Self-adaptive suspension control system for vehicle

Abstract

The invention discloses a self-adaptive suspension control system for a vehicle, relates to the technical field of suspension control, solves the problem that the hardness of a suspension is not adjusted in advance by analyzing a road surface in front of the vehicle, and ensures that the dynamic change of the road surface can be captured in time by monitoring an image of the road surface in front of the vehicle in real time. Images are accurately screened and analyzed according to the set definition, valuable low-definition areas are removed, the subsequent invalid data processing amount is greatly reduced, and the system operation efficiency is improved; the road surface actual measurement processing end utilizes an image pixel value and gradient feature algorithm to construct a calibration model surface in detail and fully considers details of each point position of the image, so that the actual condition of the road surface can be accurately restored, a solid foundation is laid for subsequent accurate control, and a vehicle is enabled to know each fluctuation of the road surface in advance to improve the road surface quality. The real-time and accurate digital presentation of the front road condition is realized, the instantaneous bounce speed of the wheel is monitored in real time, the operation process is dynamically fused, and the execution parameter is finely adjusted in real time.

Description

Technical Field

[0001] The invention relates to the technical field of suspension control, in particular to an adaptive suspension control system for a vehicle. Background Art

[0002] The vehicle suspension is one of the important chassis components of the car. It plays a key role in connecting the body and wheels, buffering road impact, and ensuring vehicle handling stability and ride comfort. From the perspective of structural composition, the common suspension system mainly includes elastic elements, shock absorbers, and guide mechanisms. Elastic elements such as coil springs, leaf springs, and air springs are responsible for bearing and buffering the vertical impact force from the road. Coil springs use their own elastic deformation ability to be compressed when the vehicle passes over potholes, absorb energy, and prevent the body from being subjected to severe vibration. The shock absorber works in conjunction with the elastic element, mostly in the form of hydraulic or pneumatic damping. It can quickly consume the energy in the process of spring compression and rebound, prevent the vehicle from continuous bumps and oscillations, and ensure that the wheel quickly returns to a normal ground-attached state. The guide mechanism is generally composed of various connecting rods and swing arms, which accurately control the movement trajectory of the wheel, ensure that the wheel always maintains the correct angle and position relationship according to the design requirements under conditions such as bouncing, vehicle steering, and braking, and maintain the stability of the vehicle.

[0003] The application with publication number CN104709025B discloses a road-adaptive hydraulic active suspension system, including an active suspension with variable stiffness and damping, a hydraulic system and a control system; the active suspension includes a variable damping shock absorber, a variable stiffness spring and a hydraulic actuator; the control system includes an electronic control unit and a number of sensors for testing the vehicle status; the suspension system can automatically control the suspension stiffness and damping at the same time to achieve good driving smoothness and handling stability of the whole vehicle; the control system has a fast response speed; the vehicle height can be adaptively or manually adjusted to improve the vehicle's passability; the structure and control strategy are simple, the operation is stable, and the service life is long; and when the active suspension components fail, the vehicle performance is the same as the traditional passive suspension system and can still be driven normally.

[0004] During the control process of the vehicle suspension, the hardness of the suspension needs to be controlled in real time based on the corresponding wheel vibration to ensure the comfort of the driver in the car. However, in the actual processing process, the road surface analysis of the road ahead is not performed. Instead, the damping force or air pressure is adjusted based on the wheel vibration, which will cause vibration in the initial stage of adjustment. If the road surface analysis can be performed in advance and the optimal suspension hardness can be determined in advance, the driving experience of the corresponding driver can be guaranteed and his comfort can be improved. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides an adaptive suspension control system for a vehicle, which solves the problem of adjusting the suspension hardness in advance without analyzing the road surface ahead.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A vehicle adaptive suspension control system, comprising:

[0007] The visual monitoring end monitors the road surface image associated with the front of the vehicle in real time, and transmits the real-time monitored road surface image to the road surface measurement processing end;

[0008] At the road measurement processing end, an analysis image is selected from the monitored road image, and based on the different pixel values ​​associated with different points in the analysis image, the gradient features associated with the corresponding points are confirmed. Then, a standard area is selected from the analysis image, and based on the different spatial position features associated with different pixels in the standard area, the spatial position features of other pixels are confirmed in turn to generate a calibration model surface associated with the corresponding analysis image. The specific method is as follows:

