A method, system and terminal for multi-objective optimization of passenger car handling stability and ride performance

Abstract

The present application discloses a method, system and terminal for multi-objective optimization of the handling and smoothness performance of a passenger car. The method includes: obtaining the whole vehicle parameters of the passenger car and establishing a whole vehicle dynamics model; parameterizing the whole vehicle dynamics model; selecting the whole vehicle response index under different working conditions according to the parameterized whole vehicle dynamics model; using the parameter test method to perform sensitivity analysis on the whole vehicle response index and determine the interaction effect between each optimization factor; determining the constraint conditions of the whole vehicle response index, and using the NSGA_Ⅱ optimization algorithm to determine the optimal solution of the whole vehicle dynamics model. The system includes: a parameter acquisition module, a model building module, a parameterization module, a response index determination module, a response index sensitivity analysis module and an optimal solution calculation module. Through the present application, two objectives are balanced at the same time, thereby achieving multi-objective optimization, which is conducive to improving the overall performance of passenger cars, and can reduce the number of actual vehicle test rounds, thereby shortening the vehicle development cycle.

Description

Technical Field

[0001] The present application relates to the technical field of automobile chassis performance, and in particular to a method, system and terminal for multi-objective optimization of the handling and smoothness performance of a passenger car. Background Art

[0002] The chassis system of a passenger car is an integrated platform of multiple systems, and the overall performance of this integrated platform is affected by various performances of the car. The various performances include handling stability and ride smoothness, which are related to the user's riding experience. These two performances are also a pair of contradictory unity in the chassis system of the car, that is, the improvement of ride smoothness will reduce the handling stability to varying degrees. Therefore, how to reasonably optimize the handling stability and ride smoothness of passenger cars to improve the overall performance of the car is an important technical issue.

[0003] At present, the method for optimizing the handling stability and ride smoothness of passenger cars is usually: according to different user needs, focus on the handling stability or ride smoothness of passenger cars respectively, aiming to improve the handling stability or ride smoothness of passenger cars respectively, and then conduct multiple actual vehicle tests to finally complete vehicle development.

[0004] However, the current methods for optimizing the handling stability and ride smoothness of passenger cars respectively aim to improve the handling stability or ride smoothness of passenger cars. Therefore, only a local optimal solution can be obtained in the end, and the two performances cannot be balanced. When the obtained optimization results are used as the basis for adjusting the chassis of the actual vehicle, more rounds of actual vehicle tests are required, which ultimately leads to a long vehicle development cycle. Summary of the invention

[0005] The present application provides a method, system and terminal for multi-objective optimization of the handling and smoothness performance of a passenger vehicle, so as to solve the problem that the performance optimization method in the prior art can only obtain a local optimal solution, resulting in a long vehicle development cycle.

[0006] In order to solve the above technical problems, the embodiments of the present application disclose the following technical solutions:

[0007] A method for multi-objective optimization of the handling and ride performance of a passenger vehicle, the method comprising:

[0008] Obtaining vehicle parameters of a passenger car, the vehicle parameters including: hard point coordinates, mass of each component, moment of inertia, suspension bushing stiffness, front and rear spring stiffness, front and rear shock absorber damping, front and rear stabilizer bar stiffness, steering subsystem transmission ratio, maximum steering wheel torque, engine characteristic curve, front and rear axle braking force distribution coefficients of front and rear brake subsystems, and front and rear brake cylinder piston areas;

[0009] Establishing a vehicle dynamics model according to the vehicle parameters;

[0010] Parameterizing the vehicle dynamics model and selecting optimization factors;

[0011] According to the parameterized vehicle dynamics model, the vehicle response indicators under different working conditions are selected, and the vehicle response indicators include: understeering degree under steady-state turning conditions, roll gradient under steady-state turning conditions, yaw rate peak response time under angular step steering conditions, yaw rate overshoot under angular step steering conditions, yaw rate gain under steering wheel center area steering conditions, and vertical acceleration peak at the driver under single impact conditions;

[0012] Using a parameter test method, a sensitivity analysis is performed on the vehicle response index to determine the interaction effect between the optimization factors;

[0013] The constraint conditions of the whole vehicle response index are determined, and the optimal solution of the whole vehicle dynamics model is determined by using the NSGA_Ⅱ optimization algorithm.

