Vehicle power assembly suspension system optimization modeling method based on analytic hierarchy process

Abstract

The invention relates to the technical field of vehicle power assembly suspension system design, in particular to a vehicle power assembly suspension system optimization modeling method based on an analytic hierarchy process, which can overcome different contribution degrees of modal frequencies and decoupling rates of power assembly suspension at various degrees of freedom and remarkably improve the comfort performance of a tracked vehicle. According to the method, an expert assignment method is introduced through an analytic hierarchy process, an expert calculates the weighting coefficient of each degree of freedom according to the importance degree of each degree of freedom and substitutes the weighting coefficient into an optimization target, the power assembly suspension rigidity value closer to engineering practice is obtained, and the accuracy of suspension optimization rigidity can be remarkably improved through calculation, so that the power assembly suspension optimization accuracy is improved. Therefore, the consistency of simulation calculation and engineering practice of the suspension system is improved, and subsequent optimization of the design of parts of the suspension system is facilitated.

Description

Technical Field

[0001] The invention relates to the technical field of vehicle powertrain suspension system design, and in particular to a vehicle powertrain suspension system optimization modeling method based on a hierarchical analysis method. Background Art

[0002] The powertrain suspension system is crucial to the NVH performance of high-speed tracked vehicle systems. The traditional optimization goal of the powertrain suspension system is to maximize the decoupling rate of each degree of freedom, so as to effectively control and attenuate the vibration between the vehicle body and the internal combustion engine. However, in actual working conditions, the modal frequencies and decoupling rates of each degree of freedom of high-speed tracked vehicles on complex and bumpy roads have different contributions, so traditional powertrain suspension modeling is not applicable. Summary of the invention

[0003] In view of this, the present invention proposes a vehicle powertrain suspension system optimization modeling method based on the hierarchical analysis method, which can overcome the different contributions of modal frequencies and decoupling rates of each degree of freedom of the powertrain suspension and significantly improve the comfort performance of tracked vehicles.

[0004] To achieve the above object, the technical solution of the present invention is:

[0005] A vehicle powertrain suspension system optimization modeling method based on the analytic hierarchy process is proposed. The decoupling rate and contribution of the powertrain suspension system are weightedly evaluated by the analytic hierarchy process to obtain the weight coefficient of each degree of freedom. According to the structural characteristics of the vehicle powertrain suspension, a 6-degree-of-freedom dynamic model of the powertrain suspension system is established, and the 6-degree-of-freedom dynamic equations and the output mass matrix, damping matrix, and stiffness matrix are derived and assembled. The natural frequency and vibration mode are solved. The optimization target, optimization variables, and optimization constraints are established, and the weight coefficients of each expert are included in the optimization target to perform optimization calculations on the vehicle powertrain suspension system.

[0006] The specific implementation steps include:

[0007] S1, construct the evaluation modeling process of each degree of freedom of experts based on the analytic hierarchy process;

[0008] S2, conduct dynamic modeling of the powertrain suspension system;

[0009] S3, perform powertrain suspension optimization modeling.

[0010] Among them, the modeling process of constructing expert evaluation of each degree of freedom based on the hierarchical analysis method includes:

[0011] Set the rating levels of the evaluation factors from 1 to 9, let multiple experts rate all the evaluation factors, collect multiple experts' rating factors for each degree of freedom, and attach the initial weights of the ratings;

[0012] According to the scoring results of multiple experts, multiple experts score the importance of each degree of freedom of the powertrain mount, and establish an internal matrix according to the above formula. If multiple experts do not meet the consistency judgment matrix, they can be brought into the equation through the Dirichlet function, and the expert scores that do not meet the consistency judgment matrix are eliminated, and then a comprehensive scoring matrix for multiple experts is established;

[0013] The eigenvalue weight calculation method is used to aggregate and solve multiple expert evaluation data to obtain the weight coefficient of each degree of freedom of the powertrain suspension system.

