Abstract:
A vehicle seat weight classification system includes a recalibration strategy to ensure sensor accuracy over time. A controller preferably is programmed to periodically sample outputs of the sensors when a seat is unoccupied. Average sensor output information is compared to a currently stored calibration value. If the newly determined average value meets selected criteria, then the sensor is recalibrated using the new information. The system and method of this invention compensates for changes in sensor performance over time caused by changes in system characteristics, such as material offset drift.

Description:
RELATED APPLICATIONS 
     This application claims priority to U.S. provisional application Ser. No. 60/152,424, which was filed on Sep. 3, 1999. 
    
    
     BACKGROUND OF THE INVENTION 
     This invention generally relates to weight classification systems for vehicles. More particularly, this invention relates to a calibration method for calibrating sensors used in a vehicle seat weight classification system. 
     Vehicle safety restraint systems have changed over the years. Seat belts have proven effective at minimizing injuries during accidents. Additional safety devices have been introduced such as air bags. While air bags provide additional benefits, it has become apparent that individualized air bag control would be beneficial. More recently, systems for classifying the weight of a seat occupant have been developed that allow for individualized control of an air bag. 
     One example weight classification system includes a plurality of sensors within a seat base portion of the seat. The sensors provide electrical signals indicative of the seat occupant&#39;s weight. These signals are processed and utilized to determine an air bag deployment strategy according to selected guidelines. 
     One issue presented by such weight classification systems is the possibility for the sensors to become less accurate over time. One issue that must be accommodated is the possibility for material offset drift, which may have an effect on the accuracy of the weight determination. Because the characteristics of a vehicle seat change over time, the performance of the sensors associated with that seat may also change. Therefore, there is a need to recalibrate or accommodate changes in the system over time. 
     This invention addresses the need for automatically recalibrating a weight classification system to compensate for changes in system performance such as material offset drift. 
     SUMMARY OF THE INVENTION 
     In general terms, this invention is a system and method for recalibrating a vehicle seat weight classification system. A system designed according to this invention includes a plurality of sensors in the vehicle seat that provide signals indicating the weight of a load on the seat. A controller communicates with the sensors. The controller also determines when a calibration condition exists. The controller samples outputs of each of the sensors, preferably when there is no load on the seat. The sample sensor outputs preferably are taken intermittently over a selected period of time. The controller determines an average value of the sensors outputs. The average value is then compared to a current calibration value and, if selected conditions are met, the new average value is substituted for the calibrated value. Accordingly, each sensor of the weight classification system can be individually recalibrated to compensate for changes in the system over time. 
     A method of this invention includes several basic steps. The method preferably begins by determining when a calibration condition exists. If the calibration condition exists, a plurality of outputs of the system sensors are sampled over a selected period. An average output of each sensor is determined using the sampled outputs. If the average is within a selected range then the corresponding sensor is recalibrated using the average value. 
     The various features and advantages of this invention will become apparent to those skilled in the art from the following detailed description of the currently preferred embodiment. The drawings that accompany the detailed description can be briefly described as follows. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 diagrammatically illustrates the system designed according to this invention. 
     FIG. 2 is a flow chart diagram illustrating a method of this invention. 
     FIG. 3 is a flow chart diagram illustrating more details of a portion of the flow chart of FIG.  2 . 
     FIG. 4 is a graphical illustration of a portion of the method of this invention. 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
     A vehicle seat weight classification system  20  is schematically shown in FIG. 1. A seat  22  includes a seat back  24  and seat base  26 . A plurality of sensors  28  preferably are provided in the seat base  26 . The sensors  28  preferably are strain gauge sensors that each provide electrical output signals indicative of a deflection in the material of the seat base  26 . The sensors  28 , therefore, provide signals indicative of the weight of a load on the seat base  26 . 
     Further details regarding the preferred operation of the sensors and the weight determination using the system  20  can be found, for example, in U.S. patent application Ser. No. 09/191,719, filed on Nov. 12, 1998, which is commonly owned with this application. The teachings of that document are incorporated into this specification by reference. 
     A controller  30  communicates with the sensors  28 . The controller  30  receives output signals from the sensors  28  and preferably controls the supply of power to the sensors. The controller  30  preferably monitors the output of each sensor to determine the presence of a load on the seat  22 . The controller  30  preferably also manages recalibration of the sensors  28  according to this invention. 
     FIG. 2 includes a flow chart diagram  40  that illustrates the general flow of the inventive method of calibrating the weight classification system  20 . A first step  42  includes determining when it is time to update the calibration of the sensors  28 . This preferably includes utilizing an event that occurs repeatedly and monitoring the number of times that event occurs to trigger a recalibration operation. In one example, the controller  30  monitors the number of times the vehicle ignition is turned on and off. By counting the number of on/off cycles of the ignition, the controller  30  is able to determine when it is time to recalibrate the sensors  28 . In one example, the controller  30  instigates a calibration operation after every twenty on/off ignition cycles. 
