Vehicle sideslip estimation for four-wheel-steering vehicles using a particle filter

The availability of the most relevant vehicle states is crucial for the development of advanced vehicle control systems and driver assistance systems. Specifically the vehicle sideslip angle plays a key role, yet this state is unpractical to measure and still not straightforward to estimate. This paper investigates a particle filter approach to estimate the chassis sideslip angle of road vehicles. The filter relies on a physical model of the vehicle and on measurements available from cheap and widespread sensors including inertial measurement unit and steering wheel angle sensor(s). The approach is validated using experimental data collected with the research platform RoboMobil (RoMo), a by-wire electric vehicle with wheel-individual traction and steering actuators. Results show that the performance of the proposed particle filter is satisfactory, and indicate directions for further improvement.