State cooperative estimation for four-wheel-independent-driving electric vehicle based on a novel robust modular observer

Abstract

To ensure the reliable operation of advanced driver assistance systems (ADAS) for vehicles, accurate and real-time vehicle state acquisition is essential. To this end, in this paper, based on the vehicle seven-degree-of-freedom model and Dugoff’s tire model, a novel robust modular observer is presented to cooperatively estimate states in a four-wheel-independent-driving electric vehicle, such as wheel angular velocity, vehicle velocity, TRFC, and tire stiffness, thereby enhancing estimation precision. First, to attenuate sensor noise disturbances, a wheel angular velocity observer is designed using the Lyapunov stability theorem. Next, a nonlinear observer is presented to estimate the lateral velocity, longitudinal velocity, and TRFC. Meanwhile, its robustness to the uncertain parameters of the vehicle is analyzed based on the Lyapunov stability theorem. Then, the longitudinal stiffness and cornering stiffness of the tire are estimated based on the recursive least squares method, in which a forgetting factor is introduced to improve the convergence performance of the observer. Finally, hardware-in-the-loop experiments demonstrate the excellent estimated performance of the presented observer.