Method for controlling the suspension of a vehicle by processing images from at least one on-board camera
10127650 ยท 2018-11-13
Assignee
Inventors
Cpc classification
B60R11/04
PERFORMING OPERATIONS; TRANSPORTING
B60R2300/303
PERFORMING OPERATIONS; TRANSPORTING
B60G2401/14
PERFORMING OPERATIONS; TRANSPORTING
B60G15/063
PERFORMING OPERATIONS; TRANSPORTING
H04N13/239
ELECTRICITY
B60G2202/322
PERFORMING OPERATIONS; TRANSPORTING
B60G11/16
PERFORMING OPERATIONS; TRANSPORTING
B60G2600/08
PERFORMING OPERATIONS; TRANSPORTING
B60G2400/824
PERFORMING OPERATIONS; TRANSPORTING
B60G17/019
PERFORMING OPERATIONS; TRANSPORTING
B60G17/016
PERFORMING OPERATIONS; TRANSPORTING
B60G17/0182
PERFORMING OPERATIONS; TRANSPORTING
B60G2202/312
PERFORMING OPERATIONS; TRANSPORTING
B60G2401/142
PERFORMING OPERATIONS; TRANSPORTING
International classification
B60G17/016
PERFORMING OPERATIONS; TRANSPORTING
B60G17/019
PERFORMING OPERATIONS; TRANSPORTING
B60G17/018
PERFORMING OPERATIONS; TRANSPORTING
B60R11/04
PERFORMING OPERATIONS; TRANSPORTING
H04N13/239
ELECTRICITY
Abstract
The disclosed method checks the state of degradation of the suspension of a vehicle without having to carry out tests that immobilize the vehicle or to use non-objective expertise. The method processes data provided by at least one front camera in an on-board visual system. The checking method includes steps for periodically acquiring images provided by the camera or cameras, followed by storage of the positional data of the three-dimensional road in relation to a flat road and basic positional parameter data for the path of the vehicle. The error between the ideal values of the suspension parameters of a chosen suspension model and the values of these parameters corresponding to the stored path data from the positional data is then minimized. By iteration, the accuracy of the error reaches a predetermined value sufficient to diagnose a state of the suspension.
Claims
1. A method for checking the state of degradation of a suspension system (10) fitted to a motor vehicle (1), comprising: periodically acquiring (210), by at least one camera (6, 7) of a visual system (60) carried on board the vehicle (1), successive images of a road (110) within a forward field of vision (Va) of the at least one camera, and storing said images of the road (110) in the form of pixels in a data storage; using image processing (220) to determine and store, from the stored pixels of the road (110) and from stored pixels of a flat reference road (100), positional data corresponding to relative values of a profile of the road (110) in relation to a linear profile of the reference road (100); determining and storing (230), from the stored pixels of the road (110), rotational and translational positional parameter data of the vehicle; using the determined relative positional data, the determined rotational and translational positional parameter data of the vehicle, and a speed of the vehicle to determine (235) a path (Ts) of the vehicle (1); carrying out and iterating a minimization function of an error (P.sup.2) between stored suspension parameter values (K, C) of an ideal model suspension and suspension parameter values corresponding to the determined path (Ts) until an accuracy of said error (P.sup.2) reaches a predetermined value .sub.R; and upon a value of the accuracy reaching the predetermined value .sub.R, diagnosing a state of the suspension (270) as a function of the error (P.sup.2) in order to trigger an alarm in the event of of a pre-critical suspension state.
2. The method for checking the state of a suspension system as claimed in claim 1, wherein the on-board visual system is a stereoscopic system (60) comprising two cameras (6, 7) that generate successive pairs of images and generate three-dimensional data on the basis of disparities between each pair of images.
3. The method for checking the state of a suspension system as claimed in claim 2, further comprising: digitally filtering a noise of said disparities.
4. The method for checking the state of a suspension system as claimed in claim 3, wherein the flat reference road (100) determined by averaging standard deviations of the positional data of the road (110) with a predetermined number of pixels.
5. The method for checking the state of a suspension system as claimed in claim 3, wherein the path (Ts) of the vehicle (1) is determined (235) by successive values of parameters relating to a height of the road (110) and a height of the vehicle (1), and positional parameter values of said rotational and translational positional parameter data of the vehicle, including at least one of a roll rotation and a pitch rotation of the vehicle (1), said positional parameter values being determined using the acquired and stored positional data and said rotational and translational positional parameter data.
6. The method for checking the state of a suspension system as claimed in claim 3, wherein a model suspension is selected for each wheel (5a, 5b) of the vehicle (1) from a library (240) stored in the data storage, including a model for a single-stage suspension system, and for a two-stage suspension system.
