신경망을 이용한 자동차 절대속도 추정

Vehicle dynamics control systems are complex and non-linear, so they have difficulties in developing a controller for ABS(Anti-lock braking system) and TCS(Traction control system). Currently the fuzzy-logic technique to estimate the absolute vehicle speed is good results in normal conditions. But the estimation error in severe braking is discontented. In this paper, we estimate the absolute vehicle speed by using the wheel speed data from standard 50-tooth ABS wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and to estimate the absolute vehicle speed. Ten algorithms are experimentally verified to estimate the absolute vehicle speed and one of those is perfectly shown to estimate the vehicle speed with a 4% error during a braking maneuver.