Tire inflation sensor

• US 5,445,020 A
• Filed: 12/02/1993
• Issued: 08/29/1995
• Est. Priority Date: 11/29/1991
• Status: Expired due to Term

• Current Assignee: Exxon Research and Engineering Company (Exxon Mobil Corporation)
• Original Assignee: Exxon Research and Engineering Company (Exxon Mobil Corporation)
• Inventors: Rosensweig, Ronald E.
• Primary Examiner(s): Chilcot, Jr., Richard E.
• Assistant Examiner(s): Biegel, Ronald L.
• Application Number:
  US08/160,988
• Time in Patent Office: 635 Days
• Field of Search: 73/862.046, 73/146, 73/146.2, 73/146.3, 73/146.5, 340/442, 340/444
• US Class Current: 73/146.2
• CPC Class Codes: G01L 1/146 for measuring force distributions, e.g. using force arrays G01L1/148 takes precedence
• CPC Class Codes: G01L 17/005 using a sensor contacting the exterior surface, e.g. for measuring deformation
• CPC Class Codes: G01P 3/44 for measuring angular speed G01P3/56 takes precedence

Abstract

A system that will indicate tire inflation. A two-dimensional array of sensors is used to determine the distribution of contact forces over the footprint of a pneumatic tire. A neural network may be employed to classify the patterns of force sensed in this manner, and to closely estimate the actual tire inflation pressure.

Claims

1. A system for determining the pressure of a pneumatic vehicular tire while mounted on the wheel of a vehicle, comprising:

a. A two-dimensional array of load sensors which provide a two-dimensional pattern of the force distribution exerted by said tire in contact with said sensors while the vehicle is moving or at rest on said array

b. a computer which is programmed (programmed computer) to determine said tire inflation pressure from said force distribution data independent of the make or model of said tire and said vehicle; and

c. means for displaying said pressure.

2. The system of claim 1 wherein said sensors are piezoelectric and/or piezoresistance elements.

3. The system of claim 1 wherein said load sensors are monitored in the driveway approaching or adjacent to a gasoline service pump.

4. The system of claim 1 wherein said computer program includes a neural network.

5. The system of claim 1 wherein said means for displaying is a visual display in close proximity to said vehicle.

6. The system of claim 1 wherein said computer uses said force distribution data to determine a mean contact pressure.

7. The system of claim 1 wherein said tire pressure is determined by said computer by neural network recognition.

8. The system of claim 7 wherein said neural net is trained on inputs that are insensitive to the position of tire on said sensors.

9. The system of claim 7 wherein said neural net is trained on pseudopressure, summation of forces, midpoint pressure, force-width data, or aspect ratio or combinations thereof.

10. The system of claim 4 wherein said neural net is trained on pseudopressure, summation of forces, midpoint pressure, force-width data, or aspect ratio or combinations thereof.

11. The system of claim 1 wherein differences in the pattern of forces are used to indicate differences in the inflation pressure of tires.