A Novel Dual Nonlinear Observer for Vehicle System Roll Behavior with Lateral and Vertical Coupling 2019-01-0432
The study of vehicle coupling state estimation accuracy, especially in observer-based vehicle chassis control for improving road handling and ride comfort, is a challenging task for the vehicle industry under various driving conditions. Due to the high fatality rate caused by vehicle rollover, how to precisely and effectively acquire vehicle roll state become a hot topic in both academia and industry. Uncertainty is unavoidable for the vehicle system, e.g., varying sprung mass, a moment of inertia and position of the center of gravity. To deal with the above issues, a novel dual observer approach, which combines Unscented Kalman Filter (UKF) and Takagi-Sugeno (T-S), is proposed in this paper. A full-car nonlinear model is first established to describe vehicle lateral and vertical coupling roll behavior under various steering wheel input and road excitation. Considering the variation of vehicle sprung mass in the movement process, a UKF approach is adopted to identify the sprung mass of the vehicle system in real time. Then, combine the identification sprung mass via UKF observer and nonlinear coupling dynamics of tire lateral force, modified T-S model-based observer is developed to estimate the vehicle coupling roll state. The stability conditions for proposed T-S observer are deduced using linear matrix inequalities (LMI). Finally, using a high-fidelity CarSim® software platform, the proposed dual observer approach is verified through J-turn test, and simulations show that more accurate are obtained by comparing with the traditional T-S approach. The research achievements develop a reasonable algorithm to apply to the vehicle chassis control system.