Wheel alignment parameter adjustment method and adjustment device

Abstract

A wheel alignment parameter adjusting method and adjusting device, relate to vehicle technical field, the wheel alignment parameter adjusting method includes the following steps: acquire "driving condition-actuator arrangement point-optimal target hard point coordinate-optimal wheel alignment parameter" contrast table through preposition simulation test;Determine the optimal target hard point coordinate and optimal wheel alignment parameter corresponding to the current driving condition and actuator arrangement point through table lookup;Control actuator output adjustment instruction and adjust the spatial position of target hard point to optimal target hard point coordinate, thereby indirectly adjust the current wheel alignment parameter of suspension system to optimal wheel alignment parameter.The present application can continuously and actively adjust the wheel alignment parameters such as real camber angle, toe angle, kingpin camber angle and kingpin caster angle for different driving conditions, which has high flexibility, large adjustment range and is beneficial to improve the driving stability of the vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, in particular to a wheel alignment parameter adjustment method and adjustment device. BACKGROUND

[0002] During vehicle driving, if the wheel alignment parameters are incorrect, abnormal wheel wear and driving deviation will occur. In an independent suspension, there are many parts and the size chain is also complex. If the size accuracy of each part is too high, the cost will increase. In order to reduce the cost, most products on the market reduce the size accuracy of parts. However, due to the cumulative tolerance between parts, the wheel alignment parameters such as camber angle and caster angle of the vehicle may not meet the use requirements of the vehicle after the independent suspension is assembled. At the same time, the wheel alignment parameters change after the vehicle is used for a period of time, so many independent suspensions in the prior art are provided with a vehicle alignment parameter adjustment mechanism to compensate and correct the wheel alignment parameters.

[0003] The invention patent with publication number CN115923933A discloses a camber angle dynamic adjustment device, which comprises a connecting rod mechanism, a driving member and a camber angle control arm. The connecting rod mechanism comprises a driving connecting rod, a driven connecting rod and a bracket. When the driving member drives one end of the driving connecting rod to move in the width direction of the vehicle body, the driven connecting rod can be driven to rotate around the bracket as the center, so as to drive the camber angle control arm to move through the other end of the driven connecting rod, so as to achieve the purpose of adjusting the camber angle of the vehicle.

[0004] However, the scheme has the following deficiencies: first, the scheme can only adjust the camber angle of the vehicle, and cannot adjust other wheel alignment parameters such as toe angle, kingpin inclination angle or caster angle, so there is a great limitation; second, the scheme has a complex structure and occupies a large space, which is not conducive to vehicle layout; third, the scheme uses a connecting rod mechanism to drive the driving member and the camber angle control arm, which has the problems of low structural strength and poor reliability. SUMMARY

[0005] The present application provides a wheel alignment parameter adjustment method and adjustment device, which mainly aims to solve the problems of limited adjustment function, complex structure, large space occupation and low structural strength of the existing vehicle alignment parameter adjustment mechanism.

[0006] The present application adopts the following technical scheme:

[0007] A wheel alignment parameter adjustment method comprises the following steps:

[0008] S1. Obtaining optimal target hard point coordinates and optimal wheel alignment parameters for the actuator at different layout points and under different driving conditions through pre-simulation tests, and developing a "driving condition-actuator layout point-optimal target hard point coordinates-optimal wheel alignment parameters" comparison table, which is stored in a control database of the actuator; the actuator layout points include four target hard points of the suspension system: the upper control arm front ball joint, the upper control arm rear ball joint, the lower control arm front ball joint, and the lower control arm rear ball joint;

[0009] S2. When there is a need to adjust the wheel alignment parameters, the current driving condition of the vehicle and the actuator arrangement points of the suspension system are obtained, and the optimal target hard point coordinates and optimal wheel alignment parameters corresponding to the current driving condition and actuator arrangement points are determined by querying a comparison table of "driving condition - actuator arrangement points - optimal target hard point coordinates - optimal wheel alignment parameters";

[0010] S3. Controlling the actuator to output an adjustment instruction based on the optimal target hard point coordinates and optimal wheel alignment parameters obtained from the table to adjust the spatial position of the target hard point to the optimal target hard point coordinates, thereby indirectly adjusting the current wheel alignment parameters of the suspension system to the optimal wheel alignment parameters.

