Nonlinear Joint Dynamic Estimator of Sideslip Angle and Tire-Road Peak Adhesion Coefficient Based on Improved Brush Tire Model

The sideslip angle and tire-road peak adhesion coefficient (TRPAC) are crucial parameters for intelligent active safety systems in automobiles. The accuracy and real-time estimation of these parameters significantly affect control effectiveness. And there is a strong coupling between the two parameters, which brings great challenges to the joint estimation. This paper proposes a nonlinear dynamic estimator that pre-estimates tire lateral force to achieve synchronous estimation of sideslip angle and TRPAC. Additionally, to cope with sudden changes in road adhesion condition, a TRPAC preliminary estimation optimization algorithm is introduced. Moreover, an adaptive gain adjustment algorithm for the sideslip angle estimator is implemented to address large lateral excitation conditions. Simulation results on various road surfaces and under various lateral excitation conditions demonstrate that the proposed joint estimator enables accurate and rapid estimation of sideslip angle and TRPAC.