Control model construction method based on intelligent suspension system

Abstract

The invention relates to the technical field of model construction, and discloses a control model construction method based on an intelligent suspension system, which comprises the steps of data acquisition, feature extraction, control parameter analysis, control model construction and suspension system control. According to the method, key data such as vehicle body vertical acceleration and wheel vertical displacement are accurately collected, feature extraction and control parameter analysis are combined, accurate calculation of the damping coefficient and the spring stiffness coefficient of the suspension system is achieved, and a basis is provided for real-time control; mutual relations among parameters of the suspension system, such as correlation between a stress value and a damping coefficient and correlation between wheel vertical displacement and a spring stiffness coefficient, are comprehensively considered, so that the control is more scientific and reasonable; a kinetic equation is constructed according to the mechanics principle, data and parameters are substituted into the equation to determine an adjustment coefficient, and a solid theoretical basis is provided for control; the suspension system can be dynamically adjusted in real time according to road conditions, the driving comfort and safety are improved, and the intelligent development requirement of modern automobiles is met.

Description

Technical Field

[0001] The present invention relates to the technical field of model construction, and in particular to a control model construction method based on an intelligent suspension system. Background Art

[0002] With the rapid development of the automobile industry and people's increasing requirements for driving comfort and handling stability, the performance optimization of vehicle suspension systems has become a key research area. Most traditional suspension systems use fixed parameter designs, that is, the spring stiffness coefficient and damping coefficient are set when the vehicle leaves the factory and cannot be dynamically adjusted according to the actual road conditions during driving.

[0003] In actual driving scenarios, vehicles face a variety of road conditions, such as flat highways, bumpy country roads, potholed city roads, etc. When driving on flat roads, a suspension system with fixed parameters may cause poor ride comfort due to its high stiffness; on rugged roads, if the suspension system has insufficient damping, the vehicle body will shake violently, affecting handling stability and even endangering driving safety.

[0004] In addition, the driving state of the vehicle changes all the time. Operations such as acceleration, braking, and turning will change the stress on the vehicle body, and the performance requirements of the suspension system will also change accordingly. Traditional suspension is difficult to adapt to these complex and changing working conditions in real time and cannot provide consistent and good support for the vehicle.

[0005] Furthermore, modern automobile technology is moving towards intelligence and automation, and consumers expect vehicles to have higher levels of intelligent perception and adaptive adjustment capabilities. Summary of the invention

[0006] The purpose of the present invention is to provide a control model construction method based on an intelligent suspension system, which solves the technical problems raised in the background technology.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] The control model construction method based on the intelligent suspension system includes the following steps:

[0009] Step 1: Data collection:

[0010] Collect key data related to the suspension system, including the vertical acceleration of the vehicle body and the vertical displacement of the wheels;

[0011] Step 2: Feature extraction:

[0012] The compression speed feature and force feature extraction of the suspension system are performed based on the key data in the suspension system. The method is as follows: subtract the vertical displacement values ​​of the wheels collected twice adjacently, and then divide by the time interval between the two adjacent collections to calculate the compression speed of the suspension system. The force value of the suspension system is calculated based on the vertical acceleration of the vehicle body multiplied by the equivalent mass supported by the suspension system.

[0013] Step 3: Control parameter analysis:

[0014] The damping coefficient of the suspension system is calculated through the compression speed of the suspension system and the force value of the suspension system, and the stiffness coefficient of the spring in the suspension system is also calculated;

[0015] Step 4: Control model construction:

[0016] According to the principle of mechanics, the suspension system is regarded as a dynamic system composed of mass, spring and damping. The results of data acquisition, feature extraction and control parameter analysis are combined to establish a dynamic equation based on the mechanical balance principle of the suspension system. Then, the vertical acceleration of the vehicle body and the vertical displacement of the wheel are obtained according to the data acquisition step. Then, the compression speed of the suspension system, as well as the damping coefficient and the spring stiffness coefficient are calculated according to the feature extraction step, and then substituted into the dynamic equation to calculate the spring stiffness adjustment coefficient and the damping adjustment coefficient.

