A multivariable multi-objective hierarchical optimization method for engine suspension system

Abstract

A kind of multivariable multi-objective hierarchical optimization method of engine suspension system can effectively improve the optimization efficiency and optimization precision of engine suspension system, and form a compromise optimization scheme that is satisfactory to each target.The steps are as follows:1.establishing a rigid-flexible coupling multibody dynamics model of engine suspension system;2.dynamics simulation and model calibration of engine suspension system;3.design variable parameterization and optimization target weight ordering;4.simulation optimization analysis of engine suspension system;5.effect evaluation of optimization scheme.The present application comprehensively uses rigid-flexible coupling dynamics principle and finite element theory, establishes a dynamics model of engine suspension system based on the coexistence of rigid body and flexible body, and uses multivariable multi-objective hierarchical optimization method to solve the problems existing in the optimization process of existing engine suspension system, such as low mathematical model precision, low optimization efficiency, and difficulty in meeting multiple targets simultaneously, and the optimization method of the present application has high applicability and operability.

Description

Technical Field

[0001] This invention relates to the field of dynamic simulation and optimization of engine mounting systems, and in particular to a multivariable, multi-objective hierarchical optimization method for engine mounting systems. Background Technology

[0002] Engine vibration is the primary excitation source causing vehicle body vibration, and the engine mounting system is a key device for attenuating engine vibration. A well-designed engine mounting system can achieve excellent vibration and noise reduction effects and significantly improve vehicle comfort. Engine mounting system optimization design is a multi-variable, multi-objective optimization problem. For a three-mounted longitudinal engine, the optimization variables include the X, Y, and Z-direction stiffness and damping of the front mount, and the X, Y, and Z-direction stiffness and damping of the rear mount, totaling 12 variables. The optimization objectives include the static compression of the front and rear suspensions in the Y and Z directions; the natural frequencies of the engine mount system in the X, Y, Z, Rx, Ry, and Rz directions; the energy decoupling rates of the engine mount system in the X, Y, Z, Rx, Ry, and Rz directions; and the vibration transmissibility of the front and rear suspensions in the Y and Z directions, totaling 20 optimization objectives. Currently, commonly used multi-objective optimization methods transform multi-objective optimization problems into single-objective optimization problems. Among these, the principal objective method and the linear weighted method are widely used multi-objective optimization methods. The primary objective method selects the most important objective from multiple objectives as the optimization objective, and the remaining objectives serve as constraints. Each sub-objective is constrained by a boundary value. This method is simple and easy to implement, but when the boundary values ​​of each sub-objective are set inappropriately, problems such as non-convergence of optimization calculations or empty solutions may occur. The linear weighted method sets weighting coefficients according to the importance of each objective, transforming the multi-objective problem into a single-objective problem for analysis. It is relatively simple to implement, but there is a problem that the weights of each objective are difficult to determine, and it cannot guarantee the quality of the optimization results.

[0003] The multiple optimization objectives of the engine mounting system are contradictory and mutually constrained, making it difficult for the established multi-objective optimization function to fully and accurately reflect the correspondence between multiple variables and multiple objectives, thus complicating the optimization analysis of the engine mounting system. At the same time, multivariate multi-objective optimization requires a lot of computing resources, has a long iteration calculation time, low computational efficiency, and the optimization results are difficult to meet the requirements of each objective at the same time. In fact, the improvement of some objectives may even lead to the reduction of other objectives.

[0004] The existing technical solutions are as follows:

[0005] Technical comparison of application number: CN201510432000.3, patent title "An optimization method for engine mounting system considering dynamic stiffness and dynamic damping":

[0006] The technical solution of "An Optimization Method for Engine Mounting Systems Considering Dynamic Stiffness and Dynamic Damping" uses only the vertical static stiffness of the mount as the design variable and only the vertical vibration transmissibility as the optimization objective, making it a typical single-objective, single-variable optimization problem. The technical solution of this paper uses the longitudinal stiffness, lateral stiffness, vertical stiffness, longitudinal damping, lateral damping, and vertical damping of the mount as design variables; the optimization objectives are the static compression, natural frequency, energy decoupling rate, and vibration transmissibility of the mount system, making it a typical multi-objective, multi-variable optimization problem. Furthermore, the "An Optimization Method for Engine Mounting Systems Considering Dynamic Stiffness and Dynamic Damping" uses a multi-stiffness dynamic model, with the data measurement point being the mount's center of mass. This paper uses a rigid-flexible coupled dynamic model, with data measurement points at the upper and lower ends of the left mount, right mount, and rear mount, as well as the mount's center of mass. Therefore, there are significant differences between the two solutions in terms of optimization methods, mount system dynamic modeling methods, and data acquisition and analysis methods.