[0014] Optionally, the method of parameterizing the vehicle dynamics model and selecting optimization factors includes:

[0015] The vehicle dynamics model is parameterized by integrating Isight software with multi-body dynamics software Adams Car;

[0016] Integrate Matlab to post-process the results and obtain the parameter values ​​of each response indicator;

[0017] Front and rear spring stiffness, front and rear shock absorber damping, and front and rear stabilizer bar diameters are selected as optimization factors, and the front and rear spring stiffness and front and rear shock absorber damping are changed in coefficients.

[0018] Optionally, the spring stiffness coefficient and the front and rear shock absorber damping coefficients are 0.7-1.3.

[0019] Optionally, a method of using a parameter test method to perform sensitivity analysis on the vehicle response index to determine the interaction effect between the optimization factors includes:

[0020] Using a parameter test method, a sensitivity analysis is performed on the whole vehicle response index to determine the single variable sensitivity of each whole vehicle response index to the optimization factor;

[0021] The single variable sensitivity of all vehicle response indicators is optimized by Latin hypercube sampling to determine the interaction effect between the optimization factors.

[0022] A system for multi-objective optimization of the handling and ride performance of a passenger vehicle, the system comprising:

[0023] A parameter acquisition module is used to obtain the whole vehicle parameters of a passenger car, wherein the whole vehicle parameters include: hard point coordinates, mass of each component, moment of inertia, suspension bushing stiffness, front and rear spring stiffness, front and rear shock absorber damping, front and rear stabilizer bar stiffness, steering subsystem transmission ratio, maximum steering wheel torque, engine characteristic curve, front and rear axle braking force distribution coefficient of the front and rear brake subsystems, and front and rear brake cylinder piston areas;

[0024] A model building module, used to build a vehicle dynamics model according to the vehicle parameters;

[0025] A parameterization module, used to parameterize the vehicle dynamics model and select optimization factors;

[0026] A response index determination module is used to select the whole vehicle response index under different working conditions according to the parameterized whole vehicle dynamics model, wherein the whole vehicle response index includes: understeering degree under steady-state turning condition, roll gradient under steady-state turning condition, yaw rate peak response time under angular step turning condition, yaw rate overshoot under angular step turning condition, yaw rate gain under steering wheel center area steering condition, and vertical acceleration peak value at the driver under single impact condition;

[0027] A response index sensitivity analysis module is used to perform sensitivity analysis on the vehicle response index by using a parameter test method to determine the interaction effect between various optimization factors;

[0028] The optimal solution calculation module is used to determine the constraint conditions of the whole vehicle response index and use the NSGA_Ⅱ optimization algorithm to determine the optimal solution of the whole vehicle dynamics model.

[0029] Optionally, the parameterized module includes:

[0030] A software integration unit, used for parameterizing the vehicle dynamics model by integrating Isight software with multi-body dynamics software Adams Car;

[0031] The processing unit is used to integrate Matlab to perform result post-processing and obtain the parameter value of each response index;

[0032] The optimization factor selection unit is used to select the front and rear spring stiffness, the front and rear shock absorber damping and the front and rear stabilizer bar diameters as optimization factors, and the front and rear spring stiffness and the front and rear shock absorber damping are changed in the form of coefficients.

[0033] Optionally, the response indicator sensitivity analysis module includes:

[0034] A single variable sensitivity determination unit, used to perform sensitivity analysis on the whole vehicle response index by using a parameter test method, and determine the single variable sensitivity of each whole vehicle response index to the optimization factor;

[0035] The interaction effect determination unit is used to optimize the Latin hypercube sampling of the single variable sensitivity of all vehicle response indicators and determine the interaction effect between each optimization factor.

[0036] A terminal comprises: a processor and a memory connected to the processor for communication, wherein:

[0037] The memory stores instructions that can be executed by the processor, and the instructions are executed by the processor so that the processor can execute any of the methods for multi-objective optimization of the handling and smoothness performance of a passenger vehicle as described above.