[0009] Based on the monitored road surface image, the area with clarity ≥ Y1 in the road surface image is confirmed, and the confirmed area image is calibrated as the analysis image, where Y1 is a preset value, and its specific value is determined by the operator based on experience;

[0010] The different pixel values ​​associated with different points in the image are confirmed from the determined analysis image, and the different pixel values ​​associated with different points are calibrated as X i , where i represents different points. A group of points are randomly selected as the center point. Other points adjacent to the center point are marked as adjacent points. The pixel values ​​associated with the adjacent points are recorded. The pixel values ​​of the center point and the adjacent points are sorted as follows: Among them, H1-H8 represent the pixel values ​​associated with the adjacent points around the center point;

[0011] Using ZX i =(-1)×H1+0×H2+1×H3+(-2)×H4+0×X i +2×H5+(-1)×H6+0×H7+1×H8 confirms the vertical gradient ZX associated with this center point i ;

[0012] Adopt ZY i =(-1)×H1+(-2)×H2+(-1)×H3+0×H4+0×X i +0×H5+1×H6+2×H7+1×H8 confirms the horizontal gradient ZY associated with this center point i ;

[0013] use Determine the gradient feature G associated with this center point i ;

[0014] In the confirmed analysis image, a set of circles with a radius of 2m is generated with the center point of the vehicle as the center, and the specific area belonging to the circle is identified from the analysis image, and the specific area is marked as the standard area;

[0015] Based on the different gradient features associated with different points in the standard area, the spatial position features associated with the corresponding points are confirmed, the gradient feature differences between adjacent points and the height differences of the spatial position features are identified, and the associated height difference values ​​are calibrated as J i , and the associated gradient feature difference value is calibrated as Gz i , using J i ÷Gz i =TZ i Identify its associated features;

[0016] Based on the confirmed associated features, starting from the determined specific area, point confirmation is performed outwards. Based on the difference in gradient features of adjacent points, the difference in spatial position features is locked, thereby confirming the spatial position features of the corresponding adjacent points. The spatial position features of the adjacent points outside the specific area are specifically confirmed, and so on and so forth, to complete the construction of the entire analysis image calibration model surface;

[0017] The road surface characteristic determination end confirms the height of the point on the determined calibration model surface based on the preset reference plane, determines the road surface characteristic value from the confirmed groups of height values, and transmits the determined road surface characteristic value to the stiffness parameter selection end, specifically in the following manner:

[0018] Based on the determined calibration model surface and the preset reference plane, the reference plane is a preset plane parallel to the vehicle chassis;

[0019] Confirm the vertical heights between different points in the calibration model surface and the reference plane, and average several groups of vertical heights confirmed by several different points to confirm the characteristic mean, using: characteristic mean - X1 = road surface characteristic value, confirm the road surface characteristic value belonging to this calibration model surface, where X1 is a preset value, and transmit the determined road surface characteristic value to the stiffness parameter selection end;

[0020] The stiffness parameter selection end, based on the determined road surface characteristic value, locks the damping force or air pressure associated with the road surface characteristic value from a preset characteristic table, and calibrates the locked damping force or air pressure as the stiffness parameter;

[0021] The real-time control end determines the execution parameters of the corresponding suspension based on the instantaneous bounce speed of the corresponding wheel monitored in real time and the selected stiffness parameters, and performs real-time control. The specific method is as follows:

[0022] The instantaneous bounce speed of the corresponding wheel is calibrated as V k , where k represents different wheels;

[0023] Using (V k -Bz)×C1+stiffness parameter=execution parameter, where C1 is a preset fixed coefficient factor, which corresponds to the selected stiffness parameter one by one, different stiffness parameters correspond to different standard spring-up speeds Bz, and the standard speed Bz is extracted from the preset feature table;

[0024] Based on the determined execution parameters, the spring component of the suspension associated with the current vehicle is confirmed, and the working parameters of the spring component are adjusted to the execution parameters to complete the overall control of the suspension associated with the corresponding wheel.

