Design of a Robust Plausibility Check for an Adaptive Vehicle Observer in an Electric Vehicle
With the increasing number and complexity of Advanced Driver Assistance Systems (ADAS) and rising control facility by individual controllable drives in electric vehicles (EV) the reliability of sensor signals becomes more and more important in nowadays vehicles. In order to enhance the safety, the estimation of vehicle states and parameters gets more relevant. In most state of the art functions a vehicle observer secures the correctness of the delivered states. As the performance of observers depends on their input signals a novel plausibility check is implemented. In this paper the checked signals serve the designed adaptive vehicle observer, based on Extended Kalman filtering technique, as input signals. Thus the integrated vehicle functions can control the electric actuators with more precision in order to improve the driving performance and a minimization of energy consumption by an optimal use of the available road traction. The complete system, existing of plausibility check and observer is validated by simulation and will be implemented in an electric vehicle within the EU funded project eFuture.
Keywordssensor plausibility vehicle state observation parameter estimation Extended Kalman filter vehicle dynamics electric vehicle
Unable to display preview. Download preview PDF.