Weight classification system

• US 6,636,792 B2
• Filed: 09/27/2001
• Issued: 10/21/2003
• Est. Priority Date: 09/29/2000
• Status: Expired due to Fees

• Current Assignee: Siemens VDO Automotive Corporation (Siemens AG)
• Original Assignee: Siemens VDO Automotive Corporation (Siemens AG)
• Inventors: Morrell, Scott, Reich, Daniel, Kremer, Maria, Graf, Robert, Lichtinger, Harald, Curtis, Brian M.
• Primary Examiner(s): Black, Thomas G.
• Assistant Examiner(s): MANCHO, RONNIE M
• Application Number:
  US09/965,390
• Publication Number:
  US 20020043789A1
• Time in Patent Office: 754 Days
• Field of Search: 701/45, 701/49, 280/735, 280/801.1, 280/733, 280/806, 738/823.91, 738/826.37, 738/620.8, 738/623.22, 180/273, 180/271, 180/282, 180/268, 177/144, 177/245, 177/211, 177/136
• US Class Current: 701/45
• CPC Class Codes: B60N 2/002 Seats provided with an occupancy detection means mounted therein or thereon detection means responsive to presence or absence of children B60N2/266
• CPC Class Codes: B60R 2021/01006 Mounting of electrical components in vehicles
• CPC Class Codes: B60R 21/01516 using force or pressure sensing means
• CPC Class Codes: B60R 21/0155 sensing belt tension
• CPC Class Codes: B60R 21/01556 Child-seat detection systems
• CPC Class Codes: B60R 22/18 Anchoring devices
• 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 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. A plurality of weight sensors are used to measure the weight exerted by a seat occupant against a seat bottom and are used to determine center of gravity for the seat occupant. A seat belt force sensor is also used to assist in classifying the seat occupant. Compensation factors using the seat belt force and center of gravity information are used to generate an estimated weight value. 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.

Claims

1. A vehicle weight classification system comprising:

a seat assembly having a seat frame for supporting a seat bottom and a seat mount for attachment to a vehicle floor;

a seat belt assembly for securing a seat occupant to said seat assembly;

a plurality of weight sensors mounted to said seat frame for generating a plurality of weight signals in response to a weight force applied to said seat bottom wherein said plurality of weight sensors comprises a first sensor mounted at a front right side corner of said seat bottom between said seat frame and said seat mount, a second sensor mounted at a front left side corner of said seat bottom between said seat frame and said seat mount, a third sensor mounted at a rear right side corner of said seat bottom between said seat frame and said seat mount, and a fourth sensor mounted at a rear left side corner of said seat bottom between said seat frame and said seat mount and wherein said plurality of weight signals comprises a first weight signal generated by said first sensor, a second weight signal generated by said second sensor, a third weight signal generated by said third sensor, and a fourth weight signal generated by said fourth sensor, said first and second weight signals being combined to produce a front weight portion signal and said third and fourth weight signals being combined to produce a rear weight portion signal;

at least one seat belt force sensor for generating a seat belt force signal;

an electronic control unit for receiving said weight signals and seat belt force signals to determine occupant weight, comparing said front and rear weight portion signals to each other to determine center of gravity, generating an occupant classification based on said occupant weight and center of gravity, and transmitting an output control signal based on said occupant classification; and

an airbag module for receiving said output control signal to control airbag deployment based on said occupant classification.

2. A system according to claim 1 wherein said front and rear weight portion signals are combined to produce an initial seat occupant weight and wherein said electronic control unit modifies said initial seat occupant weight based on said seat belt force signal and said center of gravity to produce a final seat occupant weight, said output control signal being generated based on said final seat occupant weight.

3. A vehicle weight classification system comprising:

a seat assembly having a seat frame for supporting a seat bottom and a seat mount for attachment to a vehicle floor;

a seat belt assembly for securing a seat occupant to said seat assembly;

a plurality of weight sensors mounted to said seat frame for generating a plurality of weight signals in response to a weight force applied to said seat bottom wherein said plurality of weight sensors comprises a first sensor mounted at a front right side corner of said seat bottom between said seat frame and said seat mount, a second sensor mounted at a front left side corner of said seat bottom between said seat frame and said seat mount, a third sensor mounted at a rear right side corner of said seat bottom between said seat frame and said seat mount, and a fourth sensor mounted at a rear left side corner of said seat bottom between said seat frame and said seat mount and;

at least one seat belt force sensor for generating a seat belt force signal;

an electronic control unit for receiving said weight signals and seat belt force signals to determine occupant weight, generating an occupant classification based on said occupant weight and center of gravity, and transmitting an output control signal based on said occupant classification;

wherein each of said weight sensors includes a bending element mounted between said seat frame and said seat mount, at least one strain gage assembly mounted on said bending element, and an integrated electronics package for electrically connecting said strain gage to said electronic control unit; and

an airbag module for receiving said output control signal to control airbag deployment based on said occupant classification.

4. A system according to claim 3 wherein said electronics package includes flexible printed circuit board mounted to said bending element and an application specific integrated circuit supported by said bending element for conditioning said weight signal.

5. A system according to claim 3 wherein said bending element includes a first end mountable to said seat frame, a second end mountable to said seat mount, and a bendable center portion having an upper surface and a lower surface wherein a groove is formed in one of said upper or lower surfaces extending along the width of said bending element to localize strain in said bendable center portion.

6. A system according to claim 5 wherein said strain gage assembly is mounted on the other of said upper or lower surfaces, facing opposite from said groove.

7. A system according to claim 3 wherein said electronic control unit includes a power regulator connectible to a power source, a microprocessor for analyzing said weight signals and said seat belt force signals, and a communication bus for interacting with said airbag control module.