[0025] Preferably, the visual monitoring terminal monitors and acquires road surface images once every 2 seconds.

[0026] Preferably, the preset characteristic table stores different damping forces or air pressures corresponding to different road surface characteristic values, which can be directly selected by the stiffness parameter selection end, and different damping forces or air pressures correspond to different standard bounce speeds.

[0027] Preferably, it also includes: a real-time monitoring terminal, which monitors the instantaneous bounce speed of the wheels of the moving vehicle and transmits the real-time monitored instantaneous bounce speed to the real-time control terminal.

[0028] The present invention provides an adaptive suspension control system for a vehicle. Compared with the prior art, the present invention has the following beneficial effects:

[0029] Real-time monitoring of the road image ahead of the vehicle ensures that dynamic changes in the road surface can be captured in a timely manner, and the image is accurately screened and analyzed according to the set definition, and the worthless low-definition areas are eliminated, which greatly reduces the amount of subsequent invalid data processing and improves the system operation efficiency. The road measurement processing end uses the image pixel value and gradient feature algorithm to meticulously construct the calibration model surface, fully considering the details of each point in the image, which can not only accurately restore the actual road condition, but also lay a solid foundation for subsequent precise control, so that the vehicle seems to know every ups and downs of the road in advance, and realizes a nearly real-time and accurate digital presentation of the road conditions ahead;

[0030] The instantaneous bounce speed of the wheel is monitored in real time, dynamically integrated into the calculation process, and the execution parameters are fine-tuned in real time. No matter how sudden the road surface changes, it can respond quickly and accurately adjust the working parameters of the spring parts to keep the vehicle in a stable and comfortable driving posture at all times. It not only avoids the violent shaking of the car body caused by road bumps and ensures ride comfort, but also optimizes the suspension stiffness under conditions such as high-speed driving and turning, ensures that the tires fit closely to the road surface, enhances handling stability, and improves the vehicle's driving quality in all aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the principle framework of the present invention;

[0032] Figure 2 Schematic diagram for determining execution parameters of the present invention. DETAILED DESCRIPTION

[0033] 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.

[0034] First embodiment

[0035] See also Figure 1 The present application provides an adaptive suspension control system for a vehicle, comprising: a visual monitoring end, a road surface measurement processing end, a road surface feature determination end, a stiffness parameter selection end, a real-time control end, and a real-time monitoring end, wherein the visual monitoring end is electrically connected to an input node of the road surface measurement processing end, and the road surface measurement processing end is electrically connected to an input node of the road surface feature determination end, and the road surface feature determination end, the stiffness parameter selection end, and the real-time control end are all electrically connected from an output node to an input node, and the real-time monitoring end is electrically connected to an input node of the real-time control end;

[0036] Among them, the visual monitoring end monitors the road surface image associated with the front of the vehicle in real time, and transmits the real-time monitored road surface image to the road surface measurement processing end, wherein the road surface image is monitored and acquired once every 2 seconds, and the 2 seconds is not a fixed value, and its specific value can be prepared in advance by the relevant operator, and the maximum shall not exceed 5 seconds. In addition, the road surface length monitored by the corresponding probe is limited. Based on the set clarity, the picture that meets the specified clarity will be used as the monitored analysis image;

[0037] Among them, the road surface measurement processing end selects an analysis image from the monitored road surface image, and based on the different pixel values ​​associated with different points in the analysis image, confirms the gradient features associated with the corresponding points, and then selects a standard area from the analysis image. Based on the different spatial position features associated with different pixel points in the standard area, the spatial position features of other pixel points are confirmed in turn to generate a calibration model surface associated with the corresponding analysis image. Specifically, when the corresponding camera acquires the picture, it will acquire some specific areas with low clarity. Such areas do not have any analysis value during image analysis, so such images need to be eliminated;

[0038] The specific method of generating the calibration model surface is as follows:

[0039] Based on the monitored road surface image, the area with clarity ≥ Y1 in the road surface image is confirmed, and the confirmed area image is calibrated as the analysis image, where Y1 is a preset value, and its specific value is determined by the operator based on experience;