[0038] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0039] The present application provides a method for multi-objective optimization of the handling and smoothness performance of a passenger car. The method uses a multi-body dynamics virtual simulation and optimization method to complete the adjustment of the chassis components of the test vehicle, including: the adjustment of the front and rear shock absorber damping, the front and rear spring stiffness, and the front and rear lateral stabilizer bar stiffness. The multi-body dynamics model of the whole vehicle is established by using Adams Car software, the Adams Car dynamics model is integrated by using Isight software, and the Matlab software is integrated for result post-processing, so as to achieve the optimization of the six whole vehicle response indicators under four working conditions including steady-state rotation, angular step steering, and steering wheel center area steering for the whole vehicle handling stability, and single impact working conditions for smoothness. The parameter test method is also used to perform sensitivity analysis on the whole vehicle response indicators, determine the interaction effect between the optimization factors, and finally determine the constraint conditions of the whole vehicle response indicators, and use the NSGA_Ⅱ optimization algorithm to determine the optimal solution of the whole vehicle dynamics model, and use the parameters corresponding to the optimal solution as the passenger car performance parameters for operation. This embodiment aims to improve the handling stability and smooth ride performance of passenger cars at the same time, and selects six response indicators under four different working conditions for these two performances. The optimal solution finally obtained can balance the two goals at the same time, thereby achieving multi-objective optimization, which is conducive to improving the overall performance of passenger cars. Moreover, since the handling stability and smooth ride performance of passenger cars are considered at the same time, the obtained optimization results can be used as the basis for adjusting the chassis of the actual vehicle, which can reduce the number of actual vehicle test rounds and thus shorten the vehicle development cycle. In addition, the method of determining the optimal solution of the vehicle dynamics model using the NSGA_Ⅱ optimization algorithm in this embodiment can also greatly reduce the number of actual vehicle test rounds, which is conducive to shortening the vehicle development cycle and reducing vehicle development costs.

[0040] The present application also provides a system for multi-objective optimization of the handling stability and smoothness performance of a passenger car, which mainly includes: a parameter acquisition module, a model building module, a parameterization module, a response index determination module, a response index sensitivity analysis module and an optimal solution calculation module. Through the setting of the model building module, this embodiment combines the Isight software and the multi-body dynamics software Adams Car to establish a vehicle dynamics model. Through the response index determination module, six models under four working conditions of the passenger car are determined, which can more comprehensively and accurately consider the handling stability and smoothness performance of the passenger car, thereby improving the optimization effect. Through the setting of the response index sensitivity analysis module, the sensitivity of the whole vehicle response index and the interaction effect between the optimization factors can be determined, so that the determined vehicle response index value is more conducive to improving the handling stability and smoothness performance of the passenger car.

[0041] The present application also provides a terminal, which also has the above-mentioned method and system for multi-objective optimization of the handling and smoothness performance of a passenger car and the corresponding technical effects, which will not be repeated here.

[0042] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 A flowchart of a method for multi-objective optimization of the handling and ride performance of a passenger vehicle provided in an embodiment of the present application;

[0046] Figure 2 A schematic diagram of the structure of a system for multi-objective optimization of the handling and ride performance of a passenger vehicle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present application.

[0048] In order to better understand the present application, the implementation methods of the present application are explained in detail below with reference to the accompanying drawings.

[0049] Embodiment 1

[0050] See also Figure 1 , Figure 1 A flowchart of a method for multi-objective optimization of the handling and ride performance of a passenger vehicle provided in an embodiment of the present application. Figure 1 It can be seen that the method for multi-objective optimization of the handling and ride performance of a passenger vehicle in this embodiment mainly includes the following processes:

[0051] S1: Obtain the vehicle parameters of the passenger car.

[0052] The vehicle parameters in this embodiment are used to establish a dynamic model to study the handling stability and smoothness of a passenger car. The vehicle parameters include: hard point coordinates, mass of each component, moment of inertia, suspension bushing stiffness, front and rear spring stiffness, front and rear shock absorber damping, front and rear stabilizer bar stiffness, steering subsystem transmission ratio, maximum steering wheel torque, engine characteristic curve, front and rear axle braking force distribution coefficient of the front and rear brake subsystems, and front and rear brake cylinder piston areas.

