Integrated observer approach using in-vehicle sensors and GPS for vehicle state estimation

This paper presents a new method for estimation of vehicle sideslip angle, which is a critical factor in some vehicle chassis control systems. Making use of easily available in-vehicle sensors and a standalone global positioning system (GPS), an integrated observer approach is developed, which includes a sensor offset compensator and two kinds of extended Kalman filters (EKFs) based on a bicycle model and a kinematic model, respectively. To properly combine the outputs of these EKFs, a weighting factor, a function of tire cornering stiffness and tire force, is designed. The observability of each EKF is checked by observability functions of nonlinear systems. As well as the sideslip angle, the longitudinal velocity, heading angle, and tire cornering stiffness are simultaneously estimated by the proposed algorithm. Finally, the performance of the entire system in various driving scenarios is verified using a test vehicle, and the superiority of the integrated observer is confirmed through a comparative study.