[0011] Furthermore, in step S1, the pre-simulation test includes the following steps:

[0012] S11. Select the four wheel alignment parameters of camber, toe, kingpin inclination and caster as the objective function, and use the comfort experience judgment value F of the whole vehicle as the evaluation standard to build a multi-objective function prediction model to obtain the minimum comfort experience judgment value F under different driving conditions. min The calculation formula of the multi-objective function prediction model for the corresponding optimal wheel alignment parameters is:

[0013] F min =w a *|Δf a -a i |+w b *|Δf b -b i |+w c *|Δf c -c i |+w d *|Δf d -d i Where: W a is the weight of the camber angle; Δf a is the empirical value of the camber angle; a i is the optimal value of the camber angle; W b is the weight of the toe angle; Δf b is the empirical value of the toe angle; b iis the optimal value of the camber angle; W c is the weight of the kingpin inclination angle; Δf c is the experience value of the kingpin inclination angle; c i is the optimal value of the kingpin inclination angle; Δf d is the experience value of the kingpin inclination angle; d i is the optimal value of the kingpin inclination angle;

[0014] S12, simulate different driving conditions by a whole vehicle dynamics model, take the camber angle, toe angle, kingpin inclination angle and kingpin inclination angle as control targets, adjust the spatial position of the target hard point by an actuator until the four wheel positioning parameters are all adjusted to the optimal wheel positioning parameters, record the coordinates of the target hard point at this time as the optimal target hard point coordinates, and make a "driving condition-actuator arrangement point-optimal target hard point coordinates-optimal wheel positioning parameters" table.

[0015] Further, in step S11, the ADAMS / car software is used to build a whole vehicle dynamics model for simulation test, and the upper limit value m i and the lower limit value n i of each target function in a reasonable range are confirmed, so as to obtain the corresponding tolerance value Δf i and weight w i :

[0016] m i ≤f i (x)≤n i

[0017] Δf i (x)=(n i -m i ) / 2

[0018] w i =1 / [Δf i (x)] 2 .

[0019] Further, in step S11, the OPTDES-SQP algorithm is used to iteratively optimize the multi-target function prediction model, so as to obtain the optimal wheel positioning parameters corresponding to the minimum comfort experience evaluation value F min under different driving conditions.

[0020] Further, in step S12, the ADAMS / insight software is used to build a whole vehicle dynamics model to simulate different driving conditions, and adjust the target hard point coordinates and the wheel positioning parameters.

[0021] Further, in step S2, the selection method of the actuator arrangement point is: first, the

[0022] ADAMS / view software builds a suspension model, and then respectively arranges actuators at four hard points of the upper control arm front ball joint, the upper control arm rear ball joint, the lower control arm front ball joint and the lower control arm rear ball joint, and carries out sensitivity simulation test on each hard point, and finally selects the hard point with the largest sensitivity value as the target hard point.

[0023] Further, in the sensitivity simulation test process, the coordinates of each hard point are adjusted by the actuators, so as to judge the influence of the coordinate variables of each hard point on the wheel positioning parameters, and the greater the influence of the coordinate variables of each hard point on the wheel positioning parameters, the higher the sensitivity value of the hard point.

[0024] Further, in step S3, a fuzzy PI control algorithm is used in the adjustment process to form a closed loop control, so as to ensure that the current wheel positioning parameters are adjusted to the optimal wheel positioning parameters.

[0025] A wheel positioning parameter adjusting device comprises the actuator as described above, the actuator comprises a driving motor, a speed reduction mechanism, an eccentric mechanism and a fixed support, the driving motor is transmissionally connected to the speed reduction mechanism, the eccentric mechanism comprises a cam, the cam is connected to the vehicle frame through the fixed support, and the ball joint shaft of the target hard point is eccentrically connected between the speed reduction mechanism and the cam; the ball joint shaft is driven to make eccentric motion by the actuator, so as to adjust the spatial position of the target hard point.

