Velocity estimation in land vehicle applications - Sensor Fusion using GPS, IMU and Output-shaft

Sammanfattning: In this project an alternative velocity-signal for Scania’s heavy-duty vehicles was investigated. The current velocity estimation is based on wheel-encoders obtained from other control-units like ABS- and EBSsystems. Furthermore the wheel-encoders may have poor properties at both high and low velocites. Because the velocity is important for the automatic manual gear-switching sequence, Opticruise used in Scania transmission management system (TMS), an alternative velocity estimation based only on the internal signals in the TMS and GPS is desirable. In this project the proposed algorithm utilizes sensor-fusion of a GPS, the rotational-velocity from the Output-shaft and an inertial measurement unit (IMU). An external 6-axis IMU, consisting of accelerometers and gyroscopes, was implemented to investigate if a more complete sensor-configuration would have potential benefits compared to the reduced 2-axis IMU currently in the TMS. The sensor-fusion algorithms are based on two different state-observers: Sliding mode observer (SMO), and Extended Kalman filter(EKF). The two different sensor configurations had similar performance in good conditions. But the expanded sensor-configuration would outperformed the standard in critical-scenarios, where signals either becomes lost or bad. Other phenomenon like Coriolis-accelerations could be observed and compensated for with additional sensors, and in the process improve the velocity-estimation further. A method is also proposed to detect slippage in both the GPS or the Output-shaft, and compensate for a known constant delay. Resulting in a better velocity estimation compared to the current TMS velocity-estimation, based on tachometers from the wheels, during the scenarios considered in this project.