Method and apparatus for classifying seat occupant weight

• US 6,476,516 B1
• Filed: 08/25/2000
• Issued: 11/05/2002
• Est. Priority Date: 09/03/1999
• Status: Expired due to Fees

• Current Assignee: Siemens VDO Automotive, Inc. (Continental AG)
• Original Assignee: Siemens VDO Automotive, Inc. (Continental AG)
• Inventors: Reich, Daniel
• Primary Examiner(s): Fleming, Fritz
• Assistant Examiner(s): DeBeradinis, Robert L
• Application Number:
  US09/648,222
• Time in Patent Office: 802 Days
• Field of Search: 307/10.1, 307/9.1, 280/734, 280/735, 180/271, 177/211, 177/144, 701/45
• US Class Current: 307/10.1
• 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
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands

Abstract

A method and apparatus is provided that classifies a seat occupant into one of several different weight classes based on an estimated value of the seat occupant weight. An occupant'"'"'s measured weight varies when the occupant'"'"'s seating position changes or when the vehicle travels over adverse road conditions. The estimated value of the occupant weight is compared to a series of upper and lower weight thresholds assigned to each of the weight classes to generate an occupant weight sample class. Over a period of time, several estimated weight values are compared to the weight class thresholds. Once a predetermined number of consistent and consecutive occupant weight sample classes is achieved, the occupant is locked into a specific occupant weight class. When the weight class is locked, the separation value between the upper and lower thresholds is increased to account for minor weight variations due to adverse road conditions and changes in occupant position. The weight class is unlocked when a predetermined number of inconsistent classes is observed and the process is repeated.

Claims

1. A method for classifying a seat occupant into a weight class comprising the steps of:

(a) measuring the weight of a seat occupant to generate an estimated weight;

(b) comparing the estimated weight to a series of weight classes each having at least one weight class threshold to determine an individual classification sample;

(c) repeating steps (a) and (b) until a predetermined number of individual classification samples having the same value is achieved; and

(d) locking the individual classification sample as the occupant weight class.

2. The method according to claim 1 including the steps of generating an occupant weight class signal after step (d), transmitting the occupant weight class signal to a control unit, and modifying deployment of an airbag based on the occupant weight class signal.

3. The method according to claim 2 including the steps of:

(e) unlocking the individual classification sample when a predetermined number of non-equal individual classification samples is achieved; and

(f) returning to step (a) when step (e) is satisfied.

4. The method according to claim 3 wherein step (b) further includes assigning each weight class an upper threshold and a lower threshold, comparing the estimated weight to the upper and lower thresholds for the last known weight class, and setting the individual classification sample equal to the last known weight class if the estimated weight is between the upper and lower thresholds for the last known weight class.

5. The method according to claim 4 including the step of setting the individual classification sample equal to a next higher weight class if the estimated weight is greater than the upper threshold for the last known weight class or setting the individual classification sample equal to a next lower weight class if the estimated weight is less than the lower threshold for the last known weight class.

6. The method according to claim 5 including the steps of increasing the value of the upper threshold of the individual classification sample by a first predetermined amount and decreasing the value of the lower threshold of the individual classification sample by a second predetermined amount once the individual classification sample is locked.

7. The method according to claim 5 including the steps of decreasing the value of the upper threshold of the individual classification sample by a first predetermined amount and increasing the value of the lower threshold of the individual classification sample by a second predetermined amount after the individual classification sample is unlocked.

8. The method according to claim 1 further includes the steps of

filtering out unintended weight class changes by increasing hysteresis subsequent to locking the individual classification sample by providing a track mode having a first set of thresholds for each of the weight classes and a lock mode having a second set of thresholds for each of the weight classes that is different than the first set of thresholds;

and

determining whether the track or lock mode is applicable prior to step (b).

9. The method according to claim 8 including the step of

providing the first set of thresholds with upper track thresholds and lower track thresholds for each of the weight classes;

providing the second set of thresholds with upper lock thresholds having a value greater than each respective upper track threshold and a lower lock threshold having a value less than each respective lower track threshold;

beginning in the track mode;

initiating the lock mode when a predetermined number of consistent and consecutive individual classification samples is achieved; and

changing from the lock mode to the track mode when a predetermined number of inconsistent individual classification samples are achieved.

10. The method according to claim 1 wherein step (c) further includes repeating steps (a) and (b) over a period of time prior to performing step (d).

11. A method for modifying airbag deployment based on classifying a seat occupant into a weight class comprising the steps of:

(a) measuring the weight of a seat occupant to generate an estimated weight;

(b) comparing the estimated weight to a series of weight classes each having an upper threshold and a lower threshold;

(c) assigning the estimated weight to the appropriate weight class and designating the assignment as an individual classification sample;

(d) repeating steps (a) through (c) until a predetermined number of consistent and consecutive individual classification samples are achieved;

(e) locking the individual classification sample as the occupant weight class; and

(f) generating a control signal to modify airbag deployment based on the occupant weight class.

12. The method according to claim 11 including the step of unlocking the individual classification sample as the occupant weight class when a predetermined number of inconsistent individual classification samples is achieved before step (f).

13. The method according to claim 12 including the steps of

providing a track mode having a first set of thresholds for each of the weight classes and a lock mode having a second set of thresholds for each of the weight classes that is different than the first set of thresholds; and

determining whether the method is in the track mode or the lock mode prior to step (b).

14. A method according to claim 13 including the step of filtering out unintended weight class changes by providing the first set of thresholds with an upper track threshold and a lower track threshold for each of the weight classes and providing the second set of thresholds with an upper lock threshold having a value greater than the upper track threshold and a lower lock threshold having a value less than the lower track threshold.

15. A method according to claim 14 including the step of beginning in the track mode, initiating the lock mode when a predetermined number of consistent and consecutive individual classification samples is achieved, and moving from the lock mode to the track mode when a predetermined number of inconsistent individual classification samples is achieved.

16. An occupant weight classification system comprising;

a sensor assembly for measuring the weight of a seat occupant to generate an estimated weight signal;

a series of weight class data wherein each weight class has an upper threshold and a lower threshold;

a control unit for receiving said estimated weight signal, comparing said signal to said upper and lower thresholds to assign said signal an appropriate weight class designation, and for locking said signal into an occupant specific weight class when a predetermined number of consistent and consecutive weight class designations is achieved.

17. A system according to claim 16 wherein said control unit compares said estimated weight signal to said series of weight class data over a period of time prior to locking said signal into said occupant specific weight class.

18. A system according to claim 17 wherein said control unit operates in either a track mode having a first set of thresholds for each of the weight classes or a lock mode having a second set of thresholds for each of the weight classes that is different than the first set of thresholds and wherein said control unit and determining whether the track or lock mode is applicable prior to comparing said signal to upper and lower thresholds for said weight classes.

19. A system according to claim 18 wherein said first set of thresholds have upper track thresholds and lower track thresholds for each of said weight classes and said second set of thresholds have upper lock thresholds having a value greater than each respective upper track threshold and a lower lock threshold having a value less than each respective lower track threshold to filter out unintended changes in weight class designation and wherein said control unit operates initially in said track mode, activates said lock mode when said predetermined number of consistent and consecutive weight class designations is achieved, and changes from said lock mode to said track mode when a predetermined number of inconsistent individual classification samples is achieved.

20. A system according to claim 16 including an airbag controller for controlling deployment of an airbag wherein said control unit generates a control signal and transmits said control signal to said airbag controller to modify deployment of said airbag based on said occupant specific weight class.