Siemens Aktiengesellschaft

Siemens Vdo Automotive Corporation

Continental Automotive Systems Us, Inc.

Andreas Knueppel

Gerd Winkler

Gerald Schicker

Tobias Tyroller

Robert M Andres

Thomas J Malbouef, Jr

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. Electrically erasable programmable read-only memory is used to reduce complications and inaccuracies associated with seat occupant weight sensors that have mounting configurations that vary depending upon the vehicle.

Vehicle occupant weight classification system

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. A method of reducing runtime in a system algorithm prioritizes calculations so that they are conducted on the side having the higher likelihood of having conditions requiring restraint deployment. Prioritizing calculations may also avoid refiring on a side that has already deployed a restraint, reducing the total number of calculations that the system needs to conduct. A method of evaluating a plausibility that a fire decision from a given sensor is the result of an event necessitating deployment of a restraint includes a plausibility check that checking the states of other sensors in the system before issuing a restraint firing request. The specific terms used in the plausibility check can be adjusted to accommodate different vehicle hardware configurations, vehicle setups and requirements.

Vehicle passenger restraint system with distributed sensors

An air bag system () provides a central controller (), a multiple of satellite sensors () and a multiple of deployable air bags (). The central controller () 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.

Multiple-satellite sensors algorithm wake up and reset strategy for an inflatable restraint system

Multiple-satellite sensor algorithm wake up and reset strategy for an inflatable restraint system

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Troy, MI, United States of America

Andreas Knueppel