Integrated optimal dynamics control of 4WD4WS electric ground vehicle with tire-road frictional coefficient estimation

• The control gain is obtained with an analytical solution of the Algebraic Riccati Equation.
• A Barrier Function is used to ensure all the tires work in the stable region.
• An analytic solution of allocation method is designed.
• A data fusion method is proposed to minimize the TRFC estimation error.

This paper presents an integrated optimal dynamics control of four-wheel driving and four-wheel steering (4WD4WS) electric ground vehicles via hierarchical control methodology. In the higher-level design, an LQR controller is proposed to obtain the integrated lateral force and yaw moment, according to their respective reference values. The lower-level controller is designed to ensure all the tires work in the stable region while realizing the tracking control of the vehicle dynamics. The tire-road friction coefficient is estimated through the integrated longitudinal force and lateral force, respectively, using a brush tire model. To reduce the estimation error, a novel data fusion function is employed to generate the final estimation value. Finally, the effectiveness of the proposed control and estimation strategies is validated via CarSim–Simulink joint simulation.