[0040] The different pixel values ​​associated with different points in the image are confirmed from the determined analysis image, and the different pixel values ​​associated with different points are calibrated as X i , where i represents different points. A group of points are randomly selected as the center point. Other points adjacent to the center point are marked as adjacent points. The pixel values ​​associated with the adjacent points are recorded. The pixel values ​​of the center point and the adjacent points are sorted as follows: Among them, H1-H8 represent the pixel values ​​associated with the adjacent points around the center point;

[0041] Using ZX i =(-1)×H1+0×H2+1×H3+(-2)×H4+0×X i +2×H5+(-1)×H6+0×H7+1×H8 confirms the vertical gradient ZX associated with this center point i ;

[0042] Adopt ZY i =(-1)×H1+(-2)×H2+(-1)×H3+0×H4+0×X i +0×H5+1×H6+2×H7+1×H8 confirms the horizontal gradient ZY associated with this center point i ;

[0043] use Determine the gradient feature G associated with this center point i ;

[0044] In the confirmed analysis image, a set of circles with a radius of 2m is generated with the center point of the vehicle as the center, and the specific area belonging to the circle is identified from the analysis image, and the specific area is marked as the standard area;

[0045] Based on the different gradient features associated with different points in the standard area, the spatial position features associated with the corresponding points are confirmed, the gradient feature differences between adjacent points and the height differences of the spatial position features are identified, and the associated height difference values ​​are calibrated as J i , and the associated gradient feature difference value is calibrated as Gz i , using J i ÷Gz i =TZ i Identify its associated features;

[0046] Based on the confirmed associated features, starting from the determined specific area, point confirmation is performed outwards. Based on the difference in gradient features of adjacent points, the difference in spatial position features is locked, thereby confirming the spatial position features of the corresponding adjacent points. The spatial position features of the adjacent points outside the specific area are specifically confirmed, and so on, to complete the construction of the entire analysis image calibration model surface. The close-up picture can directly confirm its height features. When determining its spatial position height, the standard horizontal plane preset in the vehicle system is used as a reference. The acquired analysis image is placed above the preset standard horizontal plane, and the spatial position height associated with the corresponding point can be locked.

[0047] Specifically, since the road surface area close to the vehicle body can be directly confirmed numerically, the corresponding points and the associated specific height features can be directly confirmed, so that the corresponding standard features can be confirmed. Subsequently, based on the different gradient features associated with different points, the feature parameters associated with each different pixel point can be locked, and the corresponding virtual plane can be constructed based on the spatial position of the corresponding point and the associated height features, thereby determining the corresponding calibration model surface.

[0048] Second embodiment

[0049] In the specific implementation process, compared with the above-mentioned embodiment, this embodiment mainly focuses on the specific control of the vehicle suspension, and specifically determines the numerical parameters based on the corresponding calibration model surface confirmed in the first embodiment. The specific execution end includes the subsequent road surface feature determination end, the stiffness parameter selection end, the real-time control end and the real-time monitoring end.

[0050] The road surface characteristic determination end confirms the height of the point on the determined calibration model surface based on the preset reference plane, determines the road surface characteristic value from the confirmed groups of height values, and transmits the determined road surface characteristic value to the stiffness parameter selection end, wherein the specific method of determining the road surface characteristic value is:

[0051] Based on the determined calibration model surface and the preset reference plane, the reference plane is a preset plane parallel to the vehicle chassis;

[0052] Confirm the vertical heights between different points in the calibration model surface and the reference plane, and average several groups of vertical heights confirmed by several different points to confirm the characteristic mean, using: characteristic mean - X1 = road surface characteristic value, confirm the road surface characteristic value belonging to this calibration model surface, where X1 is a preset value, generally the height of the vehicle chassis from the horizontal ground, which is prepared in advance by relevant operators, and the determined road surface characteristic value is transmitted to the stiffness parameter selection end;

[0053] Specifically, the road surface characteristic value is the concave and convex condition of the internal points of the calibration model surface. When the specific parameters of the concave and convex are too different, the determined road surface characteristic value will be larger. Similarly, when the height difference of the corresponding concave and convex plane is too large, the corresponding road surface characteristic value will be larger. The greater the difference, the more uneven the corresponding model surface is.

