Road Slope and Vehicle Mass Estimation Using Kalman Filtering

SUMMARY Kalman filtering is used as a powerful method to obtain accurate estimation of vehicle mass and road slope. First the problem of estimating the slope when the vehicle mass is known is studied using two different sensor configurations. One where speed is measured and one where both speed and specific-force is measured. A filter design principle is derived guaranteeing the estimation error under a worst case situation (when assuming first order dynamics). The simultaneous estimation problem required an Extended Kalman Filter (EKF) design when measuring speed only whereas the additional specific force ease yielded a simple filter structure with a time-variant measurement equation. Additionally the filter needs present propulsion force which in our case is calculated form the engine speed and amount of fuel injected. When the vehicle uses the foundation brakes the estimates are frozen since varying friction properties makes the braking force unknown. Both sensor configurations are concluded to be robust and accurate by simulation and experimental field trials.