[0017] Step 5: Suspension system control:

[0018] According to the calculated adjustment coefficient of the stiffness spring and the damping adjustment coefficient at the current moment, the spring and the damper in the suspension system are controlled in real time.

[0019] As a further solution of the present invention, the vertical acceleration of the vehicle body is obtained by installing an acceleration sensor at the center of mass of the vehicle body; the vertical displacement of the wheel is obtained by installing a displacement sensor on a wheel suspension component.

[0020] As a further solution of the present invention, the feature extraction method is as follows:

[0021] Step T1. Compression speed characteristics of the suspension system:

[0022] Extract the vertical displacement value of the wheel measured in the displacement sensor and mark it as X;

[0023] According to the acquisition frequency of the displacement sensor, the time interval between two adjacent acquisitions of the wheel vertical displacement value is determined;

[0024] The formula is:

[0025] Where, f is the acquisition frequency of the displacement sensor, and it is a preset value, t 0The time interval between two consecutive acquisitions of wheel vertical displacement values;

[0026] Then through:

[0027] Calculate the compression velocity YV of the suspension system;

[0028] In the formula, X -1 Refers to the vertical displacement value of the wheel collected last time relative to X;

[0029] Step T2: Force characteristics of the suspension system

[0030] Extract multiple body vertical accelerations measured by the acceleration sensor within a specified period of time and mark them as A;

[0031] Then through: FS = DM × A;

[0032] Calculate the force value FS of the suspension system;

[0033] Where DM is the equivalent mass supported by the suspension system, which includes the mass of the vehicle body and other masses supported by the suspension system;

[0034] As a further solution of the present invention, the equivalent mass DM is obtained as follows:

[0035] When the vehicle is stationary, the static pressure on the suspension is measured by installing a pressure sensor on each suspension and marked as FJ;

[0036] Then through the gravity formula:

[0037] Calculate the mass M supported by the suspension, which is the equivalent mass DM;

[0038] Where g is the acceleration due to gravity.

[0039] As a further solution of the present invention, the control parameter analysis method is as follows:

[0040] Firstly, the compression velocity YV of the suspension system and the force value FS of the suspension system are extracted;

[0041] Then through:

[0042] Calculate the damping coefficient ZN of the suspension system;

[0043] Among them, the damping coefficient represents the ability of the suspension system to dissipate energy during vibration;

[0044] Then pass:

[0045] Calculate the spring stiffness coefficient TG in the suspension system.

[0046] As a further solution of the present invention, when the force value of the suspension system increases, if it is desired to maintain a certain vibration suppression effect, then the damping coefficient needs to be increased while the compression speed remains unchanged; conversely, when the force value of the suspension system decreases, the damping coefficient is appropriately reduced.

[0047] As a further solution of the present invention, when the force value of the suspension system is constant, the greater the vertical displacement of the wheel, the smaller the spring stiffness coefficient; conversely, the smaller the vertical displacement of the wheel, the greater the spring stiffness coefficient.

[0048] As a further solution of the present invention, the control model is constructed as follows:

[0049] Step M1, establish the kinetic equation:

[0050] Combined with the principles of mechanics, the suspension system is regarded as a dynamic system composed of mass, spring and damping; then the results obtained from the corresponding steps of data acquisition, feature extraction and control parameter analysis are combined with the mechanical balance principle of the suspension system to establish the dynamic equation of the suspension system;

[0051] The kinetic equation is: DM×A+ZN×YV+TG×X=0;

[0052] In the formula, TG×X represents the spring force, ZN×YV represents the damping force, and DM×A represents the inertia force;

[0053] StepM2, multi-time node data collection:

[0054] In the control cycle, the vehicle body vertical acceleration and wheel vertical displacement values ​​obtained at multiple time nodes in the cycle are obtained and recorded as A and u , X u , u=1, 2, …, e, e represents the number of time nodes in the control cycle;

