Rolling virtual wheel spindle calibration

Patent metadata

Field	Value
Publication number	US-9982998-B2
Application number	US-201614990271-A
Country	US
Kind code	B2
Filing date	Jan 7, 2016
Priority date	Jan 7, 2015
Publication date	May 29, 2018
Grant date	May 29, 2018

Abstract

A vehicle wheel alignment system and method is provided for performing a rolling wheel axis of rotation and wheel spindle point calculation every time an alignment is performed. Embodiments include an aligner having a target fixedly attachable to a wheel of the vehicle; a camera for viewing the target and capturing image data of the target; and a data processor. The data processor receives the image data from the camera, and determines a vector pointing from the target origin to a wheel spindle point based on the captured target image data, when the vehicle is rolled while the wheel is on a substantially flat surface such that the wheel and target rotate a number of degrees. The data processor is further adapted to calculate an alignment parameter for the vehicle based at least in part on the wheel axis of rotation and the coordinates of the wheel spindle point.

First claim

What is claimed is:

1. A wheel alignment method for a vehicle, the method comprising:
affixing a target to a wheel of the vehicle;
providing a camera for viewing the target and capturing image data of the target;
rolling the vehicle such that the wheel and target rotate while the camera captures the image data of the target;
calculating a wheel axis of rotation based at least in part on the captured image data;
calculating a virtual wheel spindle point in the plane of motion of the target origin around which the target origin revolves, based at least in part on the captured image data;
using the virtual wheel spindle point and wheel axis of rotation to calculate an alignment parameter for the vehicle.

2. The method of claim 1 , comprising calculating a wheel spindle point based at least in part on the captured image data and using the wheel spindle point to calculate an alignment parameter for the vehicle.

3. The method of claim 1 , comprising calculating a rolling runout of the wheel based at least in part on the captured image data, and using the rolling runout calculation to calculate the alignment parameter for the vehicle.

4. The method of claim 1 , comprising calculating the virtual wheel spindle point using an iterative nonlinear least squares technique.

5. The method of claim 4 , wherein the iterative nonlinear least squares technique comprises one of a Nelder-Mead simplex algorithm, a Levenberg-Marquardt algorithm, and a gradient descent algorithm.

6. The method of claim 1 , comprising calculating the virtual wheel spindle point using a grid search algorithm.

7. The method of claim 1 , comprising affixing the target to the wheel such that the target origin is offset from the wheel axis of rotation.

8. The method of claim 1 , comprising affixing the target to the wheel such that the target origin is disposed substantially on the wheel axis of rotation.

9. A vehicle wheel alignment system comprising:
a target fixedly attachable to a wheel of the vehicle;
a camera for viewing the target and capturing image data of the target; and
a data processor adapted to:
receive the image data from the camera,
determine a wheel axis of rotation based at least in part on the image data of the target captured when the vehicle is rolled such that the wheel and target rotate;
determine a virtual wheel spindle point, based at least in part on the image data of the target captured when the vehicle is rolled, and
calculate an alignment parameter for the vehicle based at least in part on the wheel axis of rotation and the virtual wheel spindle point.

10. The system of claim 9 , comprising calculating a wheel spindle point based at least in part on the captured image data and using the wheel spindle point to calculate an alignment parameter for the vehicle.

11. The system of claim 9 , wherein the data processor is adapted to calculate a rolling runout of the wheel based at least in part on the captured image data, and calculate an alignment parameter for the vehicle based at least in part on the rolling runout.

12. The system of claim 9 , wherein the data processor is adapted to calculate the virtual wheel spindle point coordinates using an iterative nonlinear least squares technique.

13. The system of claim 12 , wherein the iterative nonlinear least squares technique comprises one of a Nelder-Mead simplex algorithm, a Levenberg-Marquardt algorithm, and a gradient descent algorithm.

14. The system of claim 9 , wherein the data processor is adapted to calculate coordinates of the virtual wheel spindle point using a grid search algorithm.

15. The system of claim 9 , comprising a clamp for affixing the target to the wheel such that the target origin is offset from the wheel axis of rotation.

16. The system of claim 9 , comprising a clamp for affixing the target to the wheel such that the target origin is disposed substantially on the wheel axis of rotation.

17. The system of claim 9 , wherein the data processor is adapted to compare coordinates of the calculated virtual wheel spindle point to predetermined reference virtual wheel spindle coordinates, and inform a user when the calculated virtual wheel spindle coordinates are outside the range of reference virtual wheel spindle coordinates.

18. A non-transitory computer readable medium having instructions stored thereon that, when executed by a processor of a vehicle wheel alignment system cause the processor to determine an alignment parameter for the vehicle, the alignment system having a target fixedly attachable to a wheel of the vehicle and a camera for viewing the target and capturing image data of the target, the determination comprising:
receiving the image data from the camera,
determining the coordinates of a virtual wheel spindle point based at least in part on the image data of the target captured when the vehicle is rolled such that the wheel and target rotate,
calculating the wheel axis of rotation based at least in part on the image data of the target captured when the vehicle is rolled such that the wheel and target rotate, and
calculating the alignment parameter for the vehicle based at least in part on the coordinates of the virtual wheel spindle point and the wheel axis of rotation.

19. The non-transitory computer readable medium of claim 18 , comprising calculating a wheel spindle point based at least in part on the captured image data and using the wheel spindle point to calculate an alignment parameter for the vehicle.

20. The non-transitory computer readable medium of claim 18 , the determination further comprising:
calculating a rolling runout of the wheel based at least in part on the captured image data, and
using the rolling runout calculation to calculate the alignment parameter for the vehicle.

21. The non-transitory computer readable medium of claim 18 , the determination further comprising calculating the virtual wheel spindle coordinates using an iterative nonlinear least squares technique.

22. The non-transitory computer readable medium of claim 21 , wherein the iterative nonlinear least squares technique comprises one of a Nelder-Mead simplex algorithm, a Levenberg-Marquardt algorithm, and a gradient descent algorithm.

23. The non-transitory computer readable medium of claim 18 , the determination further comprising calculating the virtual wheel spindle coordinates using a grid search algorithm.

24. The non-transitory computer readable medium of claim 18 , wherein the target is affixed to the wheel such that the target origin is offset from the wheel axis of rotation, or such that the target origin is disposed substantially on the wheel axis of rotation.

25. The non-transitory computer readable medium of claim 18 , the determination further comprising comparing the calculated virtual wheel spindle coordinates to a predetermined reference virtual wheel spindle coordinate range for the target, and informing a user when the calculated virtual wheel spindle coordinates are outside the reference virtual wheel spindle coordinates range.

Assignees

• Snap On Tools Corp

Inventors

• D'Agostino Robert J
• Fuhrman Michael G

Classifications

• G01B2210/16

  Active or passive device attached to the chassis of a vehicle · CPC title

• G01B2210/30

  Reference markings, reflector, scale or other passive device · CPC title

• G01B2210/14

  One or more cameras or other optical devices capable of acquiring a two-dimensional image · CPC title

• G01B11/2755 Primary

  using photoelectric detection means · CPC title

• G01B2210/26

  Algorithms, instructions, databases, computerized methods and graphical user interfaces employed by a user in conjunction with the wheel aligner · CPC title