7. The method for checking the state of a suspension system as claimed in claim 2, wherein the flat reference road (100) determined by averaging standard deviations of the positional data of the road (110) with a predetermined number of pixels.
8. The method for checking the state of a suspension system as claimed in claim 2, wherein the path (Ts) of the vehicle (1) is determined (235) by successive values of parameters relating to a height of the road (110) and a height of the vehicle (1), and positional parameter values of said rotational and translational positional parameter data of the vehicle, including at least one of a roll rotation and a pitch rotation of the vehicle (1), said positional parameter values being determined using the acquired and stored positional data and said rotational and translational positional parameter data.
9. The method for checking the state of a suspension system as claimed in claim 2, wherein a model suspension is selected for each wheel (5a, 5b) of the vehicle (1) from a library (240) stored in the data storage, including a model for a single-stage suspension system, and for a two-stage suspension system.
10. The method for checking the state of a suspension system as claimed in claim 2, wherein the suspension system (10) is controlled using active, semi-active or passive control (6A, 6B).
11. The method for checking the state of a suspension system as claimed in claim 1, wherein the flat reference road (100) determined by averaging standard deviations of the positional data of the road (110) with a predetermined number of pixels.
12. The method for checking the state of a suspension system as claimed in claim 11, wherein the path (Ts) of the vehicle (1) is determined (235) by successive values of parameters relating to a height of the road (110) and a height of the vehicle (1), and positional parameter values of said rotational and translational positional parameter data of the vehicle, including at least one of a roll rotation and a pitch rotation of the vehicle (1), said positional parameter values being determined using the acquired and stored positional data and said rotational and translational positional parameter data.
13. The method for checking the state of a suspension system as claimed in claim 11, wherein a model suspension is selected for each wheel (5a, 5b) of the vehicle (1) from a library (240) stored in the data storage, including a model for a single-stage suspension system, and for a two-stage suspension system.
14. The method for checking the state of a suspension system as claimed in claim 1, wherein the path (Ts) of the vehicle (1) is determined (235) by successive values of parameters relating to a height of the road (110) and a height of the vehicle (1), and positional parameter values of said rotational and translational positional parameter data of the vehicle, including at least one of a roll rotation and a pitch rotation of the vehicle (1), said positional parameter values being determined using the acquired and stored positional data and said rotational and translational positional parameter data.
15. The method for checking the state of a suspension system as claimed in claim 14, wherein a model suspension is selected for each wheel (5a, 5b) of the vehicle (1) from a library (240) stored in the data storage, including a model for a single-stage suspension system, and for a two-stage suspension system.
16. The method for checking the state of a suspension system as claimed in claim 1, wherein a model suspension is selected for each wheel (5a, 5b) of the vehicle (1) from a library (240) stored in the data storage, including a model for a single-stage suspension system, and for a two-stage suspension system.
17. The method for checking the state of a suspension system as claimed in claim 16, wherein the suspension parameters of the model suspension comprise a spring stiffness (K) and a shock absorber compression ratio (C) for each wheel (2a, 2b).
18. The method for checking the state of a suspension system as claimed in claim 1, wherein the suspension system (10) is controlled using one of active, semi-active, or passive control (6A, 6B).
19. The method for checking the state of a suspension system as claimed in claim 1, wherein the accuracy of the error (P.sup.2) enables determination of a state of inflation of tires (5a, 5b) of the vehicle.
20. The method for checking the state of a suspension system as claimed in claim 19, wherein the accuracy of the error (P.sup.2) makes possible a determination of which of suspension members or tires (5a, 5b) causes the pre-critical state.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
(1) Other data, characteristics and advantages of the present invention are set out in the detailed nonlimiting description below, provided with reference to the figures attached which show, respectively:
(2)
(3)
(4)
(5)
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
(6)
(7) Such a suspension system 10 is active in the example shown, i.e. controlling this suspension enables the vehicle to be kept on a flat path if the suspension is a perfect reference suspension system, this path being held at a given height in relation to the ground while the vehicle is in movement.
(8) Alternatively, suspension control is deemed to be semi-active when same does not oppose the vertical movement of the wheels, but compensates for this movement to prevent same from being amplified. If no suspension control is used, this control is deemed to be passive, in the absence of any control or standby state.
(9) The vehicle 1 also includes cameras 6 and 7 in a stereoscopic system 60 that are assembled on an on-board supporting element 12 arranged on the upper edge of the windshield 1b of the vehicle 1.