[0007] Technical comparison of application number: CN201810817059.8, patent title "An Optimization Method for Engine Powertrain Mounting System":

[0008] The technical solution of "An Optimization Method for Engine Powertrain Mounting System" uses the power transmission from the mounting system to the vehicle body as the optimization variable, the mounting stiffness as the optimization objective, and employs a single-objective optimization iterative algorithm. The technical solution in this paper uses the longitudinal stiffness, lateral stiffness, vertical stiffness, longitudinal damping, lateral damping, and vertical damping of the mounting system as optimization variables; and the static compression, natural frequency, energy decoupling rate, and vibration transmissibility of the mounting system as optimization objectives, employing a multi-objective hierarchical optimization iterative algorithm. In terms of simulation methods, "An Optimization Method for Engine Powertrain Mounting System" obtains the frequency response characteristics of the mounting system by solving the system vibration differential equations. In terms of simulation methods, this paper directly performs dynamic simulations on the mounting model to obtain the static compression, natural frequency, energy decoupling rate, and vibration transmissibility of the mounting system. Furthermore, the equivalent excitation force in "An Optimization Method for Engine Powertrain Mounting System" is obtained through actual vehicle testing and is highly dependent on test data; the excitation force in this paper is obtained by calculating through the establishment of an engine numerical model.

[0009] Technical comparison of application number: CN201610621742.5, patent title "Powertrain Mounting System Parameter Optimization Method":

[0010] The technical solution of the "Powertrain Mount System Parameter Optimization Method" is to establish a mathematical model of the mount system, using the three-dimensional stiffness of the mount as the optimization variable and the natural frequency and decoupling rate of the mount as the optimization objectives. The technical solution of this paper is to establish a rigid-flexible coupled dynamic model of the mount system, using the three-dimensional stiffness and three-dimensional damping of the mount as optimization variables, and the static compression, natural frequency, energy decoupling rate, and vibration transmissibility of the mount system as optimization objectives. In terms of optimization methods, the "Powertrain Mount System Parameter Optimization Method" uses a traditional multivariate multi-objective optimization algorithm. This paper uses a multi-objective hierarchical iterative optimization algorithm, which differs from existing multi-objective optimization methods in that it ranks the optimization objectives of the mount system by weight, transforming the complex multi-objective multivariate problem into a single-objective multivariate problem.

[0011] Technical comparison of application number: CN201410065485.2, patent title "A Multi-Objective Optimization Method for an Engine Mounting System":

[0012] The technical solution of "A Multi-Objective Optimization Method for an Engine Mount System" establishes a multi-rigid-body dynamic model for the mount system dynamics. The technical solution in this paper establishes a rigid-flexible coupled dynamic model for the mount system dynamics, considering the influence of mount bracket deformation on the system's dynamic response. The original "Multi-Objective Optimization Method for an Engine Mount System" aims to maximize the vertical decoupling rate and minimize the sum of the dynamic reaction forces in all four directions of the mounts, using the three-dimensional stiffness of the mount as the optimization variable. This paper uses the static compression, natural frequency, energy decoupling rate, and vibration transmissibility of the mount system as optimization objectives, using the three-dimensional stiffness and three-dimensional damping of the mount as optimization variables. The original "Multi-Objective Optimization Method for an Engine Mount System" employs a non-dominated sorting genetic algorithm. The difference between this paper's multi-objective hierarchical optimization iterative algorithm and existing multi-objective optimization methods lies in the weighted sorting of the optimization objectives of the mount system, transforming the complex multi-objective, multi-variable problem into a single-objective, multi-variable problem.

[0013] Technical comparison of application number: CN202111426073.3, patent title "A method for correcting a finite element model of an engine mount":

[0014] The technical solution of "A Method for Correcting the Finite Element Model of an Engine Mount Bracket" establishes a finite element model of the mount bracket; the technical solution of this paper establishes a rigid-flexible coupled dynamic model of the mount system, and the two are significantly different. "A Method for Correcting the Finite Element Model of an Engine Mount Bracket" calculates the structural modes of the mount bracket, belonging to the field of structural mechanics; this paper analyzes the dynamic response of the mount system, belonging to the field of dynamics. "A Multi-Objective Optimization Method for an Engine Mount System" optimizes the correction parameters of the finite element model of the mount bracket and employs an intelligent optimization algorithm; this paper optimizes the entire mount system and employs a multi-objective hierarchical iterative optimization algorithm.