[0014] Among them, the dynamic modeling of the powertrain suspension system is carried out, and the specific process is as follows:

[0015] Construct the mass matrix M basic parameters, center of mass position (Xc1, Yc1, Zc1), and installation angle of the powertrain rubber suspension system to obtain the powertrain suspension mass matrix;

[0016] The mass matrix K of the powertrain rubber suspension system is constructed to obtain the damping matrix of the powertrain suspension system; the dynamic modeling equation of the powertrain suspension system is obtained, and the natural frequency and main vibration mode of the powertrain suspension system under undamped conditions are calculated by the formula to obtain n eigenvalues. The obtained eigenvalues ​​are substituted into the matrix equation to calculate the corresponding main vibration mode; based on the 6-degree-of-freedom powertrain suspension system model, the energy method is used to analyze the coupling characteristics of the powertrain suspension system.

[0017] Among them, the powertrain suspension optimization modeling is carried out, and the specific steps are as follows:

[0018] Establish the objective function according to the importance of each optimization target and the requirements of energy distribution;

[0019] The frequency constraint range of the powertrain with six degrees of freedom is established according to the decoupling rate and the natural frequency, and the constraint function is established;

[0020] According to the constraint function, a nonlinear constraint function is established;

[0021] Establish the constraints of the powertrain mount stiffness;

[0022] According to the powertrain suspension distribution, the design variables of the suspension system are obtained;

[0023] After determining the optimization objective function and the weight values ​​of each degree of freedom of the expert, the vehicle powertrain suspension system is optimized based on the current constraints and optimization variables.

[0024] Among them, the MATLAB fmincon function is used to perform optimization calculations on the vehicle powertrain suspension system.

[0025] Wherein, the vehicle is a high-speed tracked vehicle.

[0026] Beneficial effects:

[0027] 1. The present invention introduces an expert assignment method through the hierarchical analysis method. Experts calculate the weighted coefficients of each degree of freedom according to the importance of each degree of freedom, and substitute them into the optimization target to obtain a powertrain suspension stiffness value that is closer to engineering practice. After calculation, the accuracy of the suspension optimization stiffness can be significantly improved, thereby improving the consistency between the suspension system simulation calculation and engineering practice, which is helpful for the subsequent optimization of the design of suspension system components.

[0028] 2. In the present invention, the hierarchical analysis method is used to evaluate and score the contribution of each degree of freedom and decoupling rate, which is then converted into a weight system and introduced into the powertrain suspension optimization dynamics model, making it closer to engineering practice and significantly improving the comfort performance of tracked vehicles.

[0029] 3. In the present invention, the suspension optimization target method is used to obtain the powertrain suspension optimization design value that is closer to engineering practice. After calculation, the accuracy of the suspension optimization stiffness can be significantly improved, thereby improving the consistency between the suspension system simulation calculation and engineering practice, which is helpful for the subsequent optimization of the design of the suspension system components.

[0030] 4. The method of the present invention has a judgment standard, and the scoring standard is divided according to the degree of importance. The modeling method of the present invention is applicable to a consistency matrix of scores judged by multiple experts. If the consistency judgment matrix is ​​satisfied, the average value of multiple experts is calculated based on the characteristic root method, and the comprehensive weight value of the powertrain suspension system is calculated. If multiple experts do not satisfy the consistency judgment matrix, the expert scores that do not satisfy the consistency matrix are eliminated. The method is applicable to the powertrain suspension system of high-speed tracked vehicles with any various layout forms. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The present invention is a flow chart of the vehicle powertrain suspension system optimization modeling method based on the hierarchical analysis method. DETAILED DESCRIPTION

[0032] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0033] The present invention discloses a vehicle powertrain suspension system optimization modeling method based on the hierarchical analysis method, which can effectively target the modal frequency and decoupling rate of each degree of freedom on complex bumpy roads. The contribution is difficult to evaluate and needs to be comprehensively evaluated in combination with engineering practice. The method includes the following steps: the decoupling rate and contribution of the powertrain suspension system are weighted evaluated by the experts through the hierarchical analysis method to obtain the weight coefficient of each degree of freedom. Then, according to the structural characteristics of the powertrain suspension of the high-speed tracked vehicle, a 6-degree-of-freedom dynamic model of the powertrain suspension system is established, and the 6-degree-of-freedom dynamic equations and the output mass matrix, damping matrix, and stiffness matrix are derived and assembled; the natural frequency and vibration mode are solved. The optimization target, optimization variables and optimization constraints are established, and then the weight coefficients of each expert are included in the optimization target, so that the optimization target and engineering practice are combined, which more effectively controls and attenuates the vibration between the engine and the frame, and provides a reference for the optimization design modeling method of the powertrain suspension of high-speed tracked vehicles for relevant scientific researchers. The specific steps of the method of the present invention are as follows:

