System for monitoring the inflation pressure of a vehicle

• US 6,060,984 A
• Filed: 01/29/1999
• Issued: 05/09/2000
• Est. Priority Date: 01/29/1998
• Status: Expired due to Fees

• Current Assignee: Daimler AG (Mercedes-Benz Group AG)
• Original Assignee: DaimlerChrysler AG (Mercedes-Benz Group AG)
• Inventors: Lich, Thomas, Braun, Fritz, Merz, Kurt-Juergen, Hrycej, Tomas, Stiltz, Winfried, Spieth, Uwe
• Primary Examiner(s): Lefkowitz, Edward
• Application Number:
  US09/239,704
• Time in Patent Office: 466 Days
• Field of Search: 340/442, 73/146, 73/146.2, 73/146.5
• US Class Current: 340/442
• CPC Class Codes: B60C 23/06 Signalling devices actuated by deformation of the tyre , e.g. tyre mounted deformation sensors or indirect determination of tyre deformation based on wheel speed, wheel-centre to ground distance or inclination of wheel axle

Abstract

A system for monitoring the vehicle tire inflation pressure has a device for detecting the vertical acceleration of the tire or of a vehicle component connected therewith and the longitudinal speed of the vehicle, as well as having an analyzing unit which determines the tire inflation pressure from the measured vertical acceleration data and the measured vehicle longitudinal speed data. The analyzing unit contains a trainable estimating unit, particularly a neuronal network, which is trained by predeterminable training example data with different tire inflation pressure values and vehicle longitudinal speed values. In the trained condition, the estimating unit determines the tire inflation pressure at least as a function of the measured vertical acceleration and vehicle longitudinal speed data fed directly or preprocessed on an input side thereof. The system provides continuous tire inflation pressure monitoring in the case of road vehicles.

Claims

1. A system for monitoring pressure of a vehicle tire, comprising:

a device for detecting at least a vertical acceleration value related to the tire and a vehicle longitudinal speed value;

an analyzing device comprising an estimating unit trainable via predeterminable training example data having different tire inflation pressure values and vehicle longitudinal speed values, said estimating unit, in a trained condition, determining a tire inflation pressure at least as a function of the measured vertical acceleration value and the vehicle longitudinal speed value input therein either directly or after preprocessing;

wherein the system comprises at least one of the following components;

i) a device for generating road condition information as a function of the measured vertical acceleration and vehicle longitudinal speed values, by which an activation and deactivation of said estimating unit is controlled as a function of whether a momentary measured vertical acceleration and vehicle longitudinal speed values are in each case inside or outside of pertaining predeterminable value ranges;

ii) a signal post-processing stage connected behind said estimating unit for suppressing estimated values obtained by said estimating unit which are outside a predeterminable trained value range;

iii) a preprocessing unit comprising an analog-digital converter unit and a post-connected system condition determination unit, said condition determination unit computing one or more time derivatives of the measured vertical acceleration value and feeding said derivatives, in addition to the measured vertical acceleration value, to said estimating unit as input quantities;

iv) a preprocessing unit comprising an analog-digital converter unit and a post-connected FFT unit having a pertaining selection unit, wherein information selected by said pertaining selection unit is fed as input quantities to said estimating unit;

v) a data memory usable in a recording phase for recording said training example data instead of said estimating unit, said recorded training example data being stored in the recording phase, and an evaluating and optimizing stage which, in a training phase, is connected behind said estimating unit, wherein in said training phase the estimating unit is connected to the data memory and is trained via the training example data stored therein with a feedback from said evaluating and optimizing stage.

2. The system according to claim 1, wherein the analyzing device is a neuronal network.

3. The system according to claim 1, wherein said preprocessing unit has an anti-aliasing filter coupled in front of said analog-digital converter unit.

4. The system according to claim 2, wherein said preprocessing unit has an anti-aliasing filter coupled in front of said analog-digital converter unit.

5. The system according to claim 1, wherein the preprocessing unit comprises a digital low-pass smoothing filter, coupled behind said analog-digital converter unit, and a high-pass offset filter connected with said digital low-pass smoothing filter.

6. The system according to claim 2, wherein the preprocessing unit comprises a digital low-pass smoothing filter, coupled behind said analog-digital converter unit, and a high-pass offset filter connected with said digital low-pass smoothing filter.

7. The system according to claim 3, wherein the preprocessing unit comprises a digital low-pass smoothing filter, coupled behind said analog-digital converter unit, and a high-pass offset filter connected with said digital low-pass smoothing filter.

8. The system according to claim 4, wherein the preprocessing unit comprises a digital low-pass smoothing filter, coupled behind said analog-digital converter unit, and a high-pass offset filter connected with said digital low-pass smoothing filter.

9. A system for monitoring inflation pressure of a vehicle tire, comprising:

a vertical acceleration sensor and a vehicle longitudinal speed sensor operable to determine vertical acceleration data related to the vehicle tire;

an analyzing unit comprising a trainable estimating unit in the form of a neuronal network, said estimating unit being trained via predeterminable training example data having different tire inflation pressure values and vehicle longitudinal speed values, wherein, in a trained condition, said estimating unit determines the inflation pressure of the vehicle tire at least as a function of the sensed vertical acceleration data and vehicle longitudinal speed data, said vertical acceleration and vehicle longitudinal speed data being fed one of directly and in a preprocessed form to said estimating unit.

10. A method for monitoring tire pressure of a vehicle tire, the method comprising the acts of:

sensing vertical acceleration data related to the vehicle tire;

sensing vehicle longitudinal speed data of the vehicle;

initially training an analyzing device containing a trainable estimating unit, said initial training being performed with predeterminable training example data having different tire inflation pressure values and vehicle longitudinal speed values;

feeding the sensed vertical acceleration data and vehicle longitudinal speed data to said analyzing device; and

in the trained condition, determining the tire pressure in the analyzing device at least as a function of said sensed vertical acceleration data and vehicle longitudinal speed data.

11. The method according to claim 10, wherein the act of feeding the data further comprises the act of initially preprocessing the vertical acceleration and vehicle longitudinal speed data prior to feeding said data to said analyzing device.

12. The method according to claim 10, further comprising the acts of:

generating road condition information as a function of said sensed vertical acceleration and vehicle longitudinal speed data; and

controlling an activation and deactivation of said estimating unit using said road condition information as a function of whether a momentary sensed vertical acceleration and vehicle longitudinal speed are, in each case, inside or outside of pertaining predeterminable value ranges.

13. The method according to claim 11, further comprising the acts of:

generating road condition information as a function of said sensed vertical acceleration and vehicle longitudinal speed data; and

controlling an activation and deactivation of said estimating unit using said road condition information as a function of whether a momentary sensed vertical acceleration and vehicle longitudinal speed are, in each case, inside or outside of pertaining predeterminable value ranges.

14. The method according to claim 11, wherein the preprocessing act further comprises the acts of computing one or more time derivatives of said sensed vertical acceleration value;

and

feeding said one or more time derivatives, in addition to said sensed vertical acceleration value, to said estimating unit as input quantities.

15. The method according to claim 11, wherein said preprocessing act further comprises the act of selecting information from a post-connected FFT unit having a pertaining selection unit, said information being fed as input quantities to said estimating unit.