Search Results

An airbag upon collision of automobiles must finish expanding at the time when the driver's body arrives at the surface of the expanded airbag from the normal position and it must receive the body softly. Either early or late expansion reduce the effect. Determination of the optimal timing for trigger the airbag is quite important. But it is a difficult job, due to the time delay in the bag filling with the gas after collision. This paper focuses on the issue of the airbag technology to how to find the optimal trigger timing and presents a new and straightforward algorithm to determine the timing by introducing the concept of the prediction. The algorithm first predicts how the driver's body will move in the future time for a time equivalent to the delay time and triggers the airbag by the predicted information so that it can compensate the delay by the airbag operation.

Accurate information of the absolute speed of a vehicle, when available, can be vital in simplifying the control laws of an anti-lock braking system (ABS) and auto-traction system (ATS). A current meter for measuring the speed of a vehicle is to multiply the measured wheel rotation rate to the wheel radius. The approach often includes abrupt unpredictable errors due to slip and skid of wheels and a biased error due to the steady state slip. These errors are sources of difficulty in the implementation of an ABS that is based on the absolute speed of the vehicle. This paper describes an accurate rule-based Kalman filtering technique for estimating the absolute speed of a vehicle. The enhanced accuracy is achieved by employing an additional accelerometer to complement the wheel speed-based speedometer. The accelerometer measures the acceleration of the vehicle in its forward direction and may be corrupted as well by high frequency noise.