Joint estimation of vehicle mass and road slope considering lateral motion
To reduce the influence of the lateral motion on the vehicle mass and the estimation accuracy of the road gradient,an estimation algorithm considering the lateral motion is proposed,the vehicle dynamics model is corrected by the acceleration,and the forgetting factor is used to enhance the new data to adapt to the minimum value of the time-varying characteristics of the vehicle system.The vehicle mass is estimated by the quadratic algorithm,and the mass estimation result is input into the road gradient estimation in real time;in addition,two gradient estimation models of vehicle kinematics and dynamics are established,and the acceleration correction term is added to the model,and the strong tracking filtering algorithm is designed respectively.A time-varying interactive multi-model fusion algorithm is proposed to estimate the road slope for the two models.The estimated road slope is obtained according to the weight coefficients of the two slope estimation models and the transition probability between the models.The proposed algorithm was tested and evaluated on a real vehicle in the Nong'an Automobile Proving Ground of the Technology Center of China FAW Co.,Ltd.Compared with the fusion estimation algorithm that did not consider the lateral direction,it improves the estimation accuracy of road slope when the vehicle moves laterally.
vehicle engineeringmass and road slope estimationtime-varying interacting multiple modelfusionlateral movementreal vehicle test
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