Abstract: A vehicle occupant classification system categorizes vehicle occupants into various classes such as adult, child, infant, etc. to provide variable control for a vehicle restraint system such as an airbag. The classification system utilizes sensors that are installed in various locations in the vehicle. The sensors are used to generate a three-dimensional profile for the vehicle occupant. Various factors can affect the accuracy of this three-dimensional profile. Fuzzy logic is used to reduce some of the inaccuracies by providing multiple decision levels for various stages of the classification. Inaccuracies are also caused by sensors shifting within the system from their original position. This condition creates offset and the system evaluates this offset and generates a correction factor to provide a more accurate three-dimensional profile.

Abstract: The recognition of seat occupancy of a seat is achieved by recording at least one measured signal by way of a seat occupancy sensor. The measured signal is allocated a weight signal by way of an allocation rule, which is representative of a weight with which the seat is occupied. The allocation rule is altered when the weight signal over the course of time is first greater than a given upper threshold and when further, during a given first duration the weight signal lies in a first weight range at a weight zero value. The allocation rule is altered such that the then current measured signal is allocated the weight signal reduced by a given percentage from the weight signal. The allocation rule is further altered when the weight signal lies around the weight zero value in a given second weight range during a given second duration, which is much longer than the first duration.

Abstract: A device and a method for differentiating between a person sitting on the seat surface of a vehicle seat and an object such as, for example, a child seat. The device has a cushion provided with weight sensors which are distributed over the seat surface in a plane manner, first weight sensors being arranged in a central region and second weight sensors being arranged on the edge of the seat surface. At least one central weight sensor is differentiated from a plurality of second weight sensors on the edge of the seat surface in that it always emits a comparatively low sensor signal when subjected to the same weight load.

Abstract: In an occupant detection or classification system for a motor vehicle, a sensor mat (2) measures the pressure or pressure distribution on a seating surface. A control unit (4) receives the signals from the sensor mat (2) representing an occupancy of the vehicle seat. The temperature of the foam core (1) underlying the seating surface is measured at a location other than in the center of the foam core and, specifically, at the control unit (4).

Abstract: A device for detecting the seat occupancy status in a motor vehicle is configured in a seat that is supported to allow movement in a direction on front and rear supports on a seat rail attached to the floor of the motor vehicle. The seat, at the lower end of its backrest, has seat belt anchorage points above the rear supports for mechanical anchorage of a seat belt. Weight sensors assigned to the rear supports are arranged in the force path below the seat belt anchorage points and above the seat rail.

Abstract: The recognition of seat occupancy of a seat is achieved by recording at least one measured signal by way of a seat occupancy sensor. The measured signal is allocated a weight signal by way of an allocation rule, which is representative of a weight with which the seat is occupied. The allocation rule is altered when the weight signal over the course of time is first greater than a given upper threshold and when further, during a given first duration the weight signal lies in a first weight range at a weight zero value. The allocation rule is altered such that the then current measured signal is allocated the weight signal reduced by a given percentage from the weight signal. The allocation rule is further altered when the weight signal lies around the weight zero value in a given second weight range during a given second duration, which is much longer than the first duration.

Abstract: A vehicle occupant classification system categorizes vehicle occupants into various classes such as adult, child, infant, etc. to provide variable control for a vehicle restraint system such as an airbag. The classification system utilizes sensors that are installed in various locations in the vehicle. The sensors are used to generate a three-dimensional profile for the vehicle occupant. Various factors can affect the accuracy of this three-dimensional profile. Fuzzy logic is used to reduce some of the inaccuracies by providing multiple decision levels for various stages of the classification. Inaccuracies are also caused by sensors shifting within the system from their original position. This condition creates offset and the system evaluates this offset and generates a correction factor to provide a more accurate three-dimensional profile.

Abstract: A device for differentiating between a person sitting on the seat surface of a vehicle seat and an object includes at least one largely flat bearing surface that is arranged over a large part of the seat surface including a central region. The novel device includes a vehicle seat, a cushion with weight sensors that are distributed over the seat surface of the vehicle seat in a plane manner, and an evaluation unit to which the signals of the weight sensors are supplied. A central region of the seat surface is curved in a concave manner in the direction of the bottom of the vehicle, in such a way that a first weight sensor arranged therein is closer to the bottom of the vehicle than a plurality of second weight sensors arranged in the region of the seat surface covered by the object, outside the central region. The capacity to differentiate between a person and an object is especially useful when the object is a child seat. In this case, the triggering of a passenger retaining means must be prevented.

Abstract: A vehicle occupant classification system categorizes vehicle occupants into various classes such as adult, child, infant, etc. to provide variable control for a vehicle restraint system such as an airbag. The classification system utilizes sensors that are installed in various locations in the vehicle. The sensors are used to generate a three-dimensional profile for the vehicle occupant. Various factors can affect the accuracy of this three-dimensional profile. Fuzzy logic is used to reduce some of the inaccuracies by providing multiple decision levels for various stages of the classification. Inaccuracies are also caused by sensors shifting within the system from their original position. This condition creates offset and the system evaluates this offset and generates a correction factor to provide a more accurate three-dimensional profile.

Abstract: A method and a device allow to detect and optionally to indicate the improper use of a seat. For this purpose, an estimated value of a variable characteristic of a mass that rests on a seating area of a seat is determined depending on at least one force that acts upon the seating area and that is detected by one or more force sensors. The estimated value is found to be reliable or unreliable depending on the oscillation behavior of the measured signal of the at least one force sensor.