[0026] Further, the speed reduction mechanism comprises a primary speed reduction mechanism and a secondary speed reduction mechanism; the primary speed reduction mechanism comprises gear one and gear two which are meshed with each other, the gear one is arranged on the output shaft of the driving motor; the secondary speed reduction mechanism comprises a worm and a turbine which are meshed with each other, the worm is coaxial with the gear two, and the two ends of the ball joint shaft are eccentrically matched with the turbine and the cam respectively.

[0027] Compared with the prior art, the present application has the following beneficial effects:

[0028] 1. The wheel positioning parameter adjusting method provided by the present application can continuously and actively adjust the wheel positioning parameters such as real camber angle, toe angle, kingpin camber angle and kingpin caster angle according to different driving conditions, has high flexibility, large adjustment range and strong universality, and is beneficial to improving the driving stability of the vehicle.

[0029] 2、The actuator provided by the application adopts the form of driving motor + mechanical transmission combination, and can be seamlessly connected with the electric control chassis due to the motor driving mode, which meets the electric and intelligent trend of the automobile chassis; due to the independent mechanical transmission mode, even if the actuator fails, it will not affect the safe driving of the vehicle, and the redundancy is high. In addition, the actuator has the advantages of simple structure, small size, low weight and high integration, and the actuator is fixed on the vehicle body, which does not increase the unsprung mass, and the installation position is more flexible. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 It is a schematic diagram of the suspension system in the application.

[0031] Figure 2 It is a schematic diagram of the suspension system and the actuator in the application.

[0032] Figure 3 It is a schematic diagram of the structure of the actuator in the application.

[0033] Figure 4 It is a schematic diagram of the cross section of the suspension system and the actuator in the application.

[0034] Figure 5 It is a control algorithm flowchart of the application.

[0035] In the figure: 1-suspension system; 11-upper control arm front spherical hinge; 12-upper control arm rear spherical hinge; 13-lower control arm front spherical hinge; 14-lower control arm rear spherical hinge; 15-spherical hinge shaft; 2-actuator; 21-driving motor; 22-gear one; 23-gear two; 24-worm; 25-turbine; 26-cam; 27-fixed support. DETAILED DESCRIPTION

[0036] The specific embodiments of the application will be described below with reference to the accompanying drawings. In order to fully understand the application, many details are described below, but the application can be implemented without these details for those skilled in the art.

[0037] As Figures 1 to 5 shown, the embodiment provides a suspension wheel alignment parameter adjusting method, which comprises the following steps:

[0038] S1, obtain the optimal target hard point coordinates and the optimal wheel alignment parameters of the actuator under different arrangement points and different driving conditions through pre-position simulation test, and make a "driving condition-actuator arrangement point-optimal target hard point coordinates-optimal wheel alignment parameter" table stored in the control database of the actuator 2; the actuator arrangement points include four target hard points of the upper control arm front spherical hinge 11, the upper control arm rear spherical hinge 12, the lower control arm front spherical hinge 13 and the lower control arm rear spherical hinge 14 of the suspension system 1.

[0039] The pre-simulation test in this step includes the following steps:

[0040] S11. Select the four wheel alignment parameters of camber, toe, kingpin inclination and caster as the objective function, and use the comfort experience judgment value F of the whole vehicle as the evaluation standard. Based on this, a multi-objective function prediction model is constructed to obtain the minimum comfort experience judgment value F under different driving conditions. min The calculation formula of the multi-objective function prediction model for the corresponding optimal wheel alignment parameters is:

[0041] F min =w a *|Δf a -a i |+w b *|Δf b -b i |+w c *|Δf c -c i |+w d *|Δf d -d i |

[0042] Where: W a is the weight of the camber angle; Δf a is the empirical value of the camber angle; a i is the optimal value of the camber angle; W b is the weight of the toe angle; Δf b is the empirical value of the toe angle; b i is the optimal value of the toe angle; W c is the weight of the kingpin inclination angle; Δf c is the empirical value of the kingpin inclination angle; c i The optimal value of the kingpin inclination angle; Δf d is the empirical value of the caster angle; d i The optimal value of the caster angle.

