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: At least two weight sensors are disposed below the seat such that measured values of the at least two weight sensors are representative of a force which is transmitted from the seat to its mount. At least two measured values are detected at a chronological interval from each other within a predetermined period of time by the weight sensors. A weight sensor is arranged in a first region of the seat and a weight sensor is arranged in a second region of the seat. A gradient is determined from the respective at least two measured values for the particular weight sensor. The jamming of the seat is recognized in dependence on the presence of different gradient signs that are assigned to the weight sensor disposed in the first region of the seat and to the weight sensor disposed in the second region of the seat.

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 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 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 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.

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.

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.

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.

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.