Joint Wheel-Slip and Vehicle-Motion Estimation Based on Inertial, GPS, and Wheel-Speed Sensors

摘要

Joint wheel-slip and vehicle-motion estimation is considered, based on measurements from wheel encoders, an inertial measurement unit, and a global positioning system (GPS). The proposed strategy effectively employs the Rao–Blackwellized particle-filtering framework using a kinematic model. Key variables in active safety systems, such as longitudinal velocity, roll angle, and wheel slip for all four wheels, are estimated. The results from a demanding field test show the efficacy of the approach; the wheel slip and velocity can be estimated with an absolute accuracy of 0.018 and 0.25 m/s, respectively, measured as time-averaged root-mean-square errors, in periods of simultaneous aggressive braking and cornering. The corresponding differences between best case and worst case performances are 0.005 and 0.1 m/s. The results from a double lane-change maneuver indicate reliable velocity and slip estimation in periods of GPS outage.