[0043] Specifically, in this step, ADAMS / car software is used to build a vehicle dynamics model to simulate the objective functions f during the up and down bouncing of the wheels. i (x) changes, thereby confirming the objective function f i (x) Upper limit value m within reasonable variation range i and the lower limit value n i . Further analysis of the objective function f i (x) Use weighted combination method to statistically analyze and determine the objective function f during the operation of actuator 2. i Tolerance value Δf of (x) i (x) and weight wi , the weight w i is larger, the greater the influence of the hard point coordinate change on the wheel parameter:

[0044] m i ≤f i (x)≤n i

[0045] Δf i (x)=(n i -m i ) / 2

[0046] w i =1 / [Δf i (x)] 2 .

[0047] The four parameters of the experience values Δf a , Δf b , Δf c and Δf d may be confirmed in combination with tests and real vehicle experiences, and are respectively used as initial values of the objective functions f i (x).

[0048] The OPTDES-SQP algorithm is used to iteratively optimize the multi-objective function prediction model, so as to obtain optimal wheel positioning parameters corresponding to the minimum comfort experience evaluation value F min under different driving conditions, i.e., optimal values of camber angle a i , toe angle b i , kingpin inclination angle c i and kingpin caster angle d i .

[0049] S12, the vehicle dynamics model is simulated under different driving conditions, the camber angle, toe angle, kingpin inclination angle and kingpin caster angle are used as control targets, the spatial position of the target hard point is adjusted by the actuator 2 until the four wheel positioning parameters are adjusted to the optimal wheel positioning parameters, the coordinates of the target hard point at this time are recorded as the optimal target hard point coordinates, and a "driving condition-actuator arrangement point-optimal target hard point coordinates-optimal wheel positioning parameters" table is prepared.

[0050] Specifically, this step uses ADAMS / insight software to build a whole vehicle dynamics model to simulate different driving conditions, and to adjust the target hard point coordinates and wheel alignment parameters, so as to sort out the optimal target hard point coordinates and optimal wheel alignment parameters of the actuator 2 under different arrangement points and different driving conditions, and to formulate a "driving condition-actuator arrangement point-optimal target hard point coordinate-optimal wheel alignment parameter" table stored in the control database of the actuator 2 as a reference standard for the output adjustment instruction of the actuator 2 in actual application.

[0051] More specifically, in the ADAMS / insight software, the test bench is set to apply ±80mm excitation to simulate the up and down movement of the wheel, and through the software, the change range of each target function value and the change amount of each hard point spatial coordinates x / y / z during the up and down movement of the wheel can be analyzed. According to the simulation test results, among the hard point spatial coordinates x / y / z, the sensitivity of the coordinates y / z to the target function is much greater than that of the x coordinate value, so the main sorting in this step is the optimal target hard point coordinates y / z and the optimal wheel alignment parameters of the actuator 2 under different arrangement points and different driving conditions.

[0052] S2, when there is a need to adjust the wheel alignment parameters, the current driving condition and the arrangement point of the actuator of the suspension system 1 are obtained, and the optimal target hard point coordinates and the optimal wheel alignment parameters corresponding to the current driving condition and the arrangement point of the actuator are determined by querying the "driving condition-actuator arrangement point-optimal target hard point coordinate-optimal wheel alignment parameter" table.

[0053] Specifically, in actual application, the selection method of the arrangement point of the actuator is as follows: first, the suspension model is built by using ADAMS / view software, then the actuator 2 is arranged at the four hard points of the upper control arm front spherical hinge 11, the upper control arm rear spherical hinge 12, the lower control arm front spherical hinge 13 and the lower control arm rear spherical hinge 14, and sensitivity simulation test is performed on each hard point, and finally the hard point with the largest sensitivity value is selected as the target hard point.

