Online road slope estimation for vehicles based on unscented Kalman filtering

Road slope information is necessary information for many kinds of vehicle control systems, and its accurate acquisition is one of the key factors to improve the motion control of intelligent vehicles, so the online estimation of road slope information has important research significance. In order to solve the road slope estimation problem, it is proposed to estimate the road slope by using the unscented Kalman filter algorithm, which only estimates the road slope based on the on-board CAN bus data without the need of external sensors. Simulation experiments are carried out using the MATLAB/Simulink-Carsim platform, and the comparative analysis of the estimation results of this research algorithm and the extended Kalman filter algorithm shows that the algorithm of this research can better filter and estimate the road slope effectively, and gradually converge and approximate the measured value in a short period of time, so that it can effectively detect the road slope information of the vehicle in motion.