Abstract
With increasing number of road accidents, India is witnessing significant developments in the area of active safety systems for Heavy Commercial Road Vehicles (HCRVs). One of the challenges faced in developing such systems is the knowledge of wheel slip ratio. This paper proposes a nonlinear estimation technique, namely theUnscented Kalman Filter (UKF) for estimating wheel slip in HCRVs. This algorithm was evaluated with vehicle data obtained from a Hardware in Loop (HiL) experimental platform running IPG TruckMaker®, a commercial vehicle simulation software, for different manoeuvres and driving scenarios.It was observed that there was a close agreement between the vehicle speed obtained from TruckMaker® simulation and the one obtained via estimation for a wide range of test cases. In addition to this, theestimated wheel slip was able to capture the onset of wheel locking. This algorithm was tested for robustness in the presence of sensor noise which produced acceptable results. Then, this workproposes an approach for accelerometer offset correction required during on-vehicle implementation Thus, this work presents a nonlinear technique for wheel slip estimation and also addresseestwo major practical problems of sensor noise and accelerometer offset for real-time application.
Keywords: heavy vehicles, active safety, slipestimation, tyre slip, unscented Kalman filter