[0015] To address the problems of low mathematical model accuracy, low optimization efficiency, and difficulty in simultaneously satisfying multiple objectives in the existing optimization process of engine mounting systems, a multivariable, multi-objective hierarchical optimization method for engine mounting systems is proposed. Summary of the Invention

[0016] To overcome the shortcomings of existing technologies, this invention proposes a multivariable, multi-objective hierarchical optimization method for engine mounting systems, which solves the problems of low mathematical model accuracy, low optimization efficiency, and difficulty in simultaneously satisfying multiple objectives in the optimization process of existing engine mounting systems.

[0017] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0018] A multivariable, multi-objective hierarchical optimization method for engine mounting systems, comprising the following steps:

[0019] (1) Establish a rigid-flexible coupled multibody dynamics model of the engine mounting system;

[0020] (2) Dynamic simulation and model calibration of engine mounting system;

[0021] (3) Parameterization of design variables and ranking of optimization target weights;

[0022] Step (3) involves parameterizing the design variables and ranking the optimization target weights, including the following steps:

[0023] 1) Establish parameterized models of front suspension stiffness in the X, Y, and Z directions, and establish parameterized models of front suspension damping in the X, Y, and Z directions;

[0024] 2) Establish parameterized models of the rear suspension stiffness in the X, Y, and Z directions, and establish parameterized models of the rear suspension damping in the X, Y, and Z directions;

[0025] 3) Establish optimization objectives for the engine mount system, including the static compression of the mount system, the natural frequency of the engine mount system, the energy decoupling rate of the engine mount system, and the vibration transmission rate of the engine mount system;

[0026] 4) Rank the optimization objectives of the engine mounting system by weight;

[0027] (4) Simulation optimization analysis of engine mounting system;

[0028] The simulation optimization analysis of the engine mounting system described in step (4) includes the following steps:

[0029] 1) Based on the optimization objective with weight 1, the front suspension stiffness range is obtained through simulation optimization. ~ , ~ , ~ ), front suspension damping range ( ~ , ~ , ~ Rear suspension stiffness range ( ~ , ~ , ~ ), rear suspension damping range ( ~ , ~ , ~ );

[0030] 2) Within the optimization result range of weight 1, based on the optimization objective of weight 2, the front suspension stiffness range is obtained through simulation optimization. ~ , ~ , ~ ), front suspension damping range ( ~ , ~ , ~ Rear suspension stiffness range ( ~ , ~ , ~ ), rear suspension damping range ( ~ , ~ , ~ );

[0031] 3) Within the optimization result range of weight 2, based on the optimization objective of weight 3, the front suspension stiffness range is obtained through simulation optimization. ~ , ~ , ~ ), front suspension damping range ( ~ , ~ , ~ Rear suspension stiffness range ( ~ , ~ , ~ ), rear suspension damping range ( ~ , ~ , ~ );

[0032] 4) Within the optimization result range of weight 3, and based on the optimization objective of weight 4, the front suspension stiffness is obtained through simulation optimization. , , ), front suspension damping ( , , Rear suspension stiffness ( , , ), rear suspension damping ( , , );

[0033] (5) Evaluation of the effectiveness of the optimization scheme.

[0034] As a further improvement of the present invention, the establishment of the rigid-flexible coupling multibody dynamics model of the engine mounting system in step (1) includes the following steps:

[0035] 1) Extract the hard point coordinates of the front and rear mounts from the 3D model of the engine mount system, and establish the spatial position coordinates of the front and rear mounts in ADAMS software;

[0036] 2) Calculate the engine's mass, moment of inertia, and center of mass coordinates, and establish an engine dynamics model in ADAMS software;

[0037] 3) Establish a finite element model of the engine mount, calculate the mount modes, and import the engine mount modal neutral file into ADAMS to establish a flexible body model of the engine mount;

[0038] 4) Use BUSHING elements to establish the front and rear engine mounts, add mass properties of the components, set constraints, and establish a rigid-flexible coupling dynamic model of the engine mount system.

[0039] 5) Establish a mathematical model of engine excitation and apply the engine excitation to the rigid-flexible coupling dynamic model of the engine mounting system.

