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Original Articles Open Access
For four-wheel independently driven in-wheel motors electric vehicle, vehicle dynamic control systems such as direct yaw moment control (DYC) can be easily achieved. Accurate estimation of vehicle state variables and uncertain parameters can improve the robustness of vehicle dynamic control systemÃ¯Â¼ÂIn order to estimate tire-road friction better, the process mathematical model(m = Ks ) was built on the basis of the proportional relations in the linear region of μ-s curve and then identified parameter K by using Recursive Least Square algorithm (RLS). The rotational dynamics of the wheel model has been taken here to characterize the tire force. The paper designed parameter K identification algorithm and computed the input and output value of the proposed process mathematical model by the application of Matlab/Simulink software and acquired real-time data by means of AMESim. The results of simulation proved the feasibility of the proposed tire-road friction identification theory better.
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Author(s): Feng Xiao Chuanxue Song and Shaokun Li
Tire-road friction estimation, Process mathematical model, RLS algorithm, Parameter identification