[0055] StepM3, Calculation of compression speed of each node:

[0056] According to the feature extraction steps, the compression velocity of the suspension system at each time node is calculated and recorded as YV u ;

[0057] Step M4, determine the key coefficients of each node:

[0058] According to the feature extraction step and the control parameter step, the damping coefficient ZN of the suspension system and the stiffness coefficient of the spring in the suspension system at each time node are calculated and recorded as ZN u and TG u ;

[0059] Step M5. Solve the adjustment coefficient according to the equation:

[0060] Binding kinetic equation: DM×A+ZN×YV+TG×X=0;

[0061] A u , X u , YV u and ZN u And substitute into the kinetic equation:

[0062] And through the transformed equation:

[0063] Calculate the spring stiffness adjustment coefficient TG0 at the corresponding time node u ;

[0064] Among them, X u The value of is not 0;

[0065] At the same time, A u , X u , YV u and TG u And substitute into the kinetic equation:

[0066] And through the transformed equation:

[0067] Calculate the damping adjustment coefficient ZN0 of the corresponding time node u ;

[0068] Among them, YV u The value of is not 0.

[0069] Beneficial effects of the present invention:

[0070] Precisely control the performance of the suspension system: Through detailed data collection steps, key data such as the vertical acceleration of the vehicle body and the vertical displacement of the wheels are obtained, and further operations such as feature extraction and control parameter analysis can be performed to accurately calculate the damping coefficient of the suspension system, the stiffness coefficient of the spring, and the subsequent spring stiffness adjustment coefficient and damping adjustment coefficient. Therefore, the springs and dampers in the suspension system can be controlled in real time and accurately according to actual conditions, effectively improving the performance of the suspension system and making it better adapt to different working conditions.

[0071] Fully consider the correlation of multiple factors: In the process of feature extraction, control parameter analysis and control model construction, the relationship between multiple related factors such as the compression speed of the suspension system, the force value, the vertical displacement of the wheel, etc. is comprehensively considered. For example, when analyzing the control parameters, the relationship between the change of the force value of the suspension system and the adjustment of the damping coefficient, as well as the relationship between the vertical displacement of the wheel and the spring stiffness coefficient when the force value of the suspension system is constant, is clarified. In this way, the various parameters of the suspension system can be adapted and adjusted more scientifically and reasonably according to the actual state to ensure the good working state of the suspension system.

[0072] Constructing the model based on scientific principles: Based on the principles of mechanics, the suspension system is regarded as a dynamic system composed of mass, spring and damping to establish the dynamic equation. The entire control model construction process is logically rigorous, scientific and reasonable, and the data obtained in multiple steps and the calculated parameters are substituted into the equation to determine the adjustment coefficient, so that the final control of the suspension system has a solid theoretical basis to support it, thereby improving the reliability and effectiveness of the control.

[0073] Real-time adaptation to changes in road conditions: With the help of calculations and analysis in each link, the suspension system can be controlled in real time according to the adjustment coefficient of the stiffness spring and the damping adjustment coefficient at the current moment, which means that the suspension system can be dynamically adjusted in real time according to different road conditions during vehicle driving, thereby improving the comfort of the driver and passengers as well as the stability and safety of the vehicle.

[0074] Accurately obtain key parameters: The method of obtaining key parameters such as vehicle body vertical acceleration, wheel vertical displacement and equivalent mass is clarified. For example, the vertical acceleration of the vehicle body is obtained by installing an acceleration sensor at the center of mass of the vehicle body, and the vertical displacement of the wheel is obtained by installing a displacement sensor on the wheel suspension component. When the vehicle is stationary, a pressure sensor is installed on each suspension to measure the static pressure on the suspension and then calculate the equivalent mass. This ensures the accuracy of the data relied on for subsequent calculations and controls, which helps the entire control model to function better. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] The present invention will be further described below in conjunction with the accompanying drawings.

[0076] Figure 1 It is a system block diagram of the control model construction method based on the intelligent suspension system of the present invention.

