simulation model, an equivalent stiffness simulation analysis system of the cab suspension system is established to simulate and obtain the equivalent stiffness of the cab suspension system. Figure 3 As shown in Figure 2, the equivalent stiffness curve obtained by simulation is as follows: Figure 4 shown.

[0059] 4) According to the equivalent stiffness of the cab suspension system obtained, the main structures that affect the equivalent stiffness due to the additional stiffness are analyzed, and the swing arm guide mechanism that reduces the deflection amplitude is selected as the optimized design structure. The structural parameter values ​​of the guide swing arm are shown in Table 1.

[0060] Table 1 Optimized coordinate parameters of the front swing arm guide mechanism

[0061]

[0062]

[0063] The structural parameters of the guide swing arm in the swing arm guide mechanism are comprehensively analyzed, and the design variable screening method is used to sort the importance of the influence of each parameter on the equivalent stiffness, and the level range of each design variable is planned based on the sorting results. The ranking of the sensitivity analysis results of each design variable is as follows Figure 5 shown.

[0064] 5) Through the approximate model construction method, an equivalent stiffness simulation approximate model is established to replace the original complex model of the commercial vehicle cab suspension system. The fitting accuracy of the constructed approximate model is as follows: Figure 6 shown.

[0065] 6) The residual sum of squares of the equivalent stiffness obtained by simulating the approximate model and the design stiffness is used as the evaluation index, and the non-sequential quadratic programming algorithm is used to optimize the swing arm guide mechanism. Figure 7 As shown, the optimized parameters of the guide swing arm structure are shown in Table 2.

[0066] Table 2 Coordinate parameters of optimized rear swing arm guide mechanism

[0067]

[0068] The design stiffness curve in the figure is 174 newton / mm, combined with Figure 7 The data in Table 1 and Table 2 are used to calculate the absolute error sum of the equivalent stiffness curve and the design stiffness curve before and after the simulation, and then the relative error of the equivalent stiffness curve before and after the simulation is compared. After calculation, the error sum of the equivalent stiffness curve and the design stiffness curve of the cab suspension system before optimization is 57.8; the error sum of the equivalent stiffness curve and the design stiffness curve of the cab suspension system after optimization is 41.4, and the relative error is reduced by 28.4%.

Claims

1. A cab swing arm guide mechanism optimization method based on equivalent stiffness theory, characterized in that: The steps include: 1) Establish a three-dimensional model of the cab suspension system, and establish a corresponding simulation model based on the established three-dimensional model; 2) According to the simulation model established in step 1), an equivalent stiffness simulation analysis system of the cab suspension system is established to obtain the equivalent stiffness of the cab suspension system by simulation; 3) According to the equivalent stiffness obtained in step 2), the main structures that affect the equivalent stiffness due to the additional stiffness are analyzed, and the swing arm guide mechanism that reduces the deflection amplitude is selected as the optimized design structure; 4) Comprehensively analyze the structural parameters of the guide swing arm in the swing arm guide mechanism, use the design variable screening method to sort the importance of each parameter on the equivalent stiffness, and plan the level range of each design variable based on the sorting results; 5) Through the approximate model construction method, an equivalent stiffness simulation approximate model is established to replace the original complex simulation model of the commercial vehicle cab suspension system; 6) The residual sum of squares of the equivalent stiffness obtained by simulating the approximate model and the design stiffness is used as an evaluation index, and a non-sequential quadratic programming algorithm is used to optimize and analyze the swing arm guide mechanism; In step 2), the equivalent stiffness simulation analysis system adds displacement excitation points to the cab simulation model to make the cab produce horizontal stage equal-distance displacement, obtains the reaction force value of each excitation point at each stage, and finally calculates the equivalent stiffness curve, wherein the calculation formula of the equivalent stiffness of the cab suspension system is: In formula (1), K E is the equivalent stiffness of the cab suspension system; F i D is the force sensor measurement data at the i-th excitation point on the cab; i is the displacement sensor measurement data of the i-th excitation point on the cab; In step 6), the design stiffness is calculated by simplifying the cab into a mass point during the cab parameter design stage, and calculating the total spring stiffness at the theoretical required modal frequency of the cab, that is, the design stiffness. Finally, the total spring stiffness is distributed to the front and rear suspensions according to the center of mass position. The specific calculation method is as follows: In formula (2), ω c is the vertical deflection frequency of the cab suspension; m is the total weight of the cab; K is the spring stiffness; N c is the gravity of the cab; d is the up and down movement of the cab suspension; The residual sum of squares is calculated as follows: In formula (3), E RSS is the residual sum of squares, n is the number of equal-distance segments of the cab suspension system displacement stroke; K i is the equivalent stiffness value when the cab is lowered by a distance i; K a is the design stiffness value; The sequential quadratic programming algorithm has the following steps: 7-1) Given an initial point X 0 , convergence accuracy∈, let H 0 =I 0 , set k = 0; Where X 0 The values ​​of the design variables representing the initial states; ∈=0.001;H 0 is the second-order derivative matrix of the initial state objective function; I 0 represents the constraints that play a role in the initial state inequality constraints; k represents the number of iterations; 7-2) The objective function of the original problem is listed as: Where f(X) is the objective function for optimizing the hard point coordinates of the guide swing arm; g u (X) is the inequality constraint for optimizing the hard point coordinates of the guide swing arm; h v Optimize the equality constraints of hard point coordinates for the guided swing arm; At the kth iteration, the objective function is set at the iteration point X k Simplify it into a quadratic function and simplify the constraints into a linear function, then the general form of the quadratic programming problem is as follows: Where S represents the determination condition of the search direction S = X 0 -X k (k=1, 2, ...); X k (k=1, 2, ...) represents the design variable value at the kth iteration; H k represents the second-order derivative matrix of the objective function at the kth iteration; C represents the response variable value at the kth iteration; A represents the inequality constraint simplified to a linear function matrix expression; B represents the matrix expression of the inequality constraint; A eq The matrix expression that represents the equality constraint simplified to a linear function; B eq Matrix expressions representing equality constraints; 7-3) Solve the above quadratic programming problem and let S k =S * ; Where S k (k=1, 2, ...) represents the judgment condition at the kth iteration, S * represents the optimal decision condition; 7-4) In direction S k Perform a constrained unique search on the original problem objective function to obtain the next iteration point X k+1 ; Where X k+1 represents the design variable value at the k+1th iteration; 7-5) Termination judgment: If X k+1 If the termination criterion of the given precision is met, then X k+1 As the optimal solution, f(X k+1 ) as the optimal iteration of the objective function, terminate the calculation; otherwise, go to step 7-6); 7-6) Modification of H according to DFP method k+1 , let k=k+1, go to step 7-2); The DFP method represents the DFP correction method, and the iterative format of this method is Represents the corrected value of the second-order derivative matrix.

2. According to the method for optimizing the cab swing arm guide mechanism based on equivalent stiffness theory as described in claim 1, it is characterized in that: In step 1), the cab suspension system includes a cab model, a cab front suspension model, a cab rear suspension model and a frame model.

3. The method for optimizing the cab swing arm guide mechanism based on equivalent stiffness theory according to claim 1, characterized in that: In step 4), the design variable screening method includes sensitivity analysis method and contribution analysis method.

4. The method for optimizing the cab swing arm guide mechanism based on equivalent stiffness theory according to claim 1, characterized in that: In step 5), the approximate model construction method is to use the response surface method to fit the design space using multiple functions, and the specific fitting formula is: In formula (4), is the objective function; ij are polynomial coefficients; x i x j is the optimization variable.

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