[0053] S2: Establish the vehicle dynamics model based on the vehicle parameters.

[0054] After obtaining the vehicle parameters of the passenger car, the multi-body dynamics software Adams Car is used to establish the vehicle dynamics model.

[0055] S3: Parameterize the vehicle dynamics model and select optimization factors.

[0056] Specifically, step S3 includes the following process:

[0057] S31: The vehicle dynamics model is parameterized by integrating Isight software with multi-body dynamics software Adams Car.

[0058] S32: Integrate Matlab to perform result post-processing and obtain parameter values ​​of each response index.

[0059] In this embodiment, simulation is pre-processing, and result processing using Matlab is defined as post-processing. Since the horizontal and vertical coordinates in the results obtained after simulation are parameters such as lateral acceleration and time, respectively, and are not values ​​such as understeering and steering gradient, post-processing is performed through Matlab to obtain the required parameter values.

[0060] That is, first, according to the vehicle dynamics model, the simulation of four working conditions, namely steady-state turning condition, angular step steering condition, steering wheel center area steering, and single impact, is completed in Adams Car software. The above simulation results are post-processed using Matlab program to obtain the response indicators of understeering degree and roll gradient, yaw rate peak response, yaw rate overshoot, yaw rate gain, and vertical acceleration peak at the driver.

[0061] S33: The front and rear spring stiffness, the front and rear shock absorber damping, and the front and rear stabilizer bar diameters are selected as optimization factors, and the front and rear spring stiffness and the front and rear shock absorber damping are changed in the form of coefficients.

[0062] Among them, the spring stiffness coefficient and the damping coefficient of the front and rear shock absorbers are 0.7-1.3.

[0063] Continue to see Figure 1 It can be seen that after the whole vehicle dynamics model is parameterized and the optimization factors are selected, step S4 is performed: according to the parameterized whole vehicle dynamics model, the whole vehicle response index under different working conditions is selected.

[0064] Among them, the vehicle response indicators include: understeer under steady-state turning conditions, roll gradient under steady-state turning conditions, yaw velocity peak response time under angular step steering conditions, yaw velocity overshoot under angular step steering conditions, yaw velocity gain under steering wheel center area steering conditions and vertical acceleration peak at the driver under single impact conditions.

[0065] S5: Use parameter test method to conduct sensitivity analysis on vehicle response indicators and determine the interaction effects between optimization factors.

[0066] Specifically, step S5 includes:

[0067] S51: Use parameter test method to perform sensitivity analysis on vehicle response index and determine the single variable sensitivity of each vehicle response index to the optimization factor.

[0068] S52: Optimize Latin hypercube sampling of the single variable sensitivity of all vehicle response indicators to determine the interaction effects between the optimization factors.

[0069] S6: Determine the constraints of the vehicle response index and use the NSGA_Ⅱ optimization algorithm to determine the optimal solution of the vehicle dynamics model.

[0070] In order to optimize the handling stability and ride comfort of passenger cars at the same time, appropriate understeering, higher yaw rate gain, lower roll gradient, yaw rate peak response time and yaw rate overshoot, and minimum impact acceleration are required, and a balance between various response indicators should be achieved. Based on this principle, the response indicator constraints and targets are determined.

[0071] The constraints and targets of the vehicle response index in this embodiment are shown in Table 1.

[0072]

[0073]

[0074] Table 1 Response indicator constraints and targets

[0075] It can be seen from Table 1 that the preferred values ​​of each normal response index are: understeer is 0.2-0.23deg / g, roll gradient is ≥-5.5deg / g, yaw rate peak response time is ≤0.55s, yaw rate overshoot is ≤3.1%, yaw rate gain is ≥0.23deg / deg, and vertical acceleration peak at the driver is ≤4.6m / s2.