Abstract: A device and a method for differentiating between a person sitting on the seat surface of a vehicle seat and an object such as, for example, a child seat. The device has a cushion provided with weight sensors which are distributed over the seat surface in a plane manner, first weight sensors being arranged in a central region and second weight sensors being arranged on the edge of the seat surface. At least one central weight sensor is differentiated from a plurality of second weight sensors on the edge of the seat surface in that it always emits a comparatively low sensor signal when subjected to the same weight load.

Abstract: A distributed sensing system and method improves sensing of events that may require restraint deployment in a vehicle by distinguishing between deployment events and non-deployment events using data from more than one sensor. A transmission check process continuously monitors an incoming signal from a sensor and counts the number of data samples that exceed a selected value using a counter. If the counter value exceeds a selected threshold, the system indicates that the transmission check is fulfilled and allows deployment of the restraint. A correlation acceleration difference (CAD) algorithm calculates a CAD term corresponding to a degree of intrusion of a foreign object into a vehicle at a given time. Acceleration data from sensors disposed at supporting sides of the vehicle are checked if they respond to an event, and the absolute values of the acceleration data are subtracted from each other to obtain an absolute difference from which the CAD term is calculated.

Abstract: A method and a device allow to detect and optionally to indicate the improper use of a seat. For this purpose, an estimated value of a variable characteristic of a mass that rests on a seating area of a seat is determined depending on at least one force that acts upon the seating area and that is detected by one or more force sensors. The estimated value is found to be reliable or unreliable depending on the oscillation behavior of the measured signal of the at least one force sensor.

Abstract: An air bag system (12) provides a central controller (14), a multiple of satellite sensors (16) and a multiple of deployable air bags (18). The central controller (14) runs the impact event algorithms. The number of satellites which are allowed to activate algorithms at any one time is limited. The minimum number of satellites required for full protection is the maximum number of satellite sensors allowed to wake up an impact event algorithm at any one time. An order for algorithm wake is also specified since the number of algorithms allowed is less than the total number of satellite sensors.

Abstract: In an occupant detection or classification system for a motor vehicle, a sensor mat (2) measures the pressure or pressure distribution on a seating surface. A control unit (4) receives the signals from the sensor mat (2) representing an occupancy of the vehicle seat. The temperature of the foam core (1) underlying the seating surface is measured at a location other than in the center of the foam core and, specifically, at the control unit (4).

Abstract: An air bag system (12) provides a central controller (14), a multiple of satellite sensors (16) and a multiple of deployable air bags (18). The central controller (14) runs the impact event algorithms. The number of satellites which are allowed to activate algorithms at any one time is limited. The minimum number of satellites required for full protection is the maximum number of satellite sensors allowed to wake up an impact event algorithm at any one time. An order for algorithm wake is also specified since the number of algorithms allowed is less than the total number of satellite sensors.

Abstract: An air bag system (12) provides a central controller (14), a multiple of satellite sensors (16) and a multiple of deployable air bags (18). The central controller (14) runs the impact event algorithms. The number of satellites which are allowed to activate algorithms at any one time is limited. The minimum number of satellites required for full protection is the maximum number of satellite sensors allowed to wake up an impact event algorithm at any one time. An order for algorithm wake is also specified since the number of algorithms allowed is less than the total number of satellite sensors.

Abstract: Sensors are mounted within a seat structure for measuring seat occupant weight. The sensors can be mounted in any one of various sensor configurations. So that common hardware can be used for each different sensor configuration, a virtual matrix is created and output from the sensors is mapped into the virtual matrix. The virtual matrix includes virtual cell locations that do not have a corresponding sensor output; i.e., there are fewer physical cells (sensors) than virtual cell locations in the virtual matrix. A weight output signal from each sensor is mapped into the corresponding position in the virtual matrix and the remaining virtual cell locations have values assigned to them based on data supplied by the surrounding physical cells. Seat occupant weight is determined based on output from the virtual matrix and the occupant is placed into one of the various occupant classifications. Deployment force of a restraint system is controlled based on the classification of the seat occupant.

Abstract: A vehicle occupant classification system categorizes vehicle occupants into various classes such as adult, child, infant, etc. to provide variable control for a vehicle restraint system such as an airbag. The classification system utilizes sensors that are installed in various locations in the vehicle. The sensors are used to generate a three-dimensional profile for the vehicle occupant. Various factors can affect the accuracy of this three-dimensional profile. Fuzzy logic is used to reduce some of the inaccuracies by providing multiple decision levels for various stages of the classification. Inaccuracies are also caused by sensors shifting within the system from their original position. This condition creates offset and the system evaluates this offset and generates a correction factor to provide a more accurate three-dimensional profile.

Abstract: A vehicle occupant classification system categorizes vehicle occupants into various classes such as adult, child, infant, etc. to provide variable control for a vehicle restraint system such as an airbag. The classification system utilizes sensors that are installed in various locations in the vehicle. The sensors are used to generate a three-dimensional profile for the vehicle occupant. Various factors can affect the accuracy of this three-dimensional profile. Fuzzy logic is used to reduce some of the inaccuracies by providing multiple decision levels for various stages of the classification. Inaccuracies are also caused by sensors shifting within the system from their original position. This condition creates offset and the system evaluates this offset and generates a correction factor to provide a more accurate three-dimensional profile.