Tire wear compensated load estimation system and method

Patent metadata

Field	Value
Publication number	US-10245906-B2
Application number	US-201414538244-A
Country	US
Kind code	B2
Filing date	Nov 11, 2014
Priority date	Nov 11, 2014
Publication date	Apr 2, 2019
Grant date	Apr 2, 2019

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.

First claim

What is claimed is:

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 hub acceleration sensor for measuring a hub acceleration of a hub supporting the vehicle tire;
a tire wear state estimation calculator for deriving an estimated depth of a tread of the tire based on the hub acceleration;
a compensation factor based upon the estimated depth of the tread; and
a tire load calculator for estimating a tire load from the contact patch length, the compensation factor, the inflation pressure level, and the tire rolling speed.

2. 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 tread depth.

3. 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;
measuring a hub acceleration of a hub supporting the vehicle tire;
deriving an estimated depth of a tread of the tire based on the hub acceleration;
basing a compensation factor upon the estimated depth of the tread; and
estimating a tire load from the contact patch length, the compensation factor, the inflation pressure level, and the tire rolling speed.

4. The method of claim 3 , 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 tread depth.

Assignees

• Goodyear Tire & Rubber

Inventors

• Singh Kanwar Bharat
• Parsons Anthony William
• Engel Marc

Classifications

• B60C23/0488 Primary

  Movement sensor, e.g. for sensing angular speed, acceleration or centripetal force · CPC title

• B60C23/04

  mounted on the wheel or tyre · CPC title

• B60C23/064

  comprising tyre mounted deformation sensors, e.g. to determine road contact area · CPC title

• B60W40/13

  Load or weight · CPC title

• G01M17/02 Primary

  Tyres · CPC title