[0040] As a further improvement to the present invention, the dynamic simulation and model calibration of the engine mounting system described in step (2) includes the following steps:

[0041] 1) Perform degree of freedom and static balance simulations on the established rigid-flexible coupled dynamic model of the engine mounting system to verify the accuracy of the model;

[0042] 2) Perform static simulations of the established rigid-flexible coupled dynamic model of the engine mount system in a gravity field to verify the static compression of the front and rear mounts.

[0043] 3) Perform constrained modal simulations on the established rigid-flexible coupled dynamic model of the engine mounting system to verify the natural frequencies of the model;

[0044] 4) The established rigid-flexible coupling dynamic model of the engine mounting system is dynamically simulated under engine excitation to verify the vibration transmissibility of the model.

[0045] As a further improvement of the present invention, the inherent frequencies of the engine mounting system mentioned in step (3) include the inherent frequencies in the X, Y, Z, Rx, Ry and Rz directions.

[0046] As a further improvement of the present invention, the energy decoupling rate of the engine mounting system mentioned in step (3) includes the energy decoupling rates in the X, Y, Z, Rx, Ry and Rz directions.

[0047] As a further improvement of the present invention, the vibration transmission rate of the engine mount system mentioned in step (3) refers to the ratio of the vibration of the active end to the vibration of the passive end of the front mount and the rear mount.

[0048] As a further improvement to the present invention, the front suspension stiffness mentioned in step (4) is... , , ), front suspension damping ( , , Rear suspension stiffness ( , , ), rear suspension damping ( , , The optimal compromise solution satisfies all optimization objectives.

[0049] As a further improvement of the present invention, the evaluation of the effect of the optimization scheme described in step (5) includes the following steps:

[0050] (1) Reset the stiffness and damping of the front and rear suspensions according to the optimal compromise scheme;

[0051] (2) Perform static simulation on the optimized rigid-flexible coupling dynamic model of the engine mount system in the gravitational field, calculate the static compression of the front mount and the rear mount, and compare it with the target value;

[0052] (3) Modal simulation was performed on the optimized rigid-flexible coupling dynamic model of the engine mount system, and the calculated natural frequencies of the engine mount system were compared with the target values;

[0053] (4) Perform energy decoupling simulation on the optimized rigid-flexible coupling dynamic model of the engine mount system, and compare the calculated energy decoupling rate of the engine mount system with the target value;

[0054] (5) Perform dynamic simulation on the optimized rigid-flexible coupling dynamic model of the engine mount system, and compare the calculated vibration transmission rates in the Y and Z directions of the front and rear mounts with the target values.

[0055] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0056] This invention provides a multivariable, multi-objective hierarchical optimization method for engine mounting systems, which solves the problems of low mathematical model accuracy, low optimization efficiency, and difficulty in simultaneously satisfying multiple objectives in the existing engine mounting system optimization process. Attached Figure Description

[0057] Figure 1 This invention provides a multivariable, multi-objective hierarchical optimization method and flowchart for engine mounting systems.

[0058] Figure 2 This is a schematic diagram of the rigid-flexible coupling dynamic model of the engine mounting system based on the present invention;

[0059] Explanation of reference numerals in the attached figures

[0060] 1. Engine; 2. Front bracket; 3. Front mount; 4. Rear bracket; 5. Rear mount. Detailed Implementation

[0061] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0062] A detailed explanation of a multivariable, multi-objective hierarchical optimization method for engine mounting systems is provided.

[0063] The main purpose of this invention is to address the problems of low mathematical model accuracy, low optimization efficiency, and difficulty in simultaneously satisfying multiple objectives in the current optimization process of engine mount systems by analyzing the current state of existing engine mount system optimization methods. This invention provides a multi-variable, multi-objective hierarchical optimization method for engine mount systems to solve the above problems, effectively improving the optimization efficiency and reliability of the optimization results.

[0064] See Figure 1 The present invention discloses a multivariable, multi-objective hierarchical optimization method for engine mounting systems, comprising the following steps:

[0065] Establish a rigid-flexible coupled multibody dynamics model of the engine mounting system.

[0066] See Figure 2 The steps for establishing a rigid-flexible coupled multibody dynamics model of the engine mounting system are as follows:

[0067] Calculate the engine's mass, moment of inertia, and center of mass coordinates, and establish an engine dynamics model in ADAMS software;

[0068] Establish a finite element model of the engine mount, calculate the mount modes, and import the engine mount modal neutral file into ADAMS to establish a flexible body model of the engine mount.

