Road slope and vehicle mass estimation using Kalman filtering

Kalman filtering is used as a powerful method to attain 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 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 case yielded a simple filter structure with a ties-variant measurement equations 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 roles and acute by simulation and experimental field trials.