TIRE WEAR COMPENSATED LOAD ESTIMATION SYSTEM AND METHOD

• US 20160129737A1
• Filed: 11/11/2014
• Published: 05/12/2016
• Est. Priority Date: 11/11/2014
• Status: Active Grant

• Current Assignee: Goodyear Tire & Rubber Company
• Original Assignee: Goodyear Tire & Rubber Company
• Inventors: Singh, Kanwar Bharat, Parsons, Anthony William, Engel, Marc
• Granted Patent: US 10,245,906 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60C 11/246 Tread wear monitoring systems
• CPC Class Codes: B60C 23/04 mounted on the wheel or tyre
• 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: B60C 23/064 comprising tyre mounted deformation sensors, e.g. to determine road contact area
• CPC Class Codes: B60W 40/13 Load or weight
• CPC Class Codes: G01G 19/086 wherein the vehicle mass is dynamically estimated
• CPC Class Codes: G01M 17/02 Tyres

Abstract

A system and method of estimating a load bearing on a vehicle tire includes an inflation pressure measuring sensor for measuring an inflation pressure level within a tire cavity; a contact patch length sensor measuring the rolling contact patch length of the tire; a tire rolling speed sensor measuring a rolling speed of the tire; and a tire wear state estimation calculator estimating a tire wear state of a tread of the tire. An artificial neural network estimates a tire load from the contact patch length, the inflation pressure level, and the tire rolling speed by utilizing as a compensation factor input the estimated tire wear state.

Claims

1. A system of estimating a load bearing on a vehicle tire, comprising:

a vehicle tire having a tire cavity and supporting a load;

an inflation pressure measuring sensor attached to the tire for measuring an inflation pressure level within the tire cavity;

a contact patch length sensor attached to the tire for measuring the contact patch length of the tire rolling against a ground surface carrying a tire load;

a tire rolling speed sensor mounted to the vehicle for measuring a rolling speed of the tire;

a tire wear state estimation calculator for estimating a tire wear state of a tread of the tire; and

a tire load calculator for estimating a tire load from the contact patch length, the inflation pressure level, and the tire rolling speed;

the tire load calculator in the estimation of the tire load operably utilizing as a compensation factor input the estimated tire wear state.

2. The system of claim 1, wherein further comprising a hub acceleration sensor for measuring a hub acceleration of a hub supporting the vehicle tire;

and wherein the tire wear state estimation calculator estimating the tire wear state from the hub acceleration.

3. The system of claim 2, wherein the tire load calculator comprises an artificial neural network-based signal processor receiving as inputs the contact patch length, the inflation pressure level, the tire rolling speed, and the estimated tire wear state.

4. The system of claim 1, wherein the tire load calculator comprises an artificial neural network-based signal processor receiving as inputs the contact patch length, the inflation pressure level, the tire rolling speed, and the estimated tire wear state.

5. The system of claim 4, wherein the tire load calculator operably compensates the measured contact patch length by the tire wear state estimation.

6. A system of estimating a load bearing on a vehicle tire, comprising:

a vehicle tire having a tire cavity and supporting a load;

an inflation pressure measuring sensor attached to the tire for measuring an inflation pressure level within the tire cavity;

a contact patch length sensor attached to the tire for measuring the contact patch length of the tire rolling against a ground surface carrying a tire load;

a tire rolling speed sensor mounted to the vehicle for measuring a rolling speed of the tire;

a hub acceleration sensor for measuring a hub acceleration of a hub supporting the vehicle tire; and

wherein the tire wear state estimation calculator estimating the tire wear state from the hub acceleration. and

a tire load calculator comprising an artificial neural network for estimating a tire load from the contact patch length, the inflation pressure level, and the tire rolling speed;

the artificial neural network in the estimation of the tire load, and wherein the artificial neural network compensates the measured contact patch length by the tire wear state estimation.

7. A method of estimating a load bearing on a vehicle tire having a tire cavity and supporting a load, comprising:

attaching an inflation pressure measuring sensor to the tire for measuring an inflation pressure level within the tire cavity;

attaching a contact patch length sensor to the tire for measuring the contact patch length of the tire rolling against a ground surface carrying the tire load;

mounting a tire rolling speed sensor to the vehicle for measuring a rolling speed of the tire;

estimating a tire wear state of a tread of the tire; and

estimating a tire load from the contact patch length, the inflation pressure level, and the tire rolling speed by utilizing as a compensation factor input the estimated tire wear state.

8. The method of claim 7, wherein further comprising measuring a hub acceleration of a hub supporting the vehicle tire;

and estimating the tire wear state from the hub acceleration.

9. The method of claim 7, wherein further comprising employing an artificial neural network-based signal processor in estimating the tire load, the artificial neural network receiving as inputs the contact patch length, the inflation pressure level, the tire rolling speed, and the estimated tire wear state.

10. The method of claim 9, wherein the artificial neural network operably compensating the measured contact patch length by the tire wear state estimation.