Tire lift-off propensity predictive system and method

• US 9,963,146 B2
• Filed: 05/31/2017
• Issued: 05/08/2018
• Est. Priority Date: 12/03/2014
• Status: Active Grant

• Current Assignee: Goodyear Tire & Rubber Company
• Original Assignee: Goodyear Tire & Rubber Company
• Inventors: Singh, Kanwar Bharat, Parsons, Anthony William, Engel, Marc
• Primary Examiner(s): Laballe, Clayton E
• Assistant Examiner(s): Hancock, Dennis
• Application Number:
  US15/609,091
• Publication Number:
  US 20170320494A1
• Time in Patent Office: 342 Days
• CPC Class Codes: B60C 11/243 Tread wear sensors, e.g. electronic sensors
• CPC Class Codes: B60C 19/00 Tyre parts or constructions not otherwise provided for
• CPC Class Codes: B60C 2019/004 Tyre sensors other than for detecting tyre pressure
• CPC Class Codes: B60C 23/04 mounted on the wheel or tyre
• 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 23/0488 Movement sensor, e.g. for sensing angular speed, acceleration or centripetal force
• CPC Class Codes: B60C 23/06 Signalling devices actuated by deformation of the tyre , e.g. tyre mounted deformation sensors or indirect determination of tyre deformation based on wheel speed, wheel-centre to ground distance or inclination of wheel axle
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2530/20 Tyre data
• CPC Class Codes: B60W 2720/10 Longitudinal speed
• CPC Class Codes: B60W 30/04 related to roll-over prevention
• CPC Class Codes: B60W 30/143 Speed control B60W30/16 takes precedence
• CPC Class Codes: B60W 40/112 Roll movement
• CPC Class Codes: B60W 40/13 Load or weight

Abstract

A system for predicting tire lift-off propensity of a vehicle tire includes a vehicle tire-affixed tire-identification device for providing a tire-specific identification, multiple tire-affixed sensors mounted to the tire measuring tire-specific parameters and generating tire-specific parameter information, one or more vehicle-affixed sensor(s) mounted to the vehicle to measure vehicle speed and a lift-off propensity estimator generating a lift-off propensity for the vehicle tire from a database containing experimentally-derived, tire-ID specific, lift-off propensities correlated with measured tire-specific parameter information and vehicle speeds.

Claims

1. A lift-off propensity predictive system comprising:

a vehicle supported by at least one vehicle tire mounted to a hub, the vehicle tire including a tire cavity and a ground-engaging tread, and the tire including a plurality of tire-specific measureable parameters;

a plurality of tire-affixed sensors mounted to the tire operably measuring the tire-specific parameters and generating tire-specific parameter information;

a tire-affixed tire-identification device for providing a tire-specific identification;

at least one vehicle-affixed sensor mounted to the vehicle operably measuring vehicle speed;

a lift-off propensity estimator operable to generate a lift-off propensity for the one vehicle tire, the lift-off propensity being correlated to a predicted tire contact patch area, wherein the predicted tire contact patch area is calculated from the tire-specific parameter information, the tire-specific identification and the vehicle speed; and

means to generate a lift off propensity warning for the vehicle.

2. The lift-off propensity predictive system for a tire according to claim 1, wherein the tire-specific parameter information is from the group:

a load estimation for the one vehicle tire;

air pressure within a cavity of the one vehicle tire; and

a wear estimation for a tread region of the one vehicle tire.

3. The lift-off propensity predictive system according to claim 2, wherein the load estimation operably calculates a load estimation based upon a vehicle-based hub accelerometer signal.

4. The lift-off propensity predictive system of claim 1, wherein the lift-off propensity substantially continuously updated during an movement of the vehicle.

5. The lift-off propensity predictive system of claim 1, wherein the lift-off propensity is correlated to the predicted tire contact patch area through a linear relationship between the lift-off propensity and the predicted tire contact patch.

6. The lift-off propensity predictive system of claim 1, wherein the predicted tire contact patch area and the lift-off propensity are stored in a database.

7. The lift-off propensity predictive system of claim 1, wherein the predicted tire contact patch area is calculated using a regression model.

8. The lift-off propensity predictive system of claim 7, wherein the predicted tire contact patch area is calculated using a non-linear regression model.

9. The lift-off propensity predictive system of claim 8, wherein the predicted tire contact patch area is calculated using a random forest regression algorithm.

10. The lift-off propensity predictive system of claim 1, further comprising means for measuring a water depth on a road travelled by the vehicle, wherein the calculation of the predicted tire contact patch area includes the measured water depth.

11. A lift-off propensity predictive system comprising:

a vehicle supported by at least one vehicle tire mounted to a hub, the vehicle tire including a tire cavity and a ground-engaging tread, and the tire including a plurality of tire-specific measureable parameters;

a plurality of tire-affixed sensors mounted to the tire operably measuring the tire-specific parameters and generating tire-specific parameter information;

a tire-affixed tire-identification device for providing a tire-specific identification;

at least one vehicle-affixed sensor mounted to the vehicle operably measuring vehicle speed;

a lift-off propensity estimator operable to generate a lift-off propensity for the one vehicle tire, the lift-off propensity being correlated to a predicted tire contact patch area, wherein the predicted tire contact patch area is calculated from the tire-specific parameter information, the tire-specific identification and the vehicle speed; and

means to generate a lift off propensity warning to multiple vehicles.

12. A method of making a lift-off propensity estimation comprising:

mounting at least one vehicle tire to a vehicle, the vehicle tire having a tire cavity and a ground-engaging tread, and the tire having a plurality of tire-specific measureable parameters;

affixing to the one vehicle tire a tire identification device providing a tire-specific identification;

affixing at least one vehicle-affixed sensor to the vehicle operably measuring vehicle speed;

mounting a plurality of tire-affixed sensors to the tire operably measuring the tire-specific parameters to generate tire-specific parameter information;

inputting the tire-specific parameter information and the tire-specific identification and the vehicle speed into a lift-off propensity estimator;

calculating a predicted tire contact patch area from the tire-specific parameter information, the tire-specific identification and the vehicle speed with the lift-off propensity estimator;

correlating the predicted tire contact patch area to a lift-off propensity for the one vehicle tire; and

generating a lift off propensity warning for the vehicle.

13. The method according to claim 12, wherein the tire-specific parameter information includes a load estimation for the one vehicle tire, air pressure within a cavity of the one vehicle tire and a wear estimation for a tread region of the one vehicle tire.

14. The method according to claim 12, further comprising utilizing a vehicle-based accelerometer signal to generate the load estimation for the one vehicle tire.

15. The method according to claim 12, wherein the lift-off propensity is correlated to the predicted tire contact patch area through a linear relationship between the lift-off propensity and the predicted tire contact patch.

16. The method according to claim 12, wherein the predicted tire contact patch area is calculated using a regression model.

17. The method according to claim 12, further comprising measuring a water depth on a road travelled by the vehicle, wherein the calculation of the predicted tire contact patch area includes the measured water depth.

18. The method according to claim 12, further comprising generating a lift off propensity warning to multiple vehicles.