[0034] S1, construct the expert evaluation modeling process for each degree of freedom based on the hierarchical analysis method, including the following steps:

[0035] Set the rating levels of the evaluation factors from 1 to 9, let multiple experts rate all the evaluation factors, collect multiple experts' rating factors for each degree of freedom, and attach the initial weights of the ratings;

[0036] In this embodiment, the expert 1 scoring matrix is:

[0037]

[0038] Expert 2 Rating Matrix:

[0039]

[0040] Expert 3 Rating Matrix:

[0041]

[0042] Expert 4 Rating Matrix:

[0043]

[0044] The calculation method of the CR of the consistency index is specifically as follows:

[0045]

[0046] In the formula, λmax is the maximum eigenvalue of the judgment matrix, m is the number of evaluation factors, and RI is the random consistency index.

[0047] When CR is greater than 0.1, the expert scoring is eliminated. Using the Dirichlet function, the judgment matrix is ​​established as follows:

[0048]

[0049] In the formula, i represents the i-th expert.

[0050] According to the scoring results of multiple experts, multiple experts score the importance of each degree of freedom of the powertrain mount, and establish an internal matrix based on the above formula. If multiple experts do not meet the consistency judgment matrix, they can be brought into the equation through the Dirichlet function, and the expert scores that do not meet the consistency judgment matrix are eliminated, and then the comprehensive scoring matrix of multiple experts is established as follows:

[0051]

[0052] In formula (7),

[0053]

[0054] The eigenvalue weight calculation method is used to aggregate and solve multiple expert evaluation data to obtain the weight coefficient δ of the powertrain suspension system in each degree of freedom.

[0055]

[0056] S2, perform dynamic modeling of the powertrain suspension system. The specific process is as follows:

[0057] The mass matrix M basic parameters, center of mass position (Xc1, Yc1, Zc1), and installation angle of the powertrain rubber suspension system are constructed to obtain the powertrain suspension mass matrix as follows:

[0058]

[0059] Among them, the input powertrain rubber suspension mass m and the rotational inertia product parameters JXX, JYY, JZZ, JXY, JZX, JXY, JYX, JZX, JYX are the inertia products between the main inertia axes of the powertrain suspension and the center of mass coordinate system.

[0060] Construct the mass matrix K of the powertrain rubber suspension system, input the number of suspensions, and the system stiffness matrix of the dynamic stiffness values ​​of one or more suspensions in the x, y, and z directions is:

[0061]

[0062] Among them, the suspension stiffness in the i-th direction is

[0063]

[0064] In formula (11), kui ,k vi ,k wi is the static stiffness of each powertrain mount in three directions in the local mount coordinate system.

[0065] In formula (11), the position transfer matrix is ​​as follows:

[0066]

[0067] In formula (11), the direction cosine matrix of each direction is

[0068]

[0069] Among them. ui , β ui , γ ui It is the angle between the local coordinate system and the global coordinate system.

[0070] The damping matrix of the powertrain suspension system is:

[0071]

[0072] In formula (15), the suspension damping in the i-th direction is

[0073]

[0074] In formula (15), the velocity transfer matrix in the i-th direction is

[0075]

[0076] Therefore, the dynamic modeling equation of the powertrain suspension system is:

[0077]

[0078] Where, is the generalized force matrix acting on the system.

[0079] F=(F x .F y ,F z ,M x .M y ,M z ) T (19)

[0080] In formula (19), q = (x, y, z, θ x ,θ y ,θz) T is the generalized coordinate of the system; is the generalized velocity of the system; is the generalized acceleration of the system.

