To address the issue of deviation in the estimation of vehicle mass and road gradient by applying the longitudinal dynamics model when there is a lateral component force in the driving process of vehicles, this paper proposes a coupled mass estimation model based on longitudinal-horizontal dynamics and an algorithm for slope estimation. By analyzing the effect of the acceleration phase on mass estimation, the mass estimation trigger condition is set and the recursive least squares method with forgetting factor is used to estimate the vehicle mass, and the kinematic Kalman filter is fused with the kinematic extended Kalman filter to jointly estimate the road slope. The algorithm is validated by Simulink-CarSim joint simulation and real vehicle test. The results show that the error of the mass estimation algorithm based on longitudinal-transverse dynamics is 0.82%, and the error of the fusion slope estimation algorithm is within 3%, which verifies that the algorithm has good accuracy and real-time performance.

Mass estimation  /  Slope estimation  /  Forgetting Factor Recursive Least Squares (FFRLS)  /  Kalman filter  /  Fused estimation