[0054] During the sensitivity simulation test, the coordinates of each hard point are taken as design variables, and the test bench is set to have ±80mm up and down movement, so that the design variables are adjusted by the actuator 2, and thus the influence of the design variables on the wheel alignment parameters is determined. The greater the influence of the design variables on the wheel alignment parameters, the higher the sensitivity value of the hard point, i.e. the hard point can be used as the target hard point to arrange the actuator 2.

[0055] According to the actual experience and sensitivity simulation test, the hard points that have greater influence on the wheel positioning parameters in the double-control-arm suspension system are the upper control arm front spherical hinge 11 and the upper control arm rear spherical hinge 12, and the sensitivity value of the upper control arm front spherical hinge 11 is slightly greater than that of the upper control arm rear spherical hinge 12. Therefore, the actuator is usually arranged at the upper control arm front spherical hinge 11 under normal circumstances. Of course, in actual application, a suitable actuator arrangement point can also be selected according to actual needs, and relevant data can be obtained by looking up the table.

[0056] S3, adjusting the spatial position of the target hard point to the optimal target hard point coordinate by controlling the actuator 2 to output an adjustment instruction according to the optimal target hard point coordinate and the optimal wheel positioning parameter obtained by looking up the table, so as to indirectly adjust the current wheel positioning parameter of the suspension system 1 to the optimal wheel positioning parameter.

[0057] Specifically, in this step, the vehicle roll angle is taken as the optimization target, and a fuzzy PI control algorithm is adopted to form a closed-loop control to adjust the spatial position of the target hard point, so as to ensure that the current wheel positioning parameter is adjusted to the optimal wheel positioning parameter, thereby improving the driving stability of the vehicle.

[0058] Through simulation experiments, it is found that the above-mentioned wheel positioning parameter adjustment method can continuously adjust the wheel positioning parameter of the suspension system 1, so that the adjustment ranges of the camber angle, the toe angle, the kingpin inclination angle and the kingpin caster angle can meet the vehicle working condition requirements. Among them, by continuously adjusting the camber angle and the toe angle of the wheel, the friction between the tire and the road surface can be greatly improved, and the tire lateral force support can be improved. The setting of the wheel toe angle can also be equivalent to the tire side slip angle, which further affects the size of the tire lateral force. Therefore, reasonably adjusting the camber angle and the toe angle of the wheel according to the vehicle working condition can significantly improve the roll stability of the vehicle when driving at high speed; by continuously adjusting the kingpin inclination angle of the automobile steering system, the suspension system lateral stiffness can be enhanced, and the roll angle when driving at high speed can be reduced; by continuously adjusting the kingpin caster angle of the automobile steering system, the stability of the vehicle when driving at high speed can be improved.

[0059] The wheel positioning parameter adjustment device involved in the above-mentioned wheel positioning parameter adjustment method is described in detail as follows:

[0060] As Figures 1 to 4As shown, the wheel alignment parameter adjusting device includes the actuator 2 involved in the wheel alignment parameter adjusting method as described above, the actuator 2 includes a driving motor 21, a speed reducer, an eccentric mechanism and a fixed support 27, the driving motor 21 is drivingly connected to the speed reducer, the eccentric mechanism includes a cam 26, the cam 26 is connected to the vehicle frame through the fixed support 27, and the spherical hinge shaft of the target hard point is eccentrically connected between the speed reducer and the cam 26. In operation, the actuator 2 monitors the vehicle driving condition in combination with the steering wheel angle sensor and the lateral acceleration sensor, drives the spherical hinge shaft to make eccentric movement by controlling the rotating speed and direction of the driving motor 21 and increasing the torque through the speed reducer, thereby adjusting the spatial position of the target hard point, and further continuously actively adjusting the camber angle, the toe angle, the kingpin inclination angle and the caster angle and other wheel alignment parameters.