[0077] Figure 2 It is a flow chart of control model construction in the control model construction method based on the intelligent suspension system of the present invention. DETAILED DESCRIPTION

[0078] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0079] Embodiment 1

[0080] See also Figure 1 and Figure 2 As shown, the present invention is a control model construction method based on an intelligent suspension system, comprising the following steps:

[0081] Step 1: Data collection:

[0082] Collect key data related to the suspension system;

[0083] Key data include vehicle body vertical acceleration and wheel vertical displacement;

[0084] The vertical acceleration of the vehicle body is obtained by installing an acceleration sensor at the center of mass of the vehicle body; the acceleration sensor can sense the acceleration change of the vehicle body in the vertical direction;

[0085] In this embodiment, for example, when a vehicle travels over a bumpy road, the vehicle body will vibrate up and down, and the acceleration sensor can measure the magnitude of the acceleration in the vertical direction; the vertical acceleration of the vehicle body is an important indicator of the driving comfort of the vehicle. A larger vertical acceleration means that the vehicle body vibrates more violently, and the passengers will feel bumpy.

[0086] The vertical displacement of the wheel is obtained by installing a displacement sensor on the wheel suspension component;

[0087] In this embodiment, when the wheel moves up and down due to the uneven road surface, the displacement sensor can record the vertical displacement; the vertical displacement of the wheel directly reflects the impact of the unevenness of the road surface on the wheel, and is an important basis for the suspension system to be adjusted;

[0088] Step 2: Feature extraction:

[0089] StepT1. Compression speed characteristics of the suspension system:

[0090] Extract the vertical displacement value of the wheel measured in the displacement sensor and mark it as X;

[0091] According to the acquisition frequency of the displacement sensor, the time interval between two adjacent acquisitions of the wheel vertical displacement value is determined;

[0092] The formula is:

[0093] Where, f is the acquisition frequency of the displacement sensor, and it is a preset value, t 0 The time interval between two consecutive acquisitions of wheel vertical displacement values;

[0094] Then through:

[0095] Calculate the compression velocity YV of the suspension system;

[0096] Where, X -1 Refers to the vertical displacement value of the wheel collected last time relative to X;

[0097] In this embodiment, the compression speed of the suspension system reflects the degree of compression of the suspension system per unit time, and plays an important role in determining the damping coefficient.

[0098] Step T2: Force characteristics of the suspension system

[0099] Extract multiple body vertical accelerations measured by the acceleration sensor within a specified period of time and mark them as A;

[0100] Then through: FS = DM × A;

[0101] Calculate the force value FS of the suspension system;

[0102] Where DM is the equivalent mass supported by the suspension system, which includes the mass of the vehicle body and other masses supported by the suspension system;

[0103] In this embodiment, the stress condition of the suspension system is the key basis for judging the working state of the suspension system and adjusting the control parameters;

[0104] Among them, the equivalent mass DM is obtained as follows:

[0105] When the vehicle is stationary, the static pressure on the suspension is measured by installing a pressure sensor on each suspension and marked as FJ;

[0106] Then through the gravity formula:

[0107] Calculate the mass M supported by the suspension, which is the equivalent mass DM;

[0108] Where g is the acceleration due to gravity;

[0109] Step 3: Control parameter analysis:

[0110] Firstly, the compression velocity YV of the suspension system and the force value FS of the suspension system are extracted;

[0111] Then through:

[0112] Calculate the damping coefficient ZN of the suspension system;

[0113] Among them, the damping coefficient indicates the ability of the suspension system to consume energy during vibration. From a mechanical point of view, the damping force is proportional to the force on the suspension system and inversely proportional to the compression speed. A reasonable damping coefficient can effectively suppress the vibration of the vehicle body and improve driving comfort.