8. A system according to claim 7 wherein said electronic control unit includes a plastic housing having integrated insert molded sealed connectors for connection to said power source and said electronics package.

9. A system according to claim 7 including a series of weight class data storable in said electronic control unit wherein each weight class has an upper threshold and a lower threshold wherein said microprocessor for generates an estimated weight signal based on the combination of said plurality of weight signals, compares said estimated weight signal to said upper and lower thresholds to assign said signal an appropriate weight class designation, and locks said estimated weight signal into an occupant specific weight class when a predetermined number of consistent and consecutive weight class designations is achieved.

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

(a) measuring a weight force of a seat occupant exerted against a seat bottom to generate a weight signal;

(b) measuring a seat belt force generated by securing the seat occupant to a vehicle seat with a seat belt assembly to generate a seat belt force signal;

(c) determining center of gravity of the seat occupant based on said weight signal;

(d) classifying the seat occupant into a predetermined weight classification based on said weight and seat belt force signals including the steps of

(d1) generating an estimated weight based on the weight signal;

(d2) comparing the estimated weight to a series of weight classes each having at least one weight class threshold to determine an individual classification sample;

(d3) repeating steps (d1) and (d2) until a predetermined number of individual classification samples having the same value is achieved;

(d4) locking the individual classification sample as the occupant weight class; and

(d5) generating an occupant weight class signal;

(e) generating an output control signal based on seat occupant classification represented by the occupant weight class signal; and

(f) controlling deployment of a safety device based via the output control signal.

11. The method according to claim 10 including the step of filtering out momentary events prior to step (d4).

12. The method according to claim 11 wherein step (d3) further includes repeating steps (d1) and (d2) for at least five seconds prior to locking the individual classification sample.

13. The method according to claim 10 including the step of updating weight class determination at least one time per second prior to locking the individual classification sample.

14. The method according to claim 10 wherein step (a) further includes

mounting a first sensor at a right front portion of the seat bottom to generate a right front weight signal;

mounting a second sensor at a left front portion of the seat bottom to generate a left front weight signal;

mounting a third sensor at a right rear portion of the seat bottom to generate a right rear weight signal;

mounting a fourth sensor at a left rear portion of the seat bottom to generate a left rear weight signal; and

generating the estimated weight based on the right front, left front, right rear, and left rear weight signals.

15. The method according to claim 14 wherein step (c) further includes combining the right front and left front weight signals to generate a front weight portion signal and combining the right rear and left rear weight signals to generate a rear weight portion signal, and comparing the front and rear weight portion signals to each other to determine the center of gravity.

16. The method according to claim 15 including the step of generating a first weight compensation factor based on the seat belt force signal.

17. The method according to claim 16 including the steps of generating a second weight compensation factor based on the center of gravity and adjusting the estimated weight via the first and second weight compensation factors to determine an adjusted seat occupant weight.

18. The method according to claim 17 wherein the adjusted seat occupant weight is determined prior to locking the individual classification sample.

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

(a) measuring a weight force of a seat occupant exerted against a seat bottom to generate a weight signal;

(b) measuring a seat belt force generated by securing the seat occupant to a vehicle seat with a seat belt assembly to generate a seat belt force signal;

(c) determining center of gravity of the seat occupant based on said weight signal;

(d) classifying the seat occupant into a predetermined weight classification based on said weight and seat belt force signals including the steps of

(d1) generating an estimated weight based on the weight signal;

(d2) comparing the estimated weight to a series of weight classes each having at least one weight class threshold to determine an individual classification sample;

(d3) repeating steps (d1) and (d2) until a predetermined number of individual classification samples having the same value is achieved;

(d4) locking the individual classification sample as the occupant weight class; and

(d5) generating an occupant weight class signal

(d6) unlocking the individual classification sample when a predetermined number of non-equal individual classification samples is achieved; and

(d7) returning to step (a) when step (d6) is satisfied;

(e) generating an output control signal based on seat occupant classification; and

(f) controlling deployment of a safety device based via the output control signal.

20. The method according to claim 19 wherein step (d2) further includes assigning each weight class an upper threshold and a lower threshold, comparing the estimated weight to the upper and lower thresholds for a 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.

21. The method according to claim 20 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.

22. The method according to claim 21 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.

23. The method according to claim 21 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.

24. The method according to claim 19 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 (d2).

25. The method according to claim 24 including the step of 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.

26. The method according to claim 25 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.

27. The method according to claim 19 wherein step (d6) further includes waiting at least five seconds before unlocking the individual classification sample.

28. A vehicle weight classification system comprising:

a seat assembly having a seat frame for supporting a seat bottom;

a seat belt assembly for securing a seat occupant to said seat assembly, said seat belt assembly including a male member and a female member for receiving said male member to secure the seat occupant to the seat assembly;

a single piece rigid member directly attached to only one of said male or female members and having a first end for supporting a seat belt portion and a second end integrally formed with said first end for attachment to a vehicle structure wherein said rigid member includes a neck portion positioned between said first and second ends having a width that is less than the width of said first and second ends;

a plurality of weight sensors mounted to said seat frame for generating a plurality of weight signals in response to a weight force applied to said seat bottom;

at least one seat belt force sensor for generating a seat belt force signal, said seat belt force sensor being mounted on said rigid member between said first and second ends for measuring a force exerted on said rigid member by a tension force applied to said seat belt portion wherein said seat belt force sensor is mounted on said neck portion;

an electronic control unit for receiving said weight signals and seat belt force signals to determine occupant weight and center of gravity, generating an occupant classification based on said occupant weight and center of gravity, and transmitting an output control signal based on said occupant classification; and

an airbag module for receiving said output control signal to control airbag deployment based on said occupant classification.