Online Boot Load Estimation Using Barometer and GNSS

Sammanfattning

Indirect tire pressure monitoring for the car industry is partially based on wheel radius estimation. When the tire pressure drops the wheel radius decreases. A problem occurs when the car is heavily loaded. The increased load compresses the tires and decreases the wheel radius similar to a pressure drop. This can lead to false alarms in the tire pressure monitoring system. Estimating load is thus an important robustness aspect for the tire pressure monitoring system to work. The load estimator presented in this thesis is, similar to earlier load estimators, based on measuring the vehicle pitch angle, which increases with boot load but also the road grade. Earlier load estimators rely on torque measurements to estimate the road grade, which are sensitive to rolling and air drag resistance changes. In this thesis, multiple sensor configurations are tested to estimate road grade more robust, including GNSS altitude, barometer and GNSS position with altitude database. Using a sensor fusion framework to combine GNSS altitude and barometer information enables a robust road grade compensation and significantly improves the load estimation under hilly driving conditions.