[0061] As shown, Figures 1 to 4 The speed reducer includes a primary speed reducer and a secondary speed reducer. As a preferred solution, the primary speed reducer includes a gear one 22 and a gear two 23 which are meshed with each other, the gear one 22 is arranged on the output shaft of the driving motor 21; the secondary speed reducer includes a worm 24 and a turbine 25 which are meshed with each other, the worm 24 is coaxial with the gear two 23, and the two ends of the spherical hinge shaft 15 are eccentrically matched with the turbine 25 and the cam 26 respectively. The worm 24 and the turbine 25 are matched with each other to increase the torque and achieve reverse locking, thereby making the actuator 2 more stable and reliable.

[0062] The actuator 2 can use, but is not limited to, the branch oil circuit of the integrated lubrication system of the whole vehicle to lubricate the bearings and the speed reducer shafts in the actuator 2. The lubrication of the bearings can also be designed and developed in the structure of maintenance-free bearings.

[0063] For the road excitation in the driving process of the large-load vehicle, a large torque is generated at the suspension hard point where the control arm is connected to the vehicle body to resist the adjustment of the actuator 2. For this influence, a large-torque servo motor with locking function can be used to meet the dynamic suspension structure adjustment of the vehicle, or a gear locking mechanism can be used for static suspension structure adjustment of the vehicle.

[0064] As can be seen from the above, the actuator 2 provided by the embodiment adopts the form of driving motor 21 + mechanical transmission combination. Since the motor driving mode is adopted, the actuator 2 can be seamlessly connected to the electronic control chassis, which meets the electric and intelligent trend of the automobile chassis. Since the independent mechanical transmission mode is adopted, even if the actuator 2 fails, it will not affect the safe driving of the vehicle, and the redundancy is high. In addition, the actuator 2 has the advantages of simple structure, small size, low weight and high integration, and the actuator 2 is fixed on the vehicle body, which will not increase the unsprung mass, and the installation position is more flexible.

[0065] The above merely illustrates the specific embodiments of the present application, but the design concept of the present application is not limited thereto, and any non-essential modification of the present application by using the concept shall be deemed as the infringement of the protection scope of the present application.

Claims

1. A method of adjusting a wheel alignment parameter, characterized by: It comprises the following steps: S1, obtaining optimal target hard point coordinates and optimal wheel alignment parameters of the actuator under different arrangement points and different driving conditions through pre-simulation test, and formulating a "driving condition-actuator arrangement point-optimal target hard point coordinates-optimal wheel alignment parameter" table stored in the control database of the actuator; the actuator arrangement points include four target hard points of the front ball joint of the upper control arm, the rear ball joint of the upper control arm, the front ball joint of the lower control arm and the rear ball joint of the lower control arm of the suspension system; S2, when there is a wheel alignment parameter adjustment requirement, obtaining the current driving condition and the actuator arrangement point of the suspension system, and determining the optimal target hard point coordinates and the optimal wheel alignment parameter corresponding to the current driving condition and the actuator arrangement point through the "driving condition-actuator arrangement point-optimal target hard point coordinates-optimal wheel alignment parameter" table; S3, controlling the actuator to output adjustment instructions to adjust the spatial position of the target hard point to the optimal target hard point coordinates according to the optimal target hard point coordinates and the optimal wheel alignment parameter obtained by the table lookup, so as to indirectly adjust the current wheel alignment parameter of the suspension system to the optimal wheel alignment parameter.

2. A method of adjusting wheel alignment parameters according to claim 1, characterized in that: In step S1, the pre-simulation test comprises the following steps: S11, select the camber angle, toe angle, kingpin inclination angle and kingpin caster angle four wheel alignment parameters as the objective function, and take the comfort experience evaluation value F of the whole vehicle as the evaluation standard, construct a multi-objective function prediction model, and obtain the minimum comfort experience evaluation value F under different driving conditions min The calculation formula of the multi-objective function prediction model corresponding to the optimal wheel alignment parameters is: F min = w a * | Δf a - a i | + w b * | Δf b - b i | + w c * | Δf c - c i | + w d * | Δf d - d i | where: W a is the weight of camber; Δf a is the experience value of camber; a i is the optimal value of camber; W b is the weight of toe; Δf b is the experience value of toe; b i is the optimal value of toe; W c is the weight of kingpin inclination; Δf c is the experience value of kingpin inclination; c i is the optimal value of kingpin inclination; Δf d is the experience value of kingpin caster; d i is the optimal value of kingpin caster; S12, simulating different driving conditions through a whole vehicle dynamics model, taking the camber angle, toe angle, kingpin inclination angle and kingpin caster angle as control targets, adjusting the spatial position of the target hard point through the actuator until the four wheel alignment parameters are adjusted to the optimal wheel alignment parameters, recording the target hard point coordinates at this time as the optimal target hard point coordinates, and formulating a "driving condition-actuator arrangement point-optimal target hard point coordinates-optimal wheel alignment parameter" table.

