TIRE WEAR STATE ESTIMATION SYSTEM AND METHOD

• US 20190001757A1
• Filed: 06/19/2018
• Published: 01/03/2019
• Est. Priority Date: 06/29/2017
• Status: Active Grant

• Current Assignee: Goodyear Tire & Rubber Company
• Original Assignee: Goodyear Tire & Rubber Company
• Inventors: Singh, Kanwar Bharat
• Granted Patent: US 10,603,962 B2
• Time in Patent Office: Days
• CPC Class Codes: B60C 11/246 Tread wear monitoring systems
• CPC Class Codes: B60C 23/0408 transmitting the signals by non-mechanical means from the wheel or tyre to a vehicle body mounted receiver
• CPC Class Codes: B60C 23/0415 Automatically identifying wheel mounted units, e.g. after replacement or exchange of wheels
• CPC Class Codes: B60C 23/0474 Measurement control, e.g. setting measurement rate or calibrating of sensors; Further processing of measured values, e.g. filtering, compensating or slope monitoring
• CPC Class Codes: B60C 23/0488 Movement sensor, e.g. for sensing angular speed, acceleration or centripetal force
• CPC Class Codes: B60C 23/061 by monitoring wheel speed measuring distance traversed on the ground by vehicles G01C22/00
• CPC Class Codes: B60W 40/12 related to parameters of the vehicle itself , e.g. tyre models
• CPC Class Codes: G01M 17/02 Tyres

Abstract

A tire wear state estimation system includes at least one sensor disposed on a vehicle and a CAN bus system. The sensor measures selected parameters associated with the vehicle and communicates data for the selected parameters through the CAN bus system, including a first set of data, a second set of data and a third set of data. A rolling radius estimator receives the first set of data and estimates a rolling radius for the tire. An acceleration slip estimator receives the second set of data and the estimated rolling radius to estimate the slip of the tire during acceleration. A braking slip estimator receives the third set of data and the estimated rolling radius to estimate the slip of the tire during braking. A tire slip analyzer correlates the acceleration slip estimation and the braking slip estimation and generates an estimated wear state of the tire.

Claims

1. A tire wear state estimation system comprising:

at least one tire supporting a vehicle;

a CAN bus system disposed on the vehicle,

at least one sensor disposed on the vehicle and in electronic communication with the CAN bus system;

the at least one sensor measuring selected parameters associated with the vehicle and communicating data for the selected parameters through the CAN bus system, including a first set of data, a second set of data and a third set of data;

a rolling radius estimator operative to receive the first set of data and estimate a rolling radius for the at least one tire;

an acceleration slip estimator operative to receive the second set of data and the estimated rolling radius to estimate the slip of the at least one tire during acceleration of the vehicle;

a braking slip estimator operative to receive the third set of data and the estimated rolling radius to estimate the slip of the at least one tire during braking of the vehicle; and

a tire slip analyzer to correlate the estimation of the slip of the at least one tire during acceleration of the vehicle and the slip of the at least one tire during braking of the vehicle and generate an estimated wear state of the at least one tire.

2. The tire wear state estimation system of claim 1, wherein the first set of data includes a speed of a wheel, a speed of the vehicle, an acceleration of the vehicle, and a position of a vehicle throttle.

3. The tire wear state estimation system of claim 2, wherein the rolling radius estimator generates a histogram for each data parameter from the first set of data over a selected period of time and estimates the rolling radius using batch mode estimation.

4. The tire wear state estimation system of claim 1, wherein the second set of data includes a speed of the vehicle, an acceleration of the vehicle and a position of a vehicle throttle.

5. The tire wear state estimation system of claim 4, further comprising an acceleration event extractor operative to generate a histogram for each data parameter from the second set of data over a selected period of time and characterize data from each slip histogram according to selected features.

6. The tire wear state estimation system of claim 5, wherein the selected features include a mean, a median, a 25^th percentile, a 75^th percentile, an interquartile range, a 9^th percentile and a 91^st percentile.

7. The tire wear state estimation system of claim 6, wherein the acceleration event extractor screens and selects the most relevant of the selected features for acceleration.

8. The tire wear state estimation system of claim 7, wherein the most relevant of the selected features for acceleration include the median and the 25^th percentile.

9. The tire wear state estimation system of claim 8, wherein the acceleration slip estimator performs feature visualization and model fitting of the most relevant of the selected features for acceleration to calculate the estimated slip of the at least one tire during acceleration of the vehicle.

10. The tire wear state estimation system of claim 1, wherein the third set of data includes a speed of the vehicle, an acceleration of the vehicle, a brake pedal position and a steering wheel angle.

11. The tire wear state estimation system of claim 10, further comprising a braking event extractor operative to generate a histogram for each data parameter from the third set of data over a selected period of time and characterize data from each slip histogram according to selected features.

12. The tire wear state estimation system of claim 11, wherein the selected features include a mean, a median, a 25^th percentile, a 75^th percentile, an interquartile range, a 9^th percentile and a 91^st percentile.

13. The tire wear state estimation system of claim 12, wherein the braking event extractor screens and selects the most relevant of the selected features for braking.

14. The tire wear state estimation system of claim 13, wherein the most relevant of the selected features for braking include the mean and the 75^th percentile.

15. The tire wear state estimation system of claim 14, wherein the braking slip estimator performs feature visualization and model fitting of the most relevant of the selected features for braking to calculate the estimated slip of the at least one tire during braking of the vehicle.

16. A method for estimating the wear state of a tire supporting a vehicle, the method comprising the steps of:

providing at least one sensor disposed on the vehicle and in electronic communication with a CAN bus system;

measuring selected parameters associated with the vehicle using the at least one sensor;

communicating data for the selected parameters through the CAN bus system, including a first set of data, a second set of data and a third set of data;

estimating a rolling radius for the at least one tire with the first set of data;

estimating the slip of the at least one tire during acceleration of the vehicle with the second set of data and the estimated rolling radius;

estimating the slip of the at least one tire during braking of the vehicle with the third set of data and the estimated rolling radius; and

correlating the estimation of the slip of the at least one tire during acceleration of the vehicle and the slip of the at least one tire during braking of the vehicle to generate an estimated wear state of the at least one tire.

17. The method for estimating the wear state of a tire supporting a vehicle of claim 16, wherein the step of estimating the slip of the at least one tire during acceleration of the vehicle includes generating a histogram for each data parameter from the second set of data over a selected period of time and characterizing data from each slip histogram according to selected features.

18. The method for estimating the wear state of a tire supporting a vehicle of claim 17, wherein the step of estimating the slip of the at least one tire during acceleration of the vehicle includes performing feature visualization and model fitting of a set of most relevant features from the selected features to calculate the estimated slip of the at least one tire during acceleration of the vehicle.

19. The method for estimating the wear state of a tire supporting a vehicle of claim 16, wherein the step of estimating the slip of the at least one tire during braking of the vehicle includes generating a histogram for each data parameter from the third set of data over a selected period of time and characterizing data from each slip histogram according to selected features.

20. The method for estimating the wear state of a tire supporting a vehicle of claim 19, wherein the step of estimating the slip of the at least one tire during braking of the vehicle includes performing feature visualization and model fitting of a set of most relevant features from the selected features to calculate the estimated slip of the at least one tire during braking of the vehicle.