[0069] The front and rear engine mounts are established using BUSHING elements, and the mass properties of the components are added. Constraints are set to establish a rigid-flexible coupling dynamic model of the engine mount system.

[0070] Establish a mathematical model of engine excitation and apply the engine excitation to the rigid-flexible coupling dynamic model of the engine mount system. The dynamic simulation and model calibration of the engine mount system include the following steps:

[0071] The established rigid-flexible coupled dynamic model of the engine mounting system was subjected to degree of freedom and static balance simulation to verify the accuracy of the model.

[0072] The established rigid-flexible coupling dynamic model of the engine mount system was subjected to static simulation in a gravity field to verify the static compression of the front and rear mounts. The calibration results are shown in Table 1.

[0073] Constrained modal simulations were performed on the established rigid-flexible coupled dynamic model of the engine mounting system to verify the natural frequencies of the model. The calibration results are shown in Table 2.

[0074] The established rigid-flexible coupling dynamic model of the engine mounting system was dynamically simulated under engine excitation to verify the vibration transmissibility of the model. The calibration results are shown in Table 3.

[0075] Table 1. Calibration results of static compression of suspension.

[0076]

[0077] Table 2 Calibration results of the natural frequency of the suspension system

[0078]

[0079] Table 3. Calibration results of suspension vibration transmissibility

[0080]

[0081] The simulation data in Tables 1 to 3 all show a greater than 90% agreement with the experimental data, demonstrating the accuracy of the rigid-flexible coupling dynamic model of the engine mounting system established in this invention. Moreover, the model has high reliability, applicability, and operability.

[0082] The design of variable parameterization and optimization of target weight ranking includes the following steps:

[0083] Establish parameterized models of front suspension stiffness in the X, Y, and Z directions, and establish parameterized models of front suspension damping in the X, Y, and Z directions;

[0084] A parametric model of the stiffness of the rear suspension in the X, Y, and Z directions is established, as well as a parametric model of the damping of the rear suspension in the X, Y, and Z directions.

[0085] Optimization targets for the engine mount system were established, including the static compression of the mount system (2mm-3mm), the natural frequency of the engine mount system (5 Hz-16Hz), the energy decoupling rate of the engine mount system (X-direction >70%, Y-direction >70%, Z-direction >85%, Rx >85%, Ry >70%, Rz >70%), and the vibration transmission rate of the engine mount system (front mount <15%, rear mount <15%).

[0086] The weights of the optimization objectives of the engine mount system are ranked as follows: weight 1 is the static compression of the mount, weight 2 is the natural frequency of the engine mount system, weight 3 is the energy decoupling rate of the engine mount system, and weight 4 is the vibration transmission rate of the engine mount system.

[0087] The simulation optimization analysis of the engine mounting system includes the following steps:

[0088] Based on the optimization objective of static compression of the suspension with weight 1, the optimization results are as follows: front suspension stiffness range (151 N / mm~312 N / mm, 126 N / mm~267 N / mm, 412 N / mm~733 N / mm), front suspension damping range (0.11~0.19, 0.10~0.23, 0.17~0.35), rear suspension stiffness range (132 N / mm~213 N / mm, 67 N / mm~126 N / mm, 308 N / mm~467 N / mm), and rear suspension damping range (0.16~0.28, 0.12~0.23, 0.19~0.31).

[0089] Within the optimization range of weight 1, and based on the optimization objective of the engine mount system's natural frequency of weight 2, the optimization results are as follows: front mount stiffness range (165 N / mm~283 N / mm, 131 N / mm~215 N / mm, 467 N / mm~706 N / mm), front mount damping range (0.12~0.20, 0.11~0.24, 0.18~0.33), rear mount stiffness range (139 N / mm~194 N / mm, 78 N / mm~108 N / mm, 312 N / mm~417 N / mm), and rear mount damping range (0.18~0.26, 0.14~0.22, 0.21~0.29).