[0081] The natural frequencies and principal vibration modes of the powertrain mounting system under the condition of no damping are calculated by formulas, and the form of the solution of the equation is (where A is the vibration amplitude), and the simplified formula is:

[0082] (K - w 2 n M)A = 0 (20)

[0083] where H=(K - W 2 n ) is called the characteristic matrix. The necessary and sufficient condition for the existence of a non - zero solution of this matrix equation is that the determinant |H| of the characteristic matrix is 0, that is

[0084] |K - w 2 n M| = 0 (21)

[0085] where, solving this matrix equation gives n values of W 2 n which are called the eigenvalues of the system. Usually, the n eigenvalues of the matrix equation are not equal to each other. Therefore, they are arranged in ascending order as 0 < w1 < w2 < w3 < … < wn, which are respectively called the first - order, second - order, third - order … nth - order natural frequencies. Substituting these obtained eigenvalues into the matrix equation above, the corresponding principal vibration modes are calculated

[0086] Based on the 6 - degree - of - freedom powertrain mounting system model, the formula for analyzing the coupling characteristics of the powertrain mounting system using the energy method is as follows

[0087]

[0088] where, w i is the i - th natural frequency of the mounting system, mkl is the element in the k - th row and l - th column of the mass matrix M, ψ i is the principal vibration mode at the i - th natural frequency, where i, j, k all take values from 1 to 6. T k is the kinetic energy of the k - th degree of freedom at the i - th mode, and T T is the total kinetic energy of the system.

[0089] S3, for powertrain mounting optimization modeling, the specific steps are as follows:

[0090] According to the importance of each optimization objective and the requirements of energy distribution, establish the objective function

[0091]

[0092] where, δ i is the weight system of the i - th mode, and max(T pi ) is that the energy decoupling rate of the i - th mode reaches the maximum value.

[0093] The frequency constraint range of the powertrain with six degrees of freedom is established according to the decoupling rate and the natural frequency, and the constraint function is established.

[0094] f ai ≤w i ≤f bi (twenty four)

[0095] Among them, f ai Indicates the minimum natural frequency range of the i-th order powertrain mount. bi Represents the maximum natural frequency range of the i-th order powertrain. According to the above formula, the nonlinear constraint function is established as follows:

[0096] C1=w1-f b1

[0097] C2=w2-f b2

[0098] C3=w3-f b3

[0099] C4=w4-f b4

[0100] C5=w5-f b5

[0101] C6=w6-f b6

[0102] C7=f a1 -w1

[0103] C8=f a2 -w2

[0104] C9=f a3 -w3

[0105] C 10 =f a4 -w4

[0106] C 11 =f a5 -w5

[0107] C 12 =f a6 -w6 (25)

[0108] Establish the constraints for the powertrain mount stiffness.

[0109] k ai ≤k ui ≤k bi

[0110] k ci ≤kvi ≤k di

[0111] k ei ≤k wi ≤k fi (26)

[0112] In the formula, k ai , k ci , k ei represents the minimum static stiffness value of the i-th order powertrain mount in the local coordinate system of the mount, k bi , k di ,k fi Represents the maximum static stiffness value of the i-th order powertrain mount.

[0113] According to the powertrain mount distribution, the design variables of the mount system are:

[0114] X=[k u1 ,k v1 ,k w1 ,k u2 ,k v2 ,k w2 ,k u3 ,k v3 ,k w3 …] T (27)

[0115] After determining the optimization objective function and the weight values ​​of each degree of freedom of the expert, based on the current constraints and optimization variables, the MATLAB fmincon function is used to optimize the powertrain suspension system of the high-speed tracked vehicle.

[0116] The method of the present invention is illustrated by the stiffness optimization design process of the powertrain suspension system of a high-speed tracked vehicle. There are three suspensions between the body and the engine of a high-speed tracked vehicle, namely the rear suspension and two left and right suspensions. The experts divide the degrees of freedom of the powertrain suspension according to the importance level and the scoring standard is shown in Table 1. The expert quantitative evaluation results are shown in Table 2.

