| In recent years,Vehicle active safety system have drawn more and more attentions.And motion and control of vehicle highly depends on the forces between tire and ground,which is limited to tire road friction coefficient,and the real-time and accurate information of tire road friction plays an improve role for active safety and control systems.However,precise measurement of tire road friction coefficient is difficult to achieve without expensive and complex equipment.At the same time,in order to meet the requirements of vehicle control system,the algorithm must be real-time and reliability.Therefore,this paper proposes a method to estimate the tire road friction coefficient based on steering torque from electric power steering system(EPS),the method combined square root unscented kalman filter(SRUKF)and hybrid estimator to estimate the tire road friction at the same time,and mean square error weighted(MSE)fusion is used to optimize the results.Finally,both numerical simulation in Carsim/Simulink and actual off-vehicle tests in winter are provided to demonstrate the efficiency of the proposed algorithm.This article is organized as follows:(1)the four wheels vehicle model is proposed to represent the vehicle dynamics.The modified brush tire model is adopted to describe the nonlinear tire force and SAT.Moreover,an EPS model is used to describe the relationship among the steering wheel torque,the current following through assistant motor and the self-aligning torque(SAT),more sensitive to tire slip angle and provides faster estimation.(2)A method combined SRUKF and nonlinear observer based on steering torque is used to estimate the tire road friction coefficient in this paper,which is described in detail in Chapter Three and Chapter Four.And the result is optimized by MSE fusion.(3)The proposed method is verified by simulation tests in Carsim/Simulink and experimental vehicle tests on snow-packed ground in this paper.Which proved that estimation of the tire tire-road friction based on steering torque information is real-time and accurate. |