     At  44 , the controller  30  prepares the system  20  for recalibration. Once the system is ready for recalibration, each sensor output is sampled at  46 . Prior to proceeding with the calibration operation, the controller  30  preferably verifies that the conditions for calibration still exist at  48 . If there is an indication of a load on the seat, for example, then the calibration operation is preferably cancelled and the controller  30  waits for the next time indicating that a calibration is due. 
     Assuming that the proper conditions for calibration still exist, the controller  30  preferably determines an average output for each sensor at  50 . The standard deviation for each sensor output preferably is also determined at  52 . 
     The next step at  54  is when the controller  30  preferably compares the average output value of each sensor to the current calibration value that is held in memory (not illustrated). If there is a difference between the determined average value and the currently stored calibration value, then the controller  30  preferably updates the calibration of the sensor using the newly determined average. If there is no difference between the determined average value and the currently stored value of a sensor, then there is no need to recalibrate that sensor and the newly determined data preferably is ignored. Lastly, at  56  the new calibration data preferably is stored in memory without overriding the previous calibration information. A system designed according to this invention preferably tracks calibration information over time and maintains old calibration information for later comparisons and other determinations. 
     There are a variety of ways to program the controller  30  to determine when a calibration condition exists. As discussed, counting the number of ignition on/off cycles is one possibility. In another example, the controller  30  automatically performs a recalibration operation after a selected time period has elapsed. Given this description, those skilled in the art will be able to develop an appropriate strategy and program a controller  30  accordingly to meet the needs of a particular situation. 
     As shown in FIG. 3, the controller  30  preferably prepares the system  20  for recalibration in a manner that maximizes energy conservation in the system. In the currently preferred embodiment, the step  44  of preparing the system for recalibration preferably includes several sub-steps. The controller  30  preferably verifies that the chosen event that triggers a recalibration operation has occurred at  60 . The controller  30  preferably then starts a timer at  62  and puts the system into sleep mode at  64 . After the time of the timer has elapsed, the controller  30  preferably wakes up the system at  66 . 
     Once the system is awakened, the sensors  28  preferably are powered using a minimal amount of power for very short times. Depending on the nature of the actual sensors  28 , the frequency of power provided to the sensors and the frequency of the corresponding outputs signals is variable. Those skilled in the art who have the benefit of this description will be able to choose appropriate parameters. 
     FIG. 4 includes a graphical illustration  70  of a sensor output over time. In this example, the sensor has a current calibration value at  72 . During the calibration operation, a plurality of sensor outputs  74  are detected by the controller  30 . An average value of the output  74  is shown at  76 . Because there is a difference between the currently stored calibration value  72  and the determined average  76 , the controller  30  next preferably determines whether the sensor should be recalibrated using the value  76 . Provided that the value  76  is within the range  78 , the controller  30  preferably substitutes the average value  76  for the previously stored calibration value  72 . Sensor  28  is accordingly recalibrated with the new value  76 . The value  72  preferably is maintained in memory for later comparison or other determinations. 
     The range  78  preferably is kept small enough to avoid any unwanted sensor outputs from being used within the calibration process. It is most preferred to calibrate the sensors when there is no load the seat  22 . If a sensor output during a calibration operation is influenced by a load on the seat  22 , then the calibration would not be accurate. Accordingly, the controller  30  is preferably programmed to recognize a sensor average value  76  that only comes within the range  78  as a possible recalibration value. Those skilled in the art who have benefit of this description will be able to choose an appropriate range  78  given the parameters of particular system with which they are working. 
     In the preferred embodiment, the standard deviation of the output value  74  is also determined. If the standard deviation value is outside of a selected range, then the controller  30  preferably is programmed to not utilize that data as part of a recalibration process. Again, spikes or outputs provided by the sensor, which are influenced by a load on the seat preferably are avoided during the calibration process. 
     This invention provides an accurate and reliable way of recalibrating sensors in a weight classification system. Because the materials used in a vehicle seat can change properties over time (i.e., stiffness or resilience in a seat cushion) some recalibration of the sensors over time is useful. Currently known weight classification systems include sensors that measure deflections in the seat material on the order of micrometers. Therefore, controlled accuracy in sensor calibration is highly desired. 
     The preceding description is exemplary rather than limiting in nature. Variations and modifications to the disclosed examples may become apparent to those skilled in the art that do not necessarily depart from the purview and spirit of this invention. The scope of legal protection given to this invention can only be determined by studying the following claims.