Vehicle Handling Dynamics State Estimation Based on Strong Tracking Filter

Due to some key state parameters of vehicle handling stability control are difficult to measure directly, the state optimization estimation algorithm of multi-sensor linear combination based on Strong Tracking Filter (STF) was proposed. Four degrees of freedom vehicle nonlinear dynamics model including longitudinal, lateral and roll motion were established. With the estimator of multi-sensors information fusion and the STF theory, the vehicle handling dynamics states estimation were simulated and analyzed. The result shows that the STF offers higher performance potential. Not only does it solve the problems of the state estimation value deviating from the true system states due to the model uncertainty, but also can inhibit the filtering divergence effectively. The technology of state estimation with the STF has wide range of adaptive tracking capability. It provides a real-time, accurate and low cost soft-sensing technology for vehicle advance control.