Load estimation system and method for a vehicle tire

• US 9,120,356 B2
• Filed: 06/27/2012
• Issued: 09/01/2015
• Est. Priority Date: 06/27/2012
• Status: Active Grant

• Current Assignee: Goodyear Tire & Rubber Company
• Original Assignee: Goodyear Tire & Rubber Company
• Inventors: Patel, Amrita, Fenkanyn, John Michael, Singh, Kanwar Bharat, Suh, Peter Jung-min
• Primary Examiner(s): Bui, Bryan
• Application Number:
  US13/534,043
• Publication Number:
  US 20140005956A1
• Time in Patent Office: 1,161 Days
• Field of Search: 702/41
• US Class Current: 1/1
• CPC Class Codes: B60C 23/04 mounted on the wheel or tyre
• CPC Class Codes: B60C 23/064 comprising tyre mounted deformation sensors, e.g. to determine road contact area

Abstract

Estimating a load bearing on a vehicle tire includes an inflation pressure measuring sensor for measuring tire inflation pressure and generating a measured tire inflation pressure signal; a deformation measuring sensor mounted in a tire region of the vehicle tire, the deformation measuring sensor in the form of a piezoelectric bending sensor generating a deformation signal estimating a length of a tire contact patch length as the senor rolls through a tire footprint. Tire rolling speed is estimated from the deformation signal and a peak to peak amplitude variation within the deformation signal is detected and measured. An artificial neural network receives the tire rolling speed estimation, the contact patch length estimation, the amplitude variation within the deformation signal, and the measured inflation pressure of the tire. The artificial neural network adaptively interprets the input data and generates an output load estimation based thereon.

Claims

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

(A) deploying a deformation measuring sensor in the vehicle tire, the deformation measuring sensor generating a cyclical tire deformation signal indicative of tire deformation in a contact patch of a rolling tire;

(B) deploying a tire inflation pressure measuring sensor in the vehicle tire, the inflation pressure measuring sensor measuring tire inflation pressure from within a tire cavity;

calculating a tire rolling speed estimation based upon the tire deformation signal;

(C) calculating a tire contact patch length estimation based upon the tire deformation signal;

(D) calculating a load estimation on the tire based upon the tire inflation pressure, the tire contact patch length estimation, and the tire rolling speed estimation and further comprising;

detecting a leading and a trailing contact edge point in the deformation measuring signal using a peak detection algorithm;

estimating a peak-to-peak amplitude variation in the deformation signal;

calculating the load estimation on the tire based upon the tire inflation pressure, the tire contact patch length estimation, the tire rolling speed estimation, and the peak-to peak amplitude magnitude of the deformation signal to estimate a tire deformation magnitude.

2. The method of claim 1, wherein the tire deformation signal comprises a pulse extending between the contact edge points in the signal, the contact edge points commencing with the deformation measuring sensor rotating into the tire footprint and substantially concluding with the deformation measuring sensor rotating out of the tire footprint.

3. The method of claim 2, wherein a tire deformation signal is generated with each tire revolution.

4. A method of estimating a load bearing on a vehicle tire, comprising:

(A) deploying a deformation measuring sensor in the vehicle tire, the deformation measuring sensor generating a cyclical tire deformation signal indicative of tire deformation in a contact patch of a rolling tire;

(B) deploying a tire inflation pressure measuring sensor in the vehicle tire, the inflation pressure measuring sensor measuring tire inflation pressure from within a tire cavity;

calculating a tire rolling speed estimation based upon the tire deformation signal;

(C) calculating a tire contact patch length estimation based upon the tire deformation signal;

(D) calculating a load estimation on the tire based upon the tire inflation pressure, the tire contact patch length estimation, and the tire rolling speed estimation and

wherein the deformation signal comprises a pulse having leading and trailing edge points identifying boundaries of the contact patch and the contact patch length and

wherein calculating the tire rolling speed estimation comprises applying an event detection algorithm to detect the occurrence of a deformation signal and using a peak detection algorithm to detect contact edge points in the deformation signal;

estimating an edge distance between the contact edge points of the deformation signal;

calculating a time-span by dividing the edge distance by a sampling frequency; and

calculating tire rolling speed by dividing a tire contact patch length estimation by the time-span.

5. The method of claim 4, wherein calculating the tire contact patch length estimation comprises multiplying a speed of the tire times the time-span.

6. The method of claim 5, wherein calculating a load estimation on the tire comprises applying as input data the tire rolling speed estimation, the contact patch length estimation, and the inflation pressure of the tire to an artificial neural network programmed to interpret the input data and output a load estimation.

7. The method of claim 6, wherein the deformation measuring sensor comprising a piezoelectric film sensor mounted to a tire region, the film sensor operable to proportionally bend with deformation of the tire region as the tire region creates a contact patch against a ground surface, whereupon the film sensor generating the tire deformation signal.

8. The method of claim 7, wherein the tire deformation signal has an amplitude and period proportional to a deformation magnitude of the tire region;

and the method further comprising applying as an additional input the deformation signal amplitude into the artificial neural network programmed to interpret the deformation signal amplitude with the tire rolling speed estimation, the contact patch length estimation, and the inflation pressure of the tire to render an output load estimation.

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

(A) a vehicle tire supporting a load;

(B) an inflation pressure measuring sensor for measuring tire inflation pressure and generating a measured tire inflation pressure signal;

(C) a deformation measuring sensor mounted in a tire region of the vehicle tire, the deformation measuring sensor comprising a piezoelectric sensor rotating with the tire region through a tire footprint, the deformation measuring sensor generating within the tire footprint a deformation signal indicative of opposite edge boundaries of a footprint contact patch and a length of the contact patch;

(D) a programmed data processor for calculating a contact patch length estimation from the deformation signal;

(E) a programmed data processor for calculating a tire rolling speed estimation from the deformation signal;

(F) an artificial neural network programmed to adaptively interpret the tire rolling speed estimation, the contact patch length estimation, and the measured inflation pressure of the tire and generate an output load estimation based thereon.

10. The system of claim 9, further comprising a programmed data processor for calculating an amplitude estimate of the deformation signal and the artificial neural network being additionally programmed to interpret the amplitude estimation with the tire rolling speed estimation, the contact patch length estimation, and the measured inflation pressure of the tire to generate the output load estimation.

11. The system of claim 10, wherein the deformation measuring sensor comprises a piezoelectric film sensor mounted to the tire to roll through a tire footprint as the tire rotates.

12. The system of claim 11, wherein the programmed data processor for calculating a contact patch length comprises an event detection algorithm to detect the occurrence of the deformation signal, a peak detection algorithm to detect within the deformation signal contact edge points;

an estimation algorithm to calculate an edge distance between the contact edge points of the deformation signal; and

an algorithm for calculating a time-span of the deformation signal by dividing the edge distance by a sampling frequency; and

an algorithm for calculating a contact patch length by applying the time-span to a rolling radius of the tire.

13. The system of claim 12, wherein the programmed data processor for calculating the tire rolling speed comprises an algorithm dividing the tire contact patch length by the time-span.

14. The system of claim 12, wherein the programmed data processor for calculating the amplitude estimate of the deformation signal comprises an algorithm to detect within the deformation signal a peak to peak amplitude variation at the deformation signal contact edge points.