차량거동 예측을 위한 센서 융합에 대한 연구

다국어 초록 (Multilingual Abstract)

This paper presents a robust estimation method of the vehicle dynamic behavior by using fusion sensors installed in suspension modules. The fusion sensor has been developed to measure 3-way accelerations and one way relative velocity between a sprung and an unsprung mass for semi-active suspension control. This paper proposes a new sensor fusion algorithm which can estimate the yaw rate and a lateral velocity of the vehicle at the center of gravity with strong robustness. The vehicle model with 6 degree of freedom was used for this work, and the normal forces between a tire and road were also estimated to calculate the accurate tire forces at each contact patch. A Kalman filter was designed to estimate the yaw rate and the lateral velocity and could also provide a covariance of the estimation error at each sensor module pair. A developed sensor fusion algorithm could provide robust estimated outputs of the vehicle dynamic parameters as well as sensor status. The performance of the proposed sensor fusion algorithm was evaluated via computer simulation study by utilizing commercial software of CarSim. The results show that the dynamic behavior of the vehicle can be estimated with satisfied accuracy even though in situation of sensor fail.