[0076] In this embodiment, the NSGA_Ⅱ optimization algorithm is used to determine the optimal solution of the vehicle dynamics model. The spring and shock absorber coefficients are set to 0.7-1.3 in this optimization search. After 169 iterative calculations, the optimal solution is determined. The initial values ​​and optimal solutions of the optimization factors such as front and rear spring stiffness, front and rear shock absorber damping, and front and rear stabilizer bar diameter can be seen in Table 2.

[0077] Design variables Initial Value Optimal solution Front spring rate 1 1.15 Rear spring rate 1 0.92 Front shock absorber damping coefficient 1 0.99 Rear shock absorber damping coefficient 1 0.73 Front stabilizer bar diameter (mm) 30 31 Rear stabilizer bar diameter (mm) 17 17.5

[0078] Table 2 Initial values ​​of design variables and optimal solutions

[0079] After the multi-objective optimization is performed using the method in this embodiment, a comparison list of the initial values ​​of each response index and the values ​​after optimization is shown in Table 3.

[0080]

[0081]

[0082] Table 3 Comparison of vehicle response indicators before and after optimization

[0083] According to the optimized response index and the optimal solution of each optimization factor, the spring stiffness of the front and rear suspension, the front and rear stabilizer bar diameters, and the front and rear shock absorber damping characteristics are finally determined by the method in this embodiment. Among them, the optimal values ​​of the spring stiffness of the front and rear suspension and the front and rear stabilizer bar diameters can be shown in Table 4, and the front and rear shock absorber damping characteristics can be shown in Table 5.

[0084] Design variables plan Front spring rate (N / mm) 135 Rear spring rate (N / mm) 28 Front stabilizer bar diameter (mm) 31 Rear stabilizer bar diameter (mm) 17.5

[0085] Table 4 Optimal values ​​of front and rear suspension spring stiffness and front and rear stabilizer bar diameters

[0086]

[0087] Table 5 Optimized values ​​of front and rear shock absorber damping characteristics

[0088] Embodiment 2

[0089] exist Figure 1 Based on the embodiment shown, see Figure 2 , Figure 2 A schematic diagram of the structure of a system for multi-objective optimization of the handling and ride performance of a passenger vehicle provided in an embodiment of the present application.

[0090] Depend on Figure 2It can be seen that the system for multi-objective optimization of the handling and smoothness performance of a passenger car in this embodiment mainly includes: a parameter acquisition module, a model building module, a parameterization module, a response index determination module, a response index sensitivity analysis module and an optimal solution calculation module. Among them, the parameter acquisition module is used to obtain the whole vehicle parameters of the passenger car, and the whole vehicle parameters include: hard point coordinates, mass of each component, moment of inertia, suspension bushing stiffness, front and rear spring stiffness, front and rear shock absorber damping, front and rear stabilizer bar stiffness, steering subsystem transmission ratio, maximum steering wheel torque, engine characteristic curve, front and rear axle braking force distribution coefficient of the front and rear brake subsystems, and front and rear brake cylinder piston areas; the model building module is used to establish a whole vehicle dynamics model according to the whole vehicle parameters; the parameterization module is used to parameterize the whole vehicle dynamics model and select optimization factors; the response index determination module is used to select the whole vehicle response under different working conditions according to the parameterized whole vehicle dynamics model. The vehicle response indicators include: understeering degree under steady-state turning conditions, roll gradient under steady-state turning conditions, yaw velocity peak response time under angular step steering conditions, yaw velocity overshoot under angular step steering conditions, yaw velocity gain under steering wheel center area conditions and vertical acceleration peak at the driver under single impact conditions; the response indicator sensitivity analysis module is used to use parameter test methods to perform sensitivity analysis on the vehicle response indicators and determine the interaction effects between the optimization factors; the optimal solution calculation module is used to determine the constraint conditions of the vehicle response indicators and use the NSGA_Ⅱ optimization algorithm to determine the optimal solution of the vehicle dynamics model.

[0091] Furthermore, the parameterization module includes: a software integration unit, a processing unit, and an optimization factor selection unit. The software integration unit is used to parameterize the vehicle dynamics model by integrating the multi-body dynamics software Adams Car with the Isight software; the processing unit is used to integrate Matlab for result post-processing to obtain the parameter values ​​of each response index; the optimization factor selection unit is used to select the front and rear spring stiffness, front and rear shock absorber damping, and front and rear stabilizer bar diameters as optimization factors, and the front and rear spring stiffness and front and rear shock absorber damping are changed in the form of coefficients.