[0054] Among them, the stiffness parameter selection end, based on the determined road surface characteristic value, locks the damping force or air pressure associated with this road surface characteristic value from the preset characteristic table (wherein the damping force corresponds to a normal shock absorber, and the adjustment of the damping force can be achieved by changing the size of the oil flow channel inside the shock absorber or by electromagnetic, hydraulic and other methods, and the air pressure corresponds to an air spring, and the overall strength of the corresponding shock absorber is determined by changing the air pressure strength inside the air spring), calibrates the locked damping force or air pressure as a stiffness parameter, and transmits the calibrated stiffness parameter to the real-time control end;

[0055] The preset characteristic table is prepared in advance by relevant operators, and different damping forces or air pressures corresponding to different road surface characteristic values ​​are stored therein, which can be directly selected from the stiffness parameter selection end, and different damping forces or air pressures correspond to different standard bounce speeds.

[0056] The real-time monitoring end monitors the instantaneous bounce speed of the wheels of the moving vehicle, and transmits the instantaneous bounce speed monitored in real time to the real-time control end;

[0057] Among them, combined Figure 2 The real-time control end determines the execution parameters of the corresponding suspension based on the instantaneous bounce speed of the corresponding wheel monitored in real time and the selected stiffness parameters, and performs real-time control, wherein the specific method of determining the execution parameters of the corresponding suspension is:

[0058] The instantaneous bounce speed of the corresponding wheel is calibrated as V k , where k represents different wheels;

[0059] Using (V k -Bz)×C1+stiffness parameter=execution parameter, where C1 is a preset fixed coefficient factor, which is formulated by relevant operators based on experience, where Bz is a preset standard pop-up speed, which corresponds to the selected stiffness parameter one by one, and different stiffness parameters correspond to different standard pop-up speeds Bz, and the standard speed Bz is extracted from a preset feature table. Specifically, due to the existence of different uneven areas in the corresponding area, the determined stiffness parameter is only an intermediate parameter. In order to make the control process more accurate and achieve better control effects, the instantaneous pop-up speed is monitored in real time, and real-time regulation is performed, and the stiffness parameter is adjusted in real time to achieve a more accurate buffer control effect;

[0060] Based on the determined execution parameters, the spring component of the suspension associated with the current vehicle is confirmed, and the working parameters of the spring component are adjusted to the execution parameters to complete the overall control of the suspension associated with the corresponding wheel.

[0061] Third embodiment

[0062] The specific implementation process of this embodiment includes all the implementation processes of the above two groups of embodiments.

[0063] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0064] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An adaptive suspension control system for a vehicle, characterized in that: include: The visual monitoring end monitors the road surface image associated with the front of the vehicle in real time, and transmits the real-time monitored road surface image to the road surface measurement processing end; At the road measurement processing end, an analysis image is selected from the monitored road surface image, and based on the different pixel values ​​associated with different points in the analysis image, the gradient features associated with the corresponding points are confirmed, and then a standard area is selected from the analysis image, and based on the different spatial position features associated with different pixel points in the standard area, the spatial position features of other pixel points are confirmed in turn to generate a calibration model surface associated with the corresponding analysis image; The road surface characteristic determination end confirms the height of the point on the determined calibration model surface based on the preset reference plane, determines the road surface characteristic value from the confirmed groups of height values, and transmits the determined road surface characteristic value to the stiffness parameter selection end; The stiffness parameter selection end, based on the determined road surface characteristic value, locks the damping force or air pressure associated with the road surface characteristic value from a preset characteristic table, and calibrates the locked damping force or air pressure as the stiffness parameter; The real-time control end determines the execution parameters of the corresponding suspension based on the instantaneous bounce speed of the corresponding wheel monitored in real time and the selected stiffness parameters, and performs real-time control.

2. The vehicle adaptive suspension control system according to claim 1, characterized in that: The visual monitoring terminal monitors and acquires road surface images once every 2 seconds.

