TIRE TEMPERATURE PREDICTIVE SYSTEM AND METHOD

• US 20150360525A1
• Filed: 06/11/2014
• Published: 12/17/2015
• Est. Priority Date: 06/11/2014
• Status: Active Grant

• Current Assignee: Goodyear Tire & Rubber Company
• Original Assignee: Goodyear Tire & Rubber Company
• Inventors: Singh, Kanwar Bharat, Parsons, Anthony William, Veppathur Sivaramakrishnan, Srikanth
• Granted Patent: US 9,636,955 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60C 23/20 Devices for measuring or signalling tyre temperature only
• CPC Class Codes: B60W 2520/105 Longitudinal acceleration
• CPC Class Codes: B60W 2520/14 Yaw
• CPC Class Codes: B60W 2520/26 Wheel slip
• CPC Class Codes: B60W 40/12 related to parameters of the vehicle itself , e.g. tyre models
• CPC Class Codes: G01K 13/08 in rotary movement

Abstract

A tire-based system and method for estimating a radially outward tire surface temperature of an identified tire supporting an identified vehicle includes a temperature sensor to measure a tire inner liner temperature. An algorithmic prediction model is empirically trained to correlate inner liner tire temperature to tire radially outward surface temperature for the tire/vehicle combination. The empirically trained algorithmic prediction model receives a steady state temperature-based model inputs including the tire inner liner temperature and an ambient temperature measurement and transient behavior vehicle-based inputs. Based upon the steady state inputs and the transient behavior inputs, a radially outward tire surface temperature estimation is made.

Claims

1. A tire-based system for estimating a radially outward tire surface temperature of an identified tire supporting an identified vehicle, the system comprising:

at least one temperature sensor mounted to the tire operative to measure a tire inner liner temperature;

an algorithmic prediction model empirically trained to correlate inner liner tire temperature to tire radially outward surface temperature for an applicable identified tire and identified vehicle combination, the empirically trained algorithmic prediction model operatively receiving a plurality of model inputs including the tire inner liner temperature and generating based upon the tire inner liner temperature a radially outward tire surface temperature estimation.

2. The system of claim 1, wherein the model inputs include temperature-measuring inputs including the tire inner liner temperature.

3. The system of claim 2, wherein the model inputs include a sensor-measured ambient temperature.

4. The system of claim 2, wherein the system further comprising vehicle-based sensors providing a plurality of vehicle-based transient behavior measurements, and frictional energy calculating means for generating a frictional energy input to the algorithmic prediction model from the vehicle-based transient behavior measurements.

5. The system of claim 4, wherein the vehicle-based transient behavior measurements comprise at least vehicle acceleration, slip angle, and yaw rate.

6. The system of claim 2, wherein the algorithmic prediction model combines frictional energy from the travel of the tire over a surface, thermal surface-conduction from the tire to the surface;

air-convection thermal loss from the tire; and

internal-conduction thermal loss within the tire.

7. A tire-based system for estimating a radially outward tire surface temperature of an identified tire supporting an identified vehicle, the system comprising:

at least one temperature sensor mounted to the tire operative to measure a tire inner liner temperature;

an algorithmic prediction model empirically trained to correlate inner liner tire temperature to tire radially outward surface temperature for the combination represented by the identified tire and the identified vehicle, the empirically trained algorithmic prediction model operatively receiving a plurality of steady-state temperature-based model inputs including the tire inner liner temperature and a plurality of transient behavior vehicle-based inputs and generating based upon the steady-state inputs and the transient behavior inputs a radially outward tire surface temperature estimation.

8. The system of claim 7, wherein the algorithmic model is trained to correlate inner liner tire temperature to tire radially outward surface temperature for the combination represented by the identified tire and the identified vehicle by a specifically identified tire location on the vehicle.

9. The system of claim 7, wherein the system further comprising vehicle-based sensors providing a plurality of vehicle-based transient behavior measurements, and frictional energy calculating means for generating the transient behavior vehicle-based inputs to the algorithmic prediction model from the vehicle-based transient behavior measurements.

10. The system of claim 9, wherein the vehicle-based transient behavior measurements comprise at least vehicle acceleration, slip angle and yaw rate.

11. The system of claim 7, wherein the steady-state temperature-based model inputs include an ambient temperature measurement.

12. The system of claim 7, wherein the algorithmic prediction model combines frictional energy loss from travel of the tire over a surface, thermal surface conduction loss from the tire to the surface;

air convection thermal loss from the tire to the air surrounding the tire and internal conduction thermal loss within the tire.

13. A tire-based method for estimating a radially outward tire surface temperature of an identified tire supporting an identified vehicle, the method comprising:

identifying the tire supporting the vehicle;

identifying the vehicle;

mounting at least one temperature sensor to the tire operative to measure a tire inner liner temperature;

empirically training an algorithmic prediction model to correlate inner liner tire temperature to tire radially outward surface temperature for the combination represented by the identified tire and the identified vehicle;

inputting into the empirically trained algorithmic prediction model a plurality of steady-state temperature-based model inputs including the tire inner liner temperature and a plurality of transient behavior vehicle-based inputs; and

generating based upon the steady-state inputs and the transient behavior inputs a radially outward tire surface temperature estimation.

14. The method of claim 13, wherein further comprising empirically training the algorithmic model to correlate inner liner tire temperature to tire radially outward surface temperature for the combination represented by the identified tire and the identified vehicle by a specifically identified tire location on the vehicle.

15. The method of claim 13, wherein further comprising:

utilizing vehicle-based sensors to provide a plurality of vehicle-based transient behavior measurements, and

calculating frictional energy as transient behavior vehicle-based inputs to the algorithmic prediction model from the vehicle-based transient behavior measurements.

16. The method of claim 15, wherein the vehicle-based transient behavior measurements comprise at least vehicle acceleration, slip angle, and yaw rate.

17. The method of claim 13, wherein the steady-state temperature-based model inputs include an ambient temperature measurement.

18. The method of claim 13, wherein further comprising combining within the algorithmic prediction model frictional energy loss from travel of the tire over a surface, thermal surface-conduction loss from the tire to the surface;

air-convection thermal loss from the tire to the air surrounding the tire; and

internal-conduction thermal loss within the tire.