[0092] The response index sensitivity analysis module includes: a single variable sensitivity determination unit and an interaction effect determination unit. The single variable sensitivity determination unit is used to perform sensitivity analysis on the vehicle response index using a parameter test method to determine the single variable sensitivity of each vehicle response index to the optimization factor; the interaction effect determination unit is used to optimize the Latin hypercube sampling of the single variable sensitivity of all vehicle response indicators to determine the interaction effect between the optimization factors.

[0093] For the parts not described in detail in this embodiment, please refer to Figure 1The two embodiments shown can refer to each other and will not be described in detail here.

[0094] Embodiment 3

[0095] The present application also provides a terminal, which includes: a processor and a memory communicatively connected to the processor, wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor so that the processor can execute the above-mentioned method for multi-objective optimization of the handling stability and smoothness performance of a passenger vehicle.

[0096] The method for multi-objective optimization of passenger vehicle handling and ride performance performed by the processor is as follows:

[0097] 1) Obtain the vehicle parameters of the passenger car, including: hard point coordinates, mass of each component, moment of inertia, suspension bushing stiffness, front and rear spring stiffness, front and rear shock absorber damping, front and rear stabilizer bar stiffness, steering subsystem transmission ratio, maximum steering wheel torque, engine characteristic curve, front and rear axle braking force distribution coefficient of the front and rear brake subsystem, and front and rear brake cylinder piston area;

[0098] 2) Establish the vehicle dynamics model based on the vehicle parameters;

[0099] 3) Parameterize the vehicle dynamics model and select the optimization factors;

[0100] 4) According to the parameterized vehicle dynamics model, the vehicle response indicators under different working conditions are selected. The vehicle response indicators include: understeering degree under steady-state turning conditions, roll gradient under steady-state turning conditions, yaw rate peak response time under angular step steering conditions, yaw rate overshoot under angular step steering conditions, yaw rate gain under steering wheel center area steering conditions, and vertical acceleration peak at the driver under single impact conditions;

[0101] 5) Use parameter test method to conduct sensitivity analysis on vehicle response indicators and determine the interaction effects between optimization factors;

[0102] 6) Determine the constraints of the vehicle response indicators and use the NSGA_Ⅱ optimization algorithm to determine the optimal solution of the vehicle dynamics model.

[0103] Parts not described in detail in this embodiment can be found in Figure 1 and Figure 2 The embodiments shown will not be described in detail here.

[0104] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features disclosed herein.

Claims

1. A method for multi-objective optimization of the handling and ride performance of a passenger vehicle, characterized in that: The method comprises: Obtaining vehicle parameters of a passenger car, the vehicle parameters including: hard point coordinates, mass of each component, moment of inertia, suspension bushing stiffness, front and rear spring stiffness, front and rear shock absorber damping, front and rear stabilizer bar stiffness, steering subsystem transmission ratio, maximum steering wheel torque, engine characteristic curve, front and rear axle braking force distribution coefficients of front and rear brake subsystems, and front and rear brake cylinder piston areas; Establishing a vehicle dynamics model according to the vehicle parameters; Parameterizing the vehicle dynamics model and selecting optimization factors; According to the parameterized vehicle dynamics model, the vehicle response indicators under different working conditions are selected, and the vehicle response indicators include: understeering degree under steady-state turning conditions, roll gradient under steady-state turning conditions, yaw rate peak response time under angular step steering conditions, yaw rate overshoot under angular step steering conditions, yaw rate gain under steering wheel center area steering conditions, and vertical acceleration peak at the driver under single impact conditions; Using a parameter test method, a sensitivity analysis is performed on the vehicle response index to determine the interaction effect between the optimization factors; The constraint conditions of the whole vehicle response index are determined, and the optimal solution of the whole vehicle dynamics model is determined by using the NSGA_Ⅱ optimization algorithm.