[0090] Within the optimization results of weight 2, based on the optimization target of energy decoupling rate of engine mount system of weight 3, the optimization results are as follows: front mount stiffness range (196 N / mm~244 N / mm, 143 N / mm~173 N / mm, 495 N / mm~566 N / mm), front mount damping range (0.15~0.18, 0.13~0.16, 0.21~0.25), rear mount stiffness range (142 N / mm~175 N / mm, 83 N / mm~96 N / mm, 336 N / mm~366 N / mm), rear mount damping range (0.19~0.23, 0.16~0.19, 0.23~0.26);

[0091] Within the optimization results of weight 3, and based on the optimization target of vibration transmissibility of engine mount system of weight 4, the optimization results are as follows: front mount stiffness (210 N / mm, 150 N / mm, 550 N / mm), front mount damping (0.16, 0.15, 0.23), rear mount stiffness (160 N / mm, 90 N / mm, 350 N / mm), and rear mount damping (0.22, 0.17, 0.25).

[0092] The optimization result based on weight 4 is the optimal compromise, which can simultaneously satisfy all optimization objectives.

[0093] The evaluation of the effectiveness of the optimization plan includes the following steps:

[0094] The stiffness and damping of the front and rear suspensions were reset according to the optimal compromise.

[0095] Static simulation was performed on the optimized rigid-flexible coupling dynamic model of the engine mount system in a gravitational field. The static compression of the front and rear mounts was calculated and compared with the target value. The evaluation results are shown in Table 4.

[0096] Modal simulation was performed on the optimized rigid-flexible coupling dynamic model of the engine mount system, and the calculated natural frequencies of the engine mount system were compared with the target values. The evaluation results are shown in Table 5.

[0097] Energy decoupling simulation was performed on the optimized rigid-flexible coupling dynamic model of the engine mount system, and the calculated energy decoupling rate of the engine mount system was compared with the target value. The evaluation results are shown in Table 6.

[0098] Dynamic simulation was performed on the optimized rigid-flexible coupling dynamic model of the engine mount system, and the calculated vibration transmission rates in the Y and Z directions of the front and rear mounts were compared with the target values. The evaluation results are shown in Table 7.

[0099] Table 4 Evaluation Results of Suspension Static Compression

[0100]

[0101] Table 5 Evaluation results of the natural frequency of the suspension system

[0102]

[0103] Table 6 Evaluation Results of Energy Decoupling Rate of Suspension System

[0104]

[0105] Table 7 Evaluation Results of Suspension Vibration Transmissibility

[0106]

[0107] The simulation data in Tables 4 to 7 all meet the requirements of the various optimization objectives of the engine mount system, proving that a multivariate, multi-objective hierarchical optimization method for engine mount systems can solve the problems of low mathematical model accuracy, low optimization efficiency, and difficulty in simultaneously satisfying multiple objectives in the current optimization process of engine mount systems. This improves the credibility of the simulation optimization results and has high reliability, applicability, and operability.

[0108] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any modifications or equivalent changes made based on the technical essence of the present invention shall still fall within the scope of protection claimed by the present invention.

Claims

1. A multivariable, multi-objective hierarchical optimization method for an engine mounting system, characterized in that, The specific steps are as follows: (1) Establish a rigid-flexible coupled multibody dynamics model of the engine mounting system; Step (1) involves establishing a rigid-flexible coupled multibody dynamics model of the engine mounting system, which includes the following steps: 1) Extract the hard point coordinates of the front and rear mounts from the 3D model of the engine mount system, and establish the spatial position coordinates of the front and rear mounts in ADAMS software; 2) Calculate the engine's mass, moment of inertia, and center of mass coordinates, and establish an engine dynamics model in ADAMS software; 3) Establish a finite element model of the engine mount, calculate the mount modes, and import the engine mount modal neutral file into ADAMS to establish a flexible body model of the engine mount; 4) Use BUSHING elements to establish the front and rear engine mounts, add mass properties of the components, set constraints, and establish a rigid-flexible coupling dynamic model of the engine mount system. 5) Establish a mathematical model of engine excitation and apply the engine excitation to the rigid-flexible coupling dynamic model of the engine mounting system; (2) Dynamic simulation and model calibration of engine mounting system; (3) Parameterization of design variables and ranking of optimization target weights; Step (3) involves parameterizing the design variables and ranking the optimization target weights, including the following steps: 1) Establish parameterized models of front suspension stiffness in the X, Y, and Z directions, and establish parameterized models of front suspension damping in the X, Y, and Z directions; 2) Establish parameterized models of the rear suspension stiffness in the X, Y, and Z directions, and establish parameterized models of the rear suspension damping in the X, Y, and Z directions; 3) Establish optimization objectives for the engine mount system, including the static compression of the mount system, the natural frequency of the engine mount system, the energy decoupling rate of the engine mount system, and the vibration transmission rate of the engine mount system; 4) Rank the optimization objectives of the engine mounting system by weight; (4) Simulation optimization analysis of engine mounting system; The simulation optimization analysis of the engine mounting system described in step (4) includes the following steps: 1) Based on the optimization objective with weight 1, the front suspension stiffness range is obtained through simulation optimization. ~ , ~ , ~ ), front suspension damping range ( ~ , ~ , ~ Rear suspension stiffness range ( ~ , ~ , ~ ), rear suspension damping range ( ~ , ~ , ~ ); 2) Within the optimization result range of weight 1, based on the optimization objective of weight 2, the front suspension stiffness range is obtained through simulation optimization. ~ , ~ , ~ ), front suspension damping range ( ~ , ~ , ~ Rear suspension stiffness range ( ~ , ~ , ~ ), rear suspension damping range ( ~ , ~ , ~ ); 3) Within the optimization result range of weight 2, based on the optimization objective of weight 3, the front suspension stiffness range is obtained through simulation optimization. ~ , ~ , ~ ), front suspension damping range ( ~ , ~ , ~ Rear suspension stiffness range ( ~ , ~ , ~ ), rear suspension damping range ( ~ , ~ , ~ ); 4) Within the optimization result range of weight 3, based on the optimization objective of weight 4, the front suspension stiffness is obtained through simulation optimization. , , ), front suspension damping ( , , Rear suspension stiffness ( , , ), rear suspension damping ( , , ); (5) Evaluation of the effectiveness of the optimization scheme.