[0117] Table 1. Hierarchy mechanism in expert quantitative evaluation

[0118] Equally important Slightly important Clearly important Strongly important Extremely important expert 1 3 5 7 9

[0119] 2, 4, 6, 8 are the median values ​​of the above two adjacent judgments.

[0120] Table 2 Expert scoring table for each degree of freedom of tracked vehicle powertrain suspension

[0121]

[0122] According to the expert scoring of each degree of freedom, the weight value is calculated as shown in Table 3.

[0123] Table 3 Weight values ​​of modal frequencies and decoupling rates of each degree of freedom of tracked vehicles

[0124]

[0125] According to the mass inertia parameters of a high-speed tracked vehicle powertrain suspension system, the input parameters are as follows in Table 4:

[0126] Table 4 Powertrain suspension system mass and inertia parameters

[0127]

[0128] The powertrain suspension position parameters of the high-speed tracked vehicle are shown in Table 5-7.

[0129] Table 5 Powertrain rear suspension position parameters

[0130]

[0131] Table 6 Powertrain left suspension installation angle

[0132]

[0133] Table 7 Powertrain right suspension installation angle

[0134]

[0135] Set frequency constraints: frequency distribution range of the powertrain mount in six directions of the vehicle, decoupling rate and other target conditions, i is the number of engine cylinders, 6; is the number of strokes, and the ignition frequency is calculated to be 32.5HZ. According to vibration theory, when the ratio of the excitation frequency to the system natural frequency is greater than 1.414, the mount system can achieve vibration isolation, so the highest order natural frequency of the mount system should be less than 23Hz.

[0136] For the powertrain suspension system of high-speed tracked vehicles, the natural frequencies of each order of the system need to differ by 1 to 2 Hz, and the system modal frequencies should be 5 Hz higher than the overall stiffness modal frequencies and the road excitation frequencies. The Z-axis modal frequency of the system should avoid the most sensitive range of 4-8 Hz for the human body, and avoid resonance with rolling, and is generally controlled at 8-17 Hz; the forward and backward modal vibration of the system X-axis is generally very small, and only has a large transient excitation during emergency braking or acceleration. To avoid a large position in this direction, the X-axis frequency is generally 5-17 Hz; the Y-axis lateral vibration is mainly considered to interfere with the frame when turning and avoid resonance with the yaw motion, and the frequency is controlled at 6-14 Hz; the Rx-axis roll vibration is the main excitation generated by the inline 6-cylinder 4-stroke, and the vibration isolation requirements are high, but it cannot be too soft, and is generally controlled at 6-17 Hz; the RY-axis pitch vibration is generally controlled at 5-17 Hz; the Rz-axis yaw vibration should avoid the steering wheel angle excitation, and is generally controlled at 8-17 Hz. The frequency interval of each mode of 6 degrees of freedom is preferably ≥ 1HZ, so the frequency distribution range of the powertrain suspension of high-speed tracked vehicles according to road conditions is shown in Table 8 below.

[0137] Table 8 Frequency distribution range of high-speed tracked vehicle powertrain suspension in the vehicle direction

[0138]

[0139] Set stiffness constraints: To determine the dynamic stiffness value range of one or more suspensions in the X, Y and / or Z directions, and analyze and process to obtain multiple stiffness values ​​of each suspension in the X, Y and Z directions, let the dynamic stiffness values ​​of the ith suspension in the X, Y and Z directions be kix, kiy and kiz respectively. Since the left and right side suspensions are located on the left and right sides of the engine and the rear suspension is located in the middle of the rear part of the engine, it is assumed that the three suspensions are the same, so the stiffness distribution range of each suspension can be defined according to the empirical values ​​in Table 9 below.

[0140] Table 9 Stiffness distribution range of high-speed tracked vehicle powertrain suspension in the vehicle direction

[0141]

[0142] In the powertrain system of the high-speed tracked vehicle, the stiffness values ​​of each suspension direction are combined by the method of step 3 and calculated to meet the optimization objectives and constraints. The specific calculation process will not be described in detail. The results of the natural frequency and decoupling rate of the powertrain suspension system of the high-speed tracked vehicle before and after optimization are shown in Table 10.

