Tire lift-off propensity predictive system and method

Patent metadata

Field	Value
Publication number	US-9963146-B2
Application number	US-201715609091-A
Country	US
Kind code	B2
Filing date	May 31, 2017
Priority date	Dec 3, 2014
Publication date	May 8, 2018
Grant date	May 8, 2018

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.

First claim

What is claimed is:

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.

Assignees

• Goodyear Tire & Rubber

Inventors

• Singh Kanwar Bharat
• Parsons Anthony William
• Engel Marc

Classifications

• B60C11/243

  Tread wear sensors, e.g. electronic sensors · CPC title

• B60W30/143 Primary

  Speed control (B60W30/16 takes precedence) · CPC title

• B60W2520/10

  Longitudinal speed · CPC title

• B60C2019/004

  Tyre sensors other than for detecting tyre pressure · CPC title

• B60W30/04

  related to roll-over prevention · CPC title