[0114] When the force value of the suspension system increases, if you want to maintain a certain vibration suppression effect, then the damping coefficient needs to be increased while the compression speed remains unchanged; conversely, when the force value of the suspension system decreases, the damping coefficient should be appropriately reduced;

[0115] Then pass:

[0116] Calculate the spring stiffness coefficient TG of the suspension system;

[0117] In the suspension system, the spring stiffness coefficient indicates the elastic force generated by the spring under unit displacement. The spring stiffness coefficient determines the support capacity of the suspension system for the vehicle body. The appropriate stiffness coefficient can ensure the stability of the vehicle body during driving.

[0118] When the force value of the suspension system is constant, the greater the vertical displacement of the wheel, the smaller the spring stiffness coefficient; conversely, the smaller the vertical displacement of the wheel, the greater the spring stiffness coefficient;

[0119] Step 4: Control model construction:

[0120] Step M1. Combining the principles of mechanics, the suspension system is considered as a dynamic system consisting of mass, springs and damping. Then, the results obtained from the corresponding steps of data acquisition, feature extraction and control parameter analysis are combined with the mechanical balance principle of the suspension system to establish the dynamic equation of the suspension system.

[0121] The kinetic equation is: DM×A+ZN×YV+TG×X=0;

[0122] In the formula, TG×X represents the spring force, ZN×YV represents the damping force, and DM×A represents the inertia force;

[0123] Among them, the dynamic equation is the basis for describing the motion state of the suspension system and the core of building the control model. Under ideal conditions, ignoring the influence of gravity in this relative motion analysis, the inertia force, damping force and spring force are in equilibrium. According to Newton's second law, their vector sum is zero, which means that at any time, the inertia force, damping force and spring force of the suspension system offset each other, ensuring the stable operation of the suspension system.

[0124] Step M2: During the control cycle, obtain the vehicle body vertical acceleration and wheel vertical displacement values ​​obtained at multiple time nodes during the cycle, and record them as A u , X u , u=1, 2, …, e, e represents the number of time nodes in the control cycle;

[0125] Step M3: According to the feature extraction step, the compression speed of the suspension system at each time node is calculated and recorded as YV u ;

[0126] Step M4: According to the feature extraction step and the control parameter step, the damping coefficient ZN of the suspension system and the stiffness coefficient of the spring in the suspension system at each time node are calculated respectively, and they are recorded as ZN u and TG u ;

[0127] Step M5, binding kinetic equation: DM×A+ZN×YV+TG×X=0;

[0128] A u , X u , YV u and ZN u And substitute into the kinetic equation:

[0129] And through the transformed equation:

[0130] Calculate the spring stiffness adjustment coefficient TG0 at the corresponding time node u ;

[0131] Among them, X u The value of is not 0;

[0132] At the same time, A u , X u , YV u and TG u And substitute into the kinetic equation:

[0133] And through the transformed equation:

[0134] Calculate the damping adjustment coefficient ZN0 of the corresponding time node u ;

[0135] Among them, YV u The value of is not 0.

[0136] This embodiment can capture the key data of the suspension system in real time and accurately by installing an acceleration sensor at the center of mass of the vehicle body to obtain the vertical acceleration of the vehicle body, and installing a displacement sensor at the wheel suspension component to obtain the vertical displacement of the wheel, so as to provide a reliable basis for subsequent regulation and control, and intuitively reflect the driving state of the vehicle and the road conditions; the compression speed of the suspension system is calculated according to the acquisition frequency of the displacement sensor, and the force value is obtained by combining the acceleration of the vehicle body and the equivalent mass, so as to accurately quantify the key characteristics of the suspension system. These characteristic parameters are helpful for in-depth understanding of the working state of the suspension system and lay a foundation for subsequent control parameter analysis; the damping coefficient and the spring stiffness coefficient are calculated based on the compression speed and the force value, and the relationship between the two and the driving conditions is clarified, such as the corresponding relationship between the force value and the damping adjustment, and the wheel displacement and the spring stiffness, so that the suspension system can be flexibly adapted according to the actual situation, and the driving comfort and vehicle stability are effectively improved; the dynamic equation is constructed according to the principle of mechanics, and the data and parameters of multiple links are substituted into the solution, so as to provide rigorous theoretical support for the control of the suspension system, ensure the stable operation of the system, ensure the balance of various forces in the suspension system under different working conditions, and optimize the vehicle handling performance.

