A simple system composed of a single axis accelerometer or inclinometer, an inexpensive solid-state rate gyro and a micro-controller is explored as a predictive rollover sensor. Inclinometers or accelerometers alone cannot predict rollover due to the effects of lateral forces during turns. These forces cause such systems to over estimate the roll angle of the vehicle by a wide margin, resulting in false alarms and rendering them useless. Inexpensive solid-state rate gyros are likewise not up to the task because of large variations in the bias both under temperature and parametric variations. Using both of these sensors along with proprietary algorithms similar to those developed for the Archangel Air Data Attitude Heading Reference System (ADAHRS) for aviation, a successful predictive system can be constructed.
Using Fuzzy Logic Adaptive Signal Processing (FLASP) algorithms, the drift is removed from the gyro in real time without extensive calibrations or modeling and the effects of lateral forces are removed from the accelerometer/inclinometer. This results in a system possessing redundant and, therefore, highly reliable information concerning both the roll rate and angle of the vehicle. The efficacy of this method is clearly demonstrated by the flight proven Archangel ADAHRS used in aircraft.
In the system, the combination of the roll rate and angle are used to predict an impending rollover up to 500 ms in advance1. This information used in conjunction with an active yaw control system could be used to prevent the rollover. Failing prevention, the information could be used to deploy airbags to minimize passenger danger.