Road Grades And Tire Forces Estimation Using Two-Stage Extended Kalman Filter In A Delayed Interconnected Cascade Structure

Intelligent vehicles sense their dynamics and the environment to make proper decisions. Some of this information are hard to be measured or need expensive sensors. This paper addresses the estimation of road grade angles, along with tire-ground interaction forces, in a delayed interconnected cascade observer structure. A new approach using a Two-Stage Extended Kalman Filter is proposed, allowing a robust simultaneous estimation of the slow and fast dynamics variables. Experimental data is used to validate the estimator.