[0137] Embodiment 2

[0138] As the second embodiment of the present invention, when the present application is implemented, compared with the first embodiment, the technical solution of the present embodiment is different from the first embodiment only in that the present embodiment further includes the steps of: suspension system control, which controls the spring and damper in the suspension system in real time according to the calculated adjustment coefficient of the stiffness spring and the damping adjustment coefficient at the current moment;

[0139] In this embodiment, for example, if the calculated damping adjustment coefficient is large, it means that the damping force needs to be increased to suppress the vehicle body vibration, and the control system will adjust the parameters of the damper to achieve the corresponding damping effect;

[0140] If the calculated spring adjustment coefficient changes, the control system will adjust the spring stiffness to ensure the stability of the vehicle body.

[0141] This embodiment adds a suspension system control step based on the first embodiment, and realizes closed-loop real-time control. According to the calculated stiffness spring adjustment coefficient and damping adjustment coefficient, the spring and damper parameters are adjusted immediately. In case of severe body vibration, the damping force can be increased rapidly; if the road surface changes and the wheel displacement changes, the spring stiffness can be adjusted in time to ensure that the vehicle is always in the best driving state, which greatly improves the adaptability and response timeliness of the suspension system to complex road conditions.

[0142] Embodiment 3

[0143] As the third embodiment of the present invention, when the present application is specifically implemented, compared with the first and second embodiments, the technical solution of this embodiment is to combine the solutions of the first and second embodiments mentioned above for implementation.

[0144] This embodiment integrates the first embodiment and the second embodiment, and has the advantages of accurate data collection, scientific feature extraction, reasonable control parameter analysis, solid theoretical modeling and real-time closed-loop control. It optimizes the performance of the suspension system in all directions, forms a complete chain from data perception, parameter calculation to dynamic regulation, and efficiently responds to various road conditions and driving conditions, providing the vehicle with excellent driving comfort, control stability and intelligent adaptability, meeting the high standard requirements of modern automobiles for suspension systems.

[0145] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0146] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A control model construction method based on an intelligent suspension system, characterized in that: The following steps are involved: Step 1: Data collection: Collect key data in the suspension system, including the vertical acceleration of the vehicle body and the vertical displacement of the wheels; Step 2: Feature extraction: Extract compression velocity characteristics and force characteristics of the suspension system based on key data in the suspension system; Step 3: Control parameter analysis: The damping coefficient of the suspension system is calculated by the compression velocity characteristics of the suspension system and the force characteristics of the suspension system. At the same time, the stiffness coefficient of the spring in the suspension system is calculated by the force characteristics of the suspension system and the vertical displacement of the wheel. Step 4: Control model construction: Based on the results of data collection, feature extraction, and control parameter analysis, the dynamic equation is established in combination with the mechanical balance principle of the suspension system. Then, the vertical acceleration of the vehicle body and the vertical displacement of the wheel are obtained according to the data collection step. Then, the compression speed of the suspension system, as well as the damping coefficient and the spring stiffness coefficient are calculated according to the feature extraction step, and the coefficients are substituted into the dynamic equation to calculate the spring stiffness adjustment coefficient and the damping adjustment coefficient. Step 5: Suspension system control: According to the calculated adjustment coefficient of the stiffness spring and the damping adjustment coefficient at the current moment, the spring and the damper in the suspension system are controlled in real time.

2. The control model construction method based on the intelligent suspension system according to claim 1 is characterized in that: The compression velocity feature extraction method of the suspension system is as follows: Extract the vertical displacement value of the wheel measured in the displacement sensor and mark it as X; According to the acquisition frequency of the displacement sensor, the time interval between two adjacent acquisitions of the wheel vertical displacement value is determined; The formula is: Wherein, f is the acquisition frequency of the displacement sensor, which is a preset value, and t0 is the time interval between two adjacent acquisitions of the wheel vertical displacement values; Then through: Calculate the compression velocity YV of the suspension system; Where, X -1 Refers to the last collected vertical displacement value of the wheel relative to X.

