Improved road grade estimation using sensor fusion

A method for estimation of the road grade based on standard mounted sensors in a heavy duty vehicle is presented. The method combines information from a barometer and a GPS with velocity and torque measurements of conventional type. The sensor information is adaptively integrated using extended Kalman filtering. This provides a systematic method for dealing with varying uncertainty in the sensors. The method can handle periods of missing or unreliable data from one or several sensors, e.g., occasions when the satellite coverage is low or when the brakes are applied.