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Journal Article

Vehicle and Occupant Responses in a Friction Trip Rollover Test

2009-04-20
2009-01-0830
Objective: A friction rollover test was conducted as part of a rollover sensing project. This study evaluates vehicle and occupant responses in the test. Methods: A flat dolly carried a Saab 9-3 sedan laterally, passenger-side leading to a release point at 42 km/h (26 mph) onto a high-friction surface. The vehicle was equipped with roll, pitch and yaw gyros near the center of gravity. Accelerometers were placed at the vehicle center tunnel, A-pillar near the roof, B-pillar near the sill, suspension sub-frame and wheels. Five off-board and two on-board cameras recorded kinematics. Hybrid III dummies were instrumented for head and chest acceleration and upper neck force and moment. Belt loads were measured. Results: The vehicle release caused the tires and then wheel rims to skid on the high-friction surface. The trip involved roll angular velocities >300 deg/s at 0.5 s and a far-side impact on the driver’s side roof at 0.94 s. The driver was inverted in the far-side, ground impact.
Technical Paper

Electronics and Algorithms for Rollover Sensing

2004-03-08
2004-01-0343
Rollover sensing and discrimination generally requires an algorithm that monitors vehicle motion and anticipates conditions that will lead to a rollover. In general, a deploy command is required in a time frame such that safety measures can be activated early enough to protect the occupants. A rollover discrimination system will typically include internal motion sensors, vehicle signals from other on-board sensors, and a microprocessor to execute the deployment algorithm. A supplemental signal path is used to arm the system, making it less susceptible to single point component failures. In this chapter we explore basic concepts of rollover sensors and system mechanization, rollover discrimination algorithms, and arming methodology. A simulation environment that models the performance of the system across part tolerance, temperature extremes and component age is used to estimate the scope of expected discrimination performance in the field.
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