2. The multivariable, multi-objective hierarchical optimization method for an engine mounting system according to claim 1, characterized in that: Step (2) describes the dynamic simulation and model calibration of the engine mounting system, which includes the following steps: 1) Perform degree of freedom and static balance simulations on the established rigid-flexible coupled dynamic model of the engine mounting system to verify the accuracy of the model; 2) Perform static simulations of the established rigid-flexible coupled dynamic model of the engine mount system in a gravity field to verify the static compression of the front and rear mounts. 3) Perform constrained modal simulations on the established rigid-flexible coupled dynamic model of the engine mounting system to verify the natural frequencies of the model; 4) The established rigid-flexible coupling dynamic model of the engine mounting system is dynamically simulated under engine excitation to verify the vibration transmissibility of the model.

3. The multivariable, multi-objective hierarchical optimization method for an engine mounting system according to claim 1, characterized in that: The inherent frequencies of the engine mounting system mentioned in step (3) include the inherent frequencies in the X, Y, Z, Rx, Ry and Rz directions.

4. The multivariable, multi-objective hierarchical optimization method for an engine mounting system according to claim 1, characterized in that: The energy decoupling rate of the engine mount system mentioned in step (3) includes the energy decoupling rates in the X, Y, Z, Rx, Ry and Rz directions.

5. The multivariable, multi-objective hierarchical optimization method for an engine mounting system according to claim 1, characterized in that: The vibration transmission rate of the engine mount system mentioned in step (3) refers to the ratio of the vibration at the active end to the vibration at the passive end of the front mount and the rear mount.

6. The multivariable, multi-objective hierarchical optimization method for an engine mounting system according to claim 1, characterized in that: The front suspension stiffness mentioned in step (4) , , ), front suspension damping ( , , Rear suspension stiffness ( , , ), rear suspension damping ( , , The optimal compromise solution satisfies all optimization objectives.

7. The multivariable, multi-objective hierarchical optimization method for an engine mounting system according to claim 1, characterized in that: The evaluation of the optimization scheme described in step (5) includes the following steps: (1) Reset the stiffness and damping of the front and rear suspensions according to the optimal compromise scheme; (2) Perform static simulation on the optimized rigid-flexible coupling dynamic model of the engine mount system in the gravitational field, calculate the static compression of the front mount and the rear mount, and compare it with the target value; (3) Modal simulation was performed on the optimized rigid-flexible coupling dynamic model of the engine mount system, and the calculated natural frequencies of the engine mount system were compared with the target values; (4) Perform energy decoupling simulation on the optimized rigid-flexible coupling dynamic model of the engine mount system, and compare the calculated energy decoupling rate of the engine mount system with the target value; (5) Perform dynamic simulation on the optimized rigid-flexible coupling dynamic model of the engine mount system, and compare the calculated vibration transmission rates in the Y and Z directions of the front and rear mounts with the target values.

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