3. The vehicle adaptive suspension control system according to claim 1, characterized in that: The specific method of confirming the gradient characteristics associated with the corresponding points at the road surface measurement processing end is: Based on the monitored road surface image, the area with clarity ≥ Y1 in the road surface image is confirmed, and the confirmed area image is calibrated as the analysis image, where Y1 is a preset value, and its specific value is determined by the operator based on experience; The different pixel values ​​associated with different points in the image are confirmed from the determined analysis image, and the different pixel values ​​associated with different points are calibrated as X i , where i represents different points. A group of points are randomly selected as the center point. Other points adjacent to the center point are marked as adjacent points. The pixel values ​​associated with the adjacent points are recorded. The pixel values ​​of the center point and the adjacent points are sorted as follows: Among them, H1-H8 represent the pixel values ​​associated with the adjacent points around the center point; Using ZX i =(-1)×H1+0×H2+1×H3+(-2)×H4+0×X i +2×H5+(-1)×H6+0×H7+1×H8 confirms the vertical gradient ZX associated with this center point i ; Adopt ZY i =(-1)×H1+(-2)×H2+(-1)×H3+0×H4+0×X i +0×H5+1×H6+2×H7+1×H8 confirms the horizontal gradient ZY associated with this center point i ; use Determine the gradient feature G associated with this center point i .

4. The vehicle adaptive suspension control system according to claim 3, characterized in that: The specific method of generating the calibration model surface at the road surface measurement processing end is as follows: In the confirmed analysis image, a set of circles with a radius of 2m is generated with the center point of the vehicle as the center, and the specific area belonging to the circle is identified from the analysis image, and the specific area is marked as the standard area; Based on the different gradient features associated with different points in the standard area, the spatial position features associated with the corresponding points are confirmed, the gradient feature differences between adjacent points and the height differences of the spatial position features are identified, and the associated height difference values ​​are calibrated as J i , and the associated gradient feature difference value is calibrated as Gz i , using J i ÷Gz i =TZ i Identify its associated features; Based on the confirmed associated features, starting from the determined specific area, point confirmation is carried out outwards. Based on the difference in gradient features of adjacent points, the difference in spatial position features is locked, thereby confirming the spatial position features of the corresponding adjacent points. The spatial position features of the adjacent points outside the specific area are specifically confirmed, and so on, to complete the construction of the entire analysis image calibration model surface.

5. The vehicle adaptive suspension control system according to claim 4, characterized in that: The road surface characteristic determination end determines the road surface characteristic value in a specific manner as follows: Based on the determined calibration model surface and the preset reference plane, the reference plane is a preset plane parallel to the vehicle chassis; Confirm the vertical heights between different points on the calibration model surface and the reference plane, and average several groups of vertical heights confirmed at several different points to confirm the characteristic mean. Use: characteristic mean - X1 = pavement characteristic value to confirm the pavement characteristic value belonging to this calibration model surface, where X1 is a preset value, and transmit the determined pavement characteristic value to the stiffness parameter selection end.

6. The vehicle adaptive suspension control system according to claim 1, characterized in that: The preset characteristic table stores different damping forces or air pressures corresponding to different road surface characteristic values, which can be directly selected by the stiffness parameter selection end, and different damping forces or air pressures correspond to different standard spring-up speeds.

7. The vehicle adaptive suspension control system according to claim 6, characterized in that: Also includes: The real-time monitoring end monitors the instantaneous bounce speed of the wheels of the moving vehicle, and transmits the real-time monitored instantaneous bounce speed to the real-time control end.

8. The vehicle adaptive suspension control system according to claim 7, characterized in that: The specific method of determining the corresponding suspension execution parameter by the real-time control end is: The instantaneous bounce speed of the corresponding wheel is calibrated as V k , where k represents different wheels; Using (V k -Bz)×C1+stiffness parameter=execution parameter, where C1 is a preset fixed coefficient factor, which corresponds to the selected stiffness parameter one by one, different stiffness parameters correspond to different standard spring-up speeds Bz, and the standard speed Bz is extracted from the preset feature table; Based on the determined execution parameters, the spring component of the suspension associated with the current vehicle is confirmed, and the working parameters of the spring component are adjusted to the execution parameters to complete the overall control of the suspension associated with the corresponding wheel.

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