State Estimation Algorithm for Distributed Electric Drive Mining Vehicle Drive Algorithm

Distributed vehicles have stronger dynamic performance than ordinary vehicles, which also means that more accurate driving algorithm is needed, and to improve the accuracy of driving algorithm, accurate body parameters need to be obtained. The special operating environment (loading, transportation and unloading) of mine car causes the change of vehicle state (mass, road slope). In view of this situation, this paper proposes a joint estimation algorithm of Recursive Least Square (RLS) and Extended Kalman Filtering (EKF). Firstly, the vehicle longitudinal dynamic model with the conversion coefficient of rotating mass is established. Then, the sensor data is obtained by Carsim, and the mass estimation value is calculated based on RLS estimation algorithm. Then, the value is brought into EKF to estimate the road slope. The effectiveness of the joint estimation algorithm is verified by Carsim-Simulink joint simulation.