Tire pressure estimation

• US 20030172728A1
• Filed: 02/27/2003
• Published: 09/18/2003
• Est. Priority Date: 04/12/2000
• Status: Active Grant

• Current Assignee: Nira Dynamics AB
• Original Assignee: Nira Dynamics AB
• Inventors: Gustafsson, Fredrik, Persson, Niclas, Drevo, Marcus
• Granted Patent: US 7,240,542 B2
• Time in Patent Office: Days
• US Class Current: 73/146
• CPC Class Codes: B60C 23/061 by monitoring wheel speed measuring distance traversed on the ground by vehicles G01C22/00
• CPC Class Codes: B60C 23/062 Frequency spectrum analysis of wheel speed signals, e.g. using Fourier transformation
• CPC Class Codes: B60T 2240/03 Tire sensors
• CPC Class Codes: B60T 2250/06 Sensor zero-point adjustment; Offset compensation
• CPC Class Codes: B60T 8/1725 Using tyre sensors, e.g. Sidewall Torsion sensors [SWT] for tyre pressure and temperature detection B60C23/00
• CPC Class Codes: B60T 8/1755 Brake regulation specially adapted to control the stability of the vehicle, e.g. taking into account yaw rate or transverse acceleration in a curve road vehicle drive control systems for control of driving stability otherwise than by controlling a particular sub-unit B60W30/02

Abstract

A method, computer program product and apparatus for estimating the pneumatic pressure of a tire on a vehicle, comprising the steps of: receiving as an input a vehicle status sensor signal; estimating first parameter values of an adaptive filter based on a predetermined model on the vehicle status dependent on the vehicle status sensor signal; calculating, dependent on said first model parameter values, a first tire pressure indication value (δ) being dependent on and indicative of the pneumatic pressure of the tire. Specifically, the vehicle status signal may be an input a wheel angular velocity signal (1) and a lateral movement indication signal; the adaptive filter is based on a predetermined model on lateral vehicle dynamics dependent on the angular velocity of said wheel and the lateral movement of said vehicle.

Claims

1. A method for estimating the pneumatic pressure of a tire on a vehicle, comprising the steps of:

receiving as an input a vehicle status sensor signal;

estimating first parameter values of an adaptive filter based on a predetermined model on the vehicle status dependent on the vehicle status sensor signal;

calculating, dependent on said first model parameter values, a first tire pressure indication value (δ

) being dependent on and indicative of the pneumatic pressure of the tire.

2. The method as recited in claim 1, farther comprising the step of combining said adaptive filter model with a rolling radius based calculation of a second tire pressure indication value dependent on a vehicle status sensor signal representing wheel angular velocity.

3. A method for estimating the pneumatic pressure of a tire on a vehicle as recited in claim 1, comprising the steps of:

receiving as an input a wheel angular velocity signal (1) and a lateral movement indication signal;

estimating first parameter values of an adaptive filter based on a predetermined model on lateral vehicle dynamics dependent on the angular velocity of said wheel and the lateral movement of said vehicle;

calculating, dependent on said first model parameter values, a first tire pressure indication value (δ

) being dependent on and indicative of the pneumatic pressure of the tire.

4. The method as recited in claim 3, wherein said lateral movement indication signal is generated by a sensor indicating the yaw rate of said vehicle, said sensor preferably being a gyro.

5. The method as recited in any of the preceding claims, further comprising a lateral movement indication signal generated by:

integrating, in an adaptive filter, parameters relating to lateral dynamics and parameters relating to rolling radius phenomena;

estimating the values of said integrated parameters dependent on a lateral movement indication signal generated by a sensor indicating the yaw rate, preferably a gyro, and on a wheel angular velocity signal;

calculating an improved lateral movement indication signal dependent on said integrated parameter values.

6. The method as recited in any of the preceding claim, farther comprising the step of integrating, in an adaptive filter, parameters relating to lateral dynamics and parameters relating to longitudinal dynamics of said vehicle;

estimating the values of said integrated parameters dependent on a lateral movement indication signal and on a road friction indication signal derived from a wheel angular velocity signal, a motor torque signal and a gear indicator signal;

calculating an improved tire pressure indication signal for an identified tire, and possibly also a confidence indication, dependent on said integrated parameter values.

7. The method as recited in any of the preceding claims, wherein said lateral movement indication signal alternatively or additionally is generated by a sensor indicating the lateral acceleration of said vehicle, said sensor preferably being an accelerometer.

8. The method as recited in any of the preceding claims, further being adapted for tire pressure estimation in a motorcycle having two wheels by comprising in said adaptive filter front and rear wheel angular velocity parameters.

9. The method as recited in any of the preceding claims, further being adapted for tire pressure estimation in a motorcycle having two wheels by comprising in said adaptive filter a roll angle parameter, the value of which is represented by a roll angle sensor signal.

10. The method as recited in claim 1, wherein said adaptive filter is based on a predetermined model of vibrations in a tire, and said first tire pressure indication value is a resonance frequency.

11. The method as recited in claim 1, wherein the adaptive filter of said predetermined model is a recursive least squares algorithm.

12. The method as recited in claim 1, wherein the adaptive filter of said predetermined model is a Kalman filter representing a state space model algorithm.

13. The method as recited in claim 1, further comprising the step of pre-processing a vehicle status signal in the shape of a wheel angular velocity signal derived from a toothed wheel sensor with respect to correction of toothed-wheel errors.

14. The method as recited in claim 13, further comprising the step of interpolating non-equidistant data in said corrected wheel angular velocity signal.

15. The method as recited in any of the preceding claims, further comprising the step of reducing the sampling frequency of a sampled sensor signal by re-sampling and band pass filtering the input sensor signals into a first and a second frequency band, and by modulating said first and second frequency bands with modulating signals dependent on the lower frequency of each frequency band.

16. The method as recited in claim 1, further comprising the step of:

integrating, in an adaptive filter, parameters relating to different groups of vehicle status parameters;

estimating the values of said integrated parameters dependent on a sensor signals representing entities related to said groups of vehicle status parameters;

calculating a tire pressure indication signal dependent on said integrated parameter values, and possibly also calculating secondary indication signals derived from the values of said integrated parameters.

17. The method as recited in claim 1, further comprising the step of:

calculating a first estimate of a tire air pressure value dependent on said first tire pressure indication value and a predetermined mapping function or mapping table.

18. A computer program product for estimating the pneumatic pressure of a tire on a vehicle, comprising program code adapted to direct a data processing system to perform the steps and functions of the preceding claims.

19. An apparatus for estimating the pneumatic pressure of a tire on a vehicle, comprising functional components for performing the steps and functions of any of the preceding claims.