Method for the determination of parameters of a seat passenger

• US 7,269,533 B2
• Filed: 08/28/2002
• Issued: 09/11/2007
• Est. Priority Date: 09/06/2001
• Status: Expired due to Fees

• Current Assignee: IEE International Electronics & Engineering SA (Aerospace Hi-Tech Holding Group Company Limited)
• Original Assignee: IEE International Electronics & Engineering SA (Aerospace Hi-Tech Holding Group Company Limited)
• Inventors: Di Mario Cola, Patrick, Theiss, Christian, Schifflers, Marc
• Primary Examiner(s): Tsai; Carol S. W.
• Assistant Examiner(s): Charioui; Mohamed
• Application Number:
  US10/489,028
• Publication Number:
  US 20050001411A1
• Time in Patent Office: 1,840 Days
• Field of Search: 702/91, 702/93, 702/94, 702/98, 702/101, 702/104, 702/105, 702/116, 702/138, 702/141, 702/142, 702/146, 702/173, 702/181, 702/182, 702/189, 702/193, 702/199, 701/45, 280/732, 280/735
• US Class Current: 702/181
• CPC Class Codes: B60R 21/01516 using force or pressure sensing means
• CPC Class Codes: G01G 19/4142 for controlling activation of safety devices, e.g. airbag systems electrical circuits for triggering safety arrangements in case of vehicle accidents B60R21/015

Abstract

A method for the determination of a physical property parameter of a seat passenger includes getting a reading of at least two parameters from an occupancy sensor; plotting a probability vector which shows, for each value of the physical property, the probability to cause the readings of the at least two parameters; and correlating the physical property parameter to the range of values of the probability vector with the highest probabilities.

Claims

1. A method for the determination of a weight parameter of a seat passenger, comprising the steps of:

a) getting a reading of at least two parameters from an occupancy sensor;

b) plotting a probability vector, said probability vector showing, for a plurality of weight ranges, the probability for a seat passenger belonging to a weight range to cause said readings of said at least two parameters;

c) correlating said weight parameter to a range of values of said probability vector with the highest probabilities.

2. The method according to claim 1, wherein said step of plotting a probability vector comprises the steps of:

a) initializing the probability vector by setting the probability for each weight range to a specific value; and

b) for each parameter, reducing the probability for each weight value for which the respective parameter is outside of calibration curves, said calibration curves showing the maximum and minimum parameter values for each weight value.

3. The method according to claim 2, wherein said step of correlating said weight parameter to said range of values with the highest probabilities comprises the steps of

a) calculating an average weight value from the range of values of said probability vector with the highest probability;

b) setting said weight parameter to be determined to equal said average weight value.

4. The method according to claim 2, wherein said step of correlating said weight parameter to said range of values with the highest probabilities comprises the steps of

a) calculating a first average weight value from the range of values of said probability vector with the highest probability;

b) calculating a second average weight value from the range of values of said probability vector for which the probability is equal or higher than a second highest probability;

c) setting said weight parameter to be determined to equal a rounded average of said first and second average weight value.

5. The method according to claim 2, wherein said occupancy sensor is a pressure sensitive seat sensor and/or a capacitive sensor.

6. The method according to claim 1, wherein said step of correlating said weight parameter to said range of values with the highest probabilities comprises the steps of

a) calculating an average weight value from the range of values of said probability vector with the highest probability;

b) setting said weight parameter to be determined to equal said average weight value.

7. The method according to claim 1, wherein said step of correlating said weight parameter to said range of values with the highest probabilities comprises the steps of

a) calculating a first average weight value from the range of values of said probability vector with the highest probability;

b) calculating a second average weight value from the range of values of said probability vector for which the probability is equal or higher than a second highest probability;

c) setting said weight parameter to be determined to equal a rounded average of said first and second average weight value.

8. The method according to claim 1, wherein said occupancy sensor is a pressure sensitive seat sensor or a capacitive sensor.

9. A method for the determination of a weight parameter of a seat passenger, comprising the steps of:

a) getting a reading of at least two parameters from an occupancy sensor;

b) providing weight ranges and plotting a probability vector, said probability vector showing, for each weight range, the probability for a seat passenger belonging to said weight range to cause said readings of said at least two parameters;

c) correlating said weight parameter to a range of values of said probability vector with the highest probabilities.

10. The method according to claim 9, wherein said step of plotting a probability vector comprises the steps of:

a) initializing the probability vector by setting the probability for the entire weight range to a specific value; and

b) for each parameter, reducing the probability for each weight value for which the respective parameter is outside of calibration curves, said calibration curves showing the maximum and minimum parameter values for each weight value.

11. The method according to claim 9, wherein said step of correlating said weight parameter to said range of values with the highest probabilities comprises the steps of:

a) calculating an average weight value from the range of values of said probability vector with the highest probability;

b) setting said weight parameter to be determined to equal said average weight value.

12. The method according to claim 9, wherein said step of correlating said weight parameter to said range of values with the highest probabilities comprises the steps of:

a) calculating a first average weight value from the range of values of said probability vector with the highest probability;

b) calculating a second average weight value from the range of values of said probability vector for which the probability is equal or higher than a second highest probability;

c) setting said weight parameter to be determined to equal a rounded average of said first and second average weight value.

13. The method according to claim 9, wherein said occupancy sensor is a pressure sensitive seat sensor or a capacitive sensor.

14. A method for controlling the deployment of a restraint system, comprising the steps of:

a) determining a weight parameter of a seat passenger by

i) getting a reading of at least two parameters from an occupancy sensor;

ii) providing weight ranges and plotting a probability vector, said probability vector showing, for each weight range, the probability for a seat passenger belonging to said weight range to cause said readings of said at least two parameters,

iii) correlating said weight parameter to a range of values of said probability vector with the highest probabilities; and

b) switching the restraint system in a deployment mode which is adapted to a passenger with said weight parameter.

15. The method according to claim 14, wherein said step of correlating said weight parameter to said range of values with the highest probabilities comprises the steps of

a) calculating an average weight value from the range of values of said probability vector with the highest probability;

b) setting said weight parameter to be determined to equal said average weight value.

16. The method according to claim 14, wherein the said step of correlating said weight parameter to said range of values with the highest probabilities comprises the steps of

a) calculating a first average weight value from the range of values of said probability vector with the highest probability;

b) calculating a second average weight value from the range of values of said probability vector for which the probability is equal or higher than a second highest probability;

c) setting said weight parameter to be determined to equal a rounded average of said first and second average weight value.

17. The method according to claim 14, wherein said occupancy sensor is a pressure sensitive seat sensor and/or a capacitive sensor.

18. A method for controlling the deployment of a secondary restraint system, comprising the steps of:

a) determining a weight parameter of a seat passenger by

i) getting a reading of at least two parameters from an occupancy sensor;

ii) plotting a probability vector, said probability vector showing, for a plurality of weight ranges, the probability for a seat passenger belonging to a weight range to cause said readings of said at least two parameters;

iii) correlating said weight parameter to a range of values of said probability vector with the highest probabilities; and

b) switching the secondary restraint system in a deployment mode which is adapted to a passenger with said weight parameter.