Real-time and accurate estimation of road slope for intelligent speed planning system of commercial vehicle
In the intelligent speed planning system, real-time estimation of road slope is the key to calculate slope resistance and realize the vehicles’ active safety control. However,if the road slope is measured by the sensor while the commercial vehicle is driving, the vibration of the vehicle body will affect its measurement accuracy. Therefore, the relevant algorithm is used to estimate the real-time slope of the road when the commercial vehicle is driving. At present, many domestic and foreign scholars have analyzed and tested the estimation of road slope by the least square method or kalman filter algorithm. Although the two methods both can achieve the estimation, the real-time performance and accuracy still need to be improved. In this paper, for traditional fuel commercial vehicle, the kalman filter algorithm based on the kinematics and the extended kalman filter algorithm based on the longitudinal dynamics are respectively used to estimate the road slope.