Road slope angle; Vehicle mass; Longitudinal dynamics; In-vehicle network sensor; Estimation; 도로 경사각; 차량 질량; 종 방향 동역학; 차량 내부 정보 센서; 추정
2015 KSAE 부문 종합학술대회, 2015.5, 398-400
The information of road slope angle and vehicle mass is becoming more important in the intelligent vehicle system. Moreover, the mass of commercial vehicle can be changed easily when many passengers get on or get off. Measuring the vehicle mass and the road slope angle is not impossible, but it is costly since additional sensors have to be mounted. while several researches proposed estimation method for each vehicle mass and road slope angle. In this paper, the estimation of vehicle mass and road slope for commercial vehicle is proposed to compensate for driving load. the estimation method is designed based on the longitudinal dynamics. the vehicle mass and the road slope angle are coupled in the longitudinal dynamics. Therefore, the proposed algorithm is designed by using the extended Kalman filter algorithm. The proposed algorithm was evaluated by using MATLAB/simulink and TruckSim.