A new estimation approach of road friction coefficient and optimum wheel slip ratio for longitudinal and lateral vehicle dynamics control using active steering and braking

In this paper, an integrated control system of longitudinal, lateral and yaw vehicle dynamics is presented using active braking and active front steering (AFS) systems. The proposed active braking system based on sliding mode controller, includes two kinds of working modes of anti-locked brake and (ABS) and an electronic stability control (ESC) and a fuzzy controller has been used in the AFS system. Also, a nonlinear estimator utilising unscented Kalman filter is applied to estimate the vehicle dynamics variables. According to the estimated values and Dugoff tire model, the tire-road friction coefficient is calculated. Since the ABS performance for shortening the stopping distance is dependent on the optimum wheel slip ratio, an adaptive neuro-fuzzy inference system (ANFIS) is proposed to obtain the optimum value. The tire-road friction coefficient, longitudinal velocity and the vertical load of each wheel are considered as the ANFIS inputs. In the simulation part, first, the hard braking action in straight line on the roads with various friction coefficients during driving is investigated, which results in high precision of the estimator for the friction coefficient and optimum wheel slip ratio, and greatly reduced the distance and stopping time in comparison to the vehicle without estimator. Then, simulation of split-μ roads has been carried out which demonstrates the integrated control of ABS, ESC and AFS systems associated with the mentioned estimators can, in addition to improving the lateral and yaw stability, also decrease the stopping distance.