2. The method for multi-objective optimization of passenger vehicle handling and ride performance according to claim 1, characterized in that: The method of parameterizing the vehicle dynamics model and selecting optimization factors includes: The vehicle dynamics model is parameterized by integrating Isight software with multi-body dynamics software Adams Car; Integrate Matlab to post-process the results and obtain the parameter values ​​of each response indicator; Front and rear spring stiffness, front and rear shock absorber damping, and front and rear stabilizer bar diameters are selected as optimization factors, and the front and rear spring stiffness and front and rear shock absorber damping are changed in coefficients.

3. The method for multi-objective optimization of passenger vehicle handling and ride performance according to claim 2, characterized in that: The spring stiffness coefficient and the front and rear shock absorber damping coefficient are 0.7-1.

3.

4. The method for multi-objective optimization of passenger vehicle handling and ride performance according to claim 1, characterized in that: The method of using a parameter test method to perform sensitivity analysis on the vehicle response index and determine the interaction effect between the optimization factors includes: Using a parameter test method, a sensitivity analysis is performed on the whole vehicle response index to determine the single variable sensitivity of each whole vehicle response index to the optimization factor; The single variable sensitivity of all vehicle response indicators is optimized by Latin hypercube sampling to determine the interaction effect between the optimization factors.

5. A system for multi-objective optimization of the handling and ride performance of a passenger vehicle, characterized in that: The system comprises: A parameter acquisition module is used to obtain the whole vehicle parameters of a passenger car, wherein the whole vehicle parameters include: hard point coordinates, mass of each component, moment of inertia, suspension bushing stiffness, front and rear spring stiffness, front and rear shock absorber damping, front and rear stabilizer bar stiffness, steering subsystem transmission ratio, maximum steering wheel torque, engine characteristic curve, front and rear axle braking force distribution coefficient of the front and rear brake subsystems, and front and rear brake cylinder piston areas; A model building module, used to build a vehicle dynamics model according to the vehicle parameters; A parameterization module, used to parameterize the vehicle dynamics model and select optimization factors; A response index determination module is used to select the whole vehicle response index under different working conditions according to the parameterized whole vehicle dynamics model, wherein the whole vehicle response index includes: understeering degree under steady-state turning condition, roll gradient under steady-state turning condition, yaw rate peak response time under angular step turning condition, yaw rate overshoot under angular step turning condition, yaw rate gain under steering wheel center area steering condition, and vertical acceleration peak value at the driver under single impact condition; A response index sensitivity analysis module is used to perform sensitivity analysis on the vehicle response index by using a parameter test method to determine the interaction effect between various optimization factors; The optimal solution calculation module is used to determine the constraint conditions of the whole vehicle response index and use the NSGA_Ⅱ optimization algorithm to determine the optimal solution of the whole vehicle dynamics model.

6. The system for multi-objective optimization of the handling and ride performance of a passenger vehicle according to claim 5, characterized in that: The parameterized modules include: A software integration unit, used for parameterizing the vehicle dynamics model by integrating Isight software with multi-body dynamics software Adams Car; The processing unit is used to integrate Matlab to perform result post-processing and obtain the parameter value of each response index; The optimization factor selection unit is used to select the front and rear spring stiffness, the front and rear shock absorber damping and the front and rear stabilizer bar diameters as optimization factors, and the front and rear spring stiffness and the front and rear shock absorber damping are changed in the form of coefficients.

7. The system for multi-objective optimization of the handling and ride performance of a passenger vehicle according to claim 5, characterized in that: The response index sensitivity analysis module includes: A single variable sensitivity determination unit, used to perform sensitivity analysis on the whole vehicle response index by using a parameter test method, and determine the single variable sensitivity of each whole vehicle response index to the optimization factor; The interaction effect determination unit is used to optimize the Latin hypercube sampling of the single variable sensitivity of all vehicle response indicators and determine the interaction effect between each optimization factor.

8. A terminal, characterized in that: The terminal includes: a processor and a memory connected to the processor in communication, wherein: The memory stores instructions that can be executed by the processor, and the instructions are executed by the processor so that the processor can execute the method for multi-objective optimization of the handling and smoothness performance of a passenger vehicle as described in any one of claims 1 to 4.

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