(10) In order to illustrate a suspension model 10, the side view of the vehicle body 1c in
(11) Each of the suspension members proper 11A or 11B comprises an equivalent spring 3a or 3b and a shock absorber that are assembled in parallel, each shock absorber being represented by a piston 41 combined with an oil cylinder 42. A suspension control actuator 6A and 6B is provided for each suspension member proper in order to adjust the suspension actively for each wheel 2a and 2b (
(12) Each suspension member proper 11A or 11B bears a sprung mass Ms estimated to be one quarter of the mass of the vehicle body 1c. Furthermore, each tire, represented here by a spring 5a, 5b, bears an unsprung mass Mu, estimated to be one quarter of the chassis. The stiffness of the springs and the compression ratio of the shock absorbers are set in advance to enable the actuators to distribute the masses optimally at all times when the vehicle is in movement.
(13) Under these conditions, the pairs of images of the forward field of vision Va successively stored by the stereoscopic system 60 rigidly attached to the body 1c also save the behaviour of the vehicle that depends on the state of the suspension of same.
(14) This behaviour is entirely determined using variations in the six basic positional parameters in an orthogonal reference system OXYZ, three rotations (pitch, roll and yaw, respectively about the axes OX, OY and OZ) and three translational movements (parallel to the axes OX, OY and OZ), as conventionally applied. In this case, the reference system OXYZ is oriented according to the reference road 100 considered to be flat, which is determined by averaging the standard deviations of the pixels of the road from the forward field of vision Va (i.e. of a real three-dimensional road 110) successively stored. Fewer than six basic parameters may be used in simplified embodiments.
(15) Determining successive values of the six basic parameters saved by the stereoscopic system makes it possible to determine, using a suitable matrix transformation, the variations in the values of the specific positional parameters, defining the path of the vehicle 1 on the reference road 100 and characterizing the behaviour of the vehicle in relation to the state of the suspension of same.
(16) In the example, these specific positional parameters relate to the variation in height h of the irregularities 101 in the real three-dimensional road 110 in relation to the reference road 100, as well as two other parameters related to the position of the vehicle in the reference system OXYZ, specifically the height z of same measured along the axis OZ and the pitch rotation of same about the axis OX. Alternatively, roll rotation of the vehicle may be added, or pitch rotation may be replaced by roll rotation.
(17) The side view in the plane ZOY in
(18)
(19) The logical diagram in
(20) In parallel to this, a step 230 acquiring and storing successive values of the six basic rotational and translational positional parameters of the path of the camera Ts is also performed using the images saved in step 210.
(21) The values of the six basic positional parameters in step 230 and the relative values of the profile of the real three-dimensional road 110 in relation to the linear profile of the reference road 100 (step 220) are used to determine the path Ts of the vehicle (
(22) A suspension model is selected from a model library in step 240. The model accurately translates the effects of the configuration of the suspension of the vehicle being checked using the modelling type of same (distribution of equivalent springs and shock absorbers, number of stages and control type) and the intrinsic parameter values of these equivalents. These intrinsic parameters relate to the stiffness K of the springs and the compression ratio C of the shock absorbers. In the example, the two-stage active suspension model in
(23) In step 250, the mean square error P.sup.2 of the deviations between the value of the intrinsic parameters of the suspension model chosen in the ideal state of same (corresponding to a new suspension system) and the value of these intrinsic parameters corresponding to the vehicle path parameter values stored (the specific positional parameters h, z and in the example) are minimized. As long as the accuracy of the square error P.sup.2 of said deviations is less than a reference accuracy value .sub.R (step 260), the previous step is repeated.
(24) When the accuracy reaches a predetermined value, for example .sub.R, a suspension state diagnosis is provided as a function of the value of the mean square error P.sup.2 (step 270). If this state corresponds to a potentially dangerous, or pre-critical, state, a visual alarm is triggered on the dashboard of the vehicle by sending information over a controller area network (CAN) bus. Advantageously, if the accuracy is particularly high, greater than a predetermined threshold value, it is possible to determined a state of inflation of the tire or to identify the suspension component (suspension members proper or tires) that is responsible for the pre-critical state, or to predict the time of a failure.
(25) The invention is not limited to the examples described and shown. As such, the invention may be applied to visual systems fitted with just one camera. The profile of the road is then detected by analyzing the optical stream to identify movements between two successive images.
(26) Depending on the processing power available, the suspension model selected may be more or less sophisticated and the number of basic positional and suspension parameters may be adjusted to advantageously obtain adequate accuracy, that is greater than a predetermined threshold value, corresponding to the desired information on suspension and potentially inflation state.
(27) Furthermore, the noise in the disparities between pairs of images in a stereoscopic visual system is advantageously filtered, in particular by applying mathematical morphology tools to a disparity map.