3. A wheel alignment parameter adjustment method as claimed in claim 2, characterized in that: In step S11, the ADAMS / car software is used to build a whole vehicle dynamics model to perform simulation test, and to confirm the upper limit value m of each target function in a reasonable change range i and the lower limit value n i , so as to obtain the corresponding tolerance value Δf i and weight w i : m i ≤f i (x)≤n i Δf i (x) = (n i -m i ) / 2 w i = 1 / [Δf i (x)] 2 .

4. A method of adjusting wheel alignment parameters according to claim 2, wherein: In step S11, the OPTDES-SQP algorithm is used to iteratively optimize the multi-objective function prediction model, thereby obtaining the minimum comfort empirical evaluation value F under different driving conditions min The corresponding optimal wheel alignment parameters.

5. A method of adjusting wheel alignment parameters as set forth in claim 2, wherein: In step S12, the ADAMS / insight software is used to build a whole vehicle dynamics model to simulate different driving conditions and adjust the target hard point coordinates and the wheel alignment parameters.

6. A method of adjusting wheel alignment parameters as set forth in claim 1, wherein: In step S2, the selection method of the actuator arrangement point is: first, the ADAMS / view software is used to build a suspension model, then the actuator is arranged at the four hard points of the front ball joint of the upper control arm, the rear ball joint of the upper control arm, the front ball joint of the lower control arm and the rear ball joint of the lower control arm, and sensitivity simulation test is performed on each hard point, and finally the hard point with the largest sensitivity value is selected as the target hard point.

7. A method of adjusting wheel alignment parameters according to claim 6, characterized in that: During the sensitivity simulation test, the actuator is used to adjust the coordinates of each hard point, so as to judge the influence of each hard point coordinate variable on the wheel alignment parameters, and the greater the influence of the hard point coordinate variable on the wheel alignment parameters, the higher the sensitivity value of the hard point.

8. A method of adjusting wheel alignment parameters as defined in claim 1, wherein: In step S3, a fuzzy PI control algorithm is used to form a closed loop control during the adjustment process, so as to ensure that the current wheel alignment parameter is adjusted to the optimal wheel alignment parameter.

9. A wheel alignment parameter adjustment device, characterized by: The adjusting method of the wheel alignment parameters comprises the following steps: the adjusting method of the wheel alignment parameters is adopted by an actuator, the actuator comprises a driving motor, a speed reduction mechanism, an eccentric mechanism and a fixed support, the driving motor is connected to the speed reduction mechanism, the eccentric mechanism comprises a cam, the cam is connected to a vehicle frame through the fixed support, and a ball joint shaft of a target hard point is eccentrically connected between the speed reduction mechanism and the cam; the ball joint shaft is driven to make eccentric motion by the actuator, so as to adjust the spatial position of the target hard point.

10. A wheel alignment parameter adjustment device as in claim 9, wherein: The speed reduction mechanism comprises a first speed reduction mechanism and a second speed reduction mechanism; the first speed reduction mechanism comprises a gear one and a gear two which are engaged with each other, the gear one is arranged on an output shaft of the driving motor; the second speed reduction mechanism comprises a worm and a turbine which are engaged with each other, the worm is coaxial with the gear two, and two ends of the ball joint shaft are eccentrically matched with the turbine and the cam respectively.

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