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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Integrated State Estimation with Driving Dynamic Sensors and GPS Data to Evaluate Driving Dynamics Control Functions
verfasst von : Markus Bauer, Carlo Ackermann, Rolf Isermann
Erschienen in: Proceedings of the FISITA 2012 World Automotive Congress
Verlag: Springer Berlin Heidelberg
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Abstract
The aim of this research project is to investigate the use of GPS data for test drives. Based on data of a multi-antenna GPS system and vehicle dynamic sensors, an information platform is performed. This platform includes the merged sensor signals and an estimation of vehicle states that are not measurable. In a state estimator the lateral dynamic model is combined with a navigation model. The state estimation is accomplished by coupling the signals in an extended Kalman Filter (EKF) which is a variant of the Kalman Filter (KF) for nonlinear dynamic systems. The double-track approach with a linear tire force model is used to describe the lateral vehicle dynamics. Pitch and roll movements are analyzed separately from each other. The unknown or time-variant vehicle parameters are estimated online by recursive estimation methods. In addition to the presentation of the developed methods, results from test drives with the research vehicle (BMW 540i) at the testing area of the Technische Universität Darmstadt are presented.