Identification of Vehicle Dynamics Model and Lever-Arm for Arbitrarily Mounted Motion Sensor

Abstract

This paper presents a novel identification method for vehicle dynamics model and sensor lever-arm using the motion measurements from sensors mounted on arbitrary positions. Since known methods for vehicle model parameter identification and sensor lever-arm estimation have been cross-referencing the results from each other, a simple conjugation of two methods cannot solve the identification of model parameter and lever-arm concurrently. A modified single track model with normalized tire stiffness is formulated to decouple the lever-arm effect from the vehicle's dynamics states. The identification scheme is conducted through an unscented Kalman filter by fusing the modified model with inertial and velocity measurements from the sensor. We demonstrate the efficacy of identification performance of the proposed method in simulations and real-vehicle experiments. The identified model accomplished the accuracy within 5% error for geometrical parameters and 10% error for tire stiffness over various experimental conditions and confirms the feasibility of utilizing motion estimation devices in vehicle dynamics and vice versa.