3. The control model construction method based on the intelligent suspension system according to claim 2 is characterized in that: The force characteristics of the suspension system are extracted as follows: Extract multiple body vertical accelerations measured by the acceleration sensor within a specified period of time and mark them as A; Then through: FS = DM × A; Calculate the force value FS of the suspension system; Where DM is the equivalent mass supported by the suspension system.

4. The control model construction method based on the intelligent suspension system according to claim 3 is characterized in that: The equivalent quality DM is obtained as follows: When the vehicle is stationary, the static pressure on the suspension is measured by installing a pressure sensor on each suspension and marked as FJ; Then through the gravity formula: Calculate the mass M supported by the suspension, which is the equivalent mass DM; Where g is the acceleration due to gravity.

5. The control model construction method based on the intelligent suspension system according to claim 3 is characterized in that: The control parameters are analyzed as follows: Firstly, the compression velocity YV of the suspension system and the force value FS of the suspension system are extracted; Then through: Calculate the damping coefficient ZN of the suspension system; Among them, the damping coefficient represents the ability of the suspension system to dissipate energy during vibration; Then pass: Calculate the spring stiffness coefficient TG in the suspension system.

6. The control model construction method based on the intelligent suspension system according to claim 5 is characterized in that: When the force value of the suspension system increases, the damping coefficient increases; conversely, when the force value of the suspension system decreases, the damping coefficient decreases.

7. The control model construction method based on the intelligent suspension system according to claim 5 is characterized in that: When the force value of the suspension system is fixed, the greater the vertical displacement of the wheel, the smaller the spring stiffness coefficient; conversely, the smaller the vertical displacement of the wheel, the greater the spring stiffness coefficient.

8. The control model construction method based on the intelligent suspension system according to claim 5 is characterized in that: The control model is constructed as follows: Step M1, combining the results obtained from the corresponding steps of data acquisition, feature extraction, and control parameter analysis with the mechanical balance principle of the suspension system to establish the dynamic equation of the suspension system; Step M2: During the control cycle, obtain the vehicle body vertical acceleration and wheel vertical displacement values ​​obtained at multiple time nodes during the cycle, and record them as A u , X u , u=1, 2, …, e, e represents the number of time nodes in the control cycle; Step M3: According to the feature extraction step, the compression speed of the suspension system at each time node is calculated and recorded as YV u ; Step M4: According to the feature extraction step and the control parameter step, the damping coefficient ZN of the suspension system and the stiffness coefficient of the spring in the suspension system at each time node are calculated respectively, and they are recorded as ZN u and TG u ; Step M5, A u , X u , YV u and ZN u Substitute and into the dynamic equation to calculate the stiffness adjustment coefficient of the spring at the corresponding time node; At the same time, A u , X u , YV u and TG u Substitute and into the dynamic equation to calculate the damping adjustment coefficient of the corresponding time node.

9. The control model construction method based on the intelligent suspension system according to claim 8, characterized in that: The kinetic equation in StepM1 is: DM×A+ZN×YV+TG×X=0; In the formula, TG×X represents the spring force, ZN×YV represents the damping force, and DM×A represents the inertia force; The calculation formulas for the stiffness adjustment coefficient and the damping adjustment coefficient in Step M5 are: Among them, TG0 u Indicates the stiffness adjustment coefficient, ZN0 u Indicates the damping adjustment factor.

10. The control model construction method based on the intelligent suspension system according to claim 1, characterized in that: in, The vertical acceleration of the vehicle body is obtained by installing an acceleration sensor at the center of mass of the vehicle body; the vertical displacement of the wheel is obtained by installing a displacement sensor on the wheel suspension component.

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