[0143] Table 10 Results of the natural frequency and decoupling rate of the powertrain suspension system of high-speed tracked vehicles before and after optimization

[0144]

[0145] Table 10 shows that the comparison of the decoupling rate of the powertrain mount before and after optimization shows that the decoupling rate of the powertrain mount in the lateral Y direction before optimization is 87.638%, and the decoupling rate of the powertrain mount in the lateral Y direction after optimization is 92.72%, which significantly improves the vibration isolation performance. The decoupling rate of each degree of freedom after optimization reaches more than 90%, and the vibration isolation effect of the optimized mount system is better.

[0146] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle powertrain suspension system optimization modeling method based on hierarchical analysis method, characterized in that: Through the hierarchical analysis method, the decoupling rate and contribution of the experts to the powertrain suspension system are weightedly evaluated to obtain the weight coefficient of each degree of freedom; according to the structural characteristics of the vehicle powertrain suspension, a 6-degree-of-freedom dynamic model of the powertrain suspension system is established, and the six-degree-of-freedom dynamic equations and the output mass matrix, damping matrix, and stiffness matrix are derived and assembled; the natural frequency and vibration mode are solved; the optimization goal, optimization variables and optimization constraints are established, and the weighted coefficients of each expert are included in the optimization goal to perform optimization calculations on the vehicle powertrain suspension system.

2. The method according to claim 1, characterized in that The specific implementation steps include: S1, construct the evaluation modeling process of each degree of freedom of experts based on the analytic hierarchy process; S2, conduct dynamic modeling of the powertrain suspension system; S3, perform powertrain suspension optimization modeling.

3. The method according to claim 2, characterized in that The modeling process of constructing expert evaluation of each degree of freedom based on the hierarchical analysis method includes: Set the rating levels of the evaluation factors from 1 to 9, let multiple experts rate all the evaluation factors, collect multiple experts' rating factors for each degree of freedom, and attach the initial weights of the ratings; According to the scoring results of multiple experts, multiple experts score the importance of each degree of freedom of the powertrain mount, and establish an internal matrix according to the above formula. If multiple experts do not meet the consistency judgment matrix, they can be brought into the equation through the Dirichlet function, and the expert scores that do not meet the consistency judgment matrix are eliminated, and then a comprehensive scoring matrix for multiple experts is established; The eigenvalue weight calculation method is used to aggregate and solve multiple expert evaluation data to obtain the weight coefficient of each degree of freedom of the powertrain suspension system.

4. The method according to claim 2 or 3, characterized in that Carry out dynamic modeling of powertrain suspension system. The specific process is as follows: Construct the mass matrix M basic parameters, center of mass position (Xc1, Yc1, Zc1), and installation angle of the powertrain rubber suspension system to obtain the powertrain suspension mass matrix; Construct the mass matrix K of the powertrain rubber suspension system and obtain the damping matrix of the powertrain suspension system; The dynamic modeling equation of the powertrain suspension system is obtained, and the natural frequency and main vibration mode of the powertrain suspension system under undamped conditions are calculated through the formula to obtain n eigenvalues. The obtained eigenvalues ​​are substituted into the matrix equation to calculate the corresponding main vibration mode; based on the six-degree-of-freedom powertrain suspension system model, the energy method is used to analyze the coupling characteristics of the powertrain suspension system.

5. The method according to claim 4, characterized in that The specific steps for powertrain suspension optimization modeling are as follows: Establish the objective function according to the importance of each optimization target and the requirements of energy distribution; The frequency constraint range of the powertrain with six degrees of freedom is established according to the decoupling rate and the natural frequency, and the constraint function is established; According to the constraint function, a nonlinear constraint function is established; Establish the constraints of the powertrain mount stiffness; According to the powertrain suspension distribution, the design variables of the suspension system are obtained; After determining the optimization objective function and the weight values ​​of each degree of freedom of the expert, the vehicle powertrain suspension system is optimized based on the current constraints and optimization variables.

6. The method according to claim 5, characterized in that The MATLAB fmincon function is used to optimize the vehicle powertrain suspension system.

7. The method according to claim 2, 3, 5 or 6, characterized in that: The vehicle is a high-speed tracked vehicle.

Images