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.
F2012-E15-013
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bewersdorff S (2007) Simulation und Bewertung von Fahrdynamikeigenschaften im Grenzbereich. ATZ, Juni 2007
Bevly DM (2010) GNSS for vehicle control. Artech House, Boston
Beiker S (2006) GPS augmented vehicle dynamics control. SAE International, Warrendale
Ryu J (2004) State and parameter estimation for vehicle dynamics control using GPS. Dissertation, Stanford University
Schmidt D (2010) Fehleranalyse und Datenfusion von Satellitennavigations- und Fahrdynamik-sensorsignalen, Bd. 719, Düsseldorf: VDI-Verlag
Wendel J (2007) Integrierte navigationssysteme. Oldenbourg, München
Septentrio. PolaRX@ Datenblatt 2009
Bauer M (2011) Bestimmung der Übergrundgeschwindigkeit aus Fahrdynamiksensoren und Satelliten-Navigationsdaten. AUTOREG, Baden–Baden
Bauer M (2012) Estimation of vehicle dynamic states using driving dynamics sensors and GPS data to evaluate driving control functions. Chassis Tech, München
Isermann R (2006) Hrsg. Fahrdynamik-Regelung. Wiesbaden. Friedr. Vieweg & Sohn Verlag | GWV Fachverlage GmbH Wiesbaden
Isermann R (ed) (2011) Identification of dynamic system. Springer, Berlin
Mitschke M (ed) (2004) Dynamik der Kraftfahrzeuge. Springer, Berlin
Kiencke U (2005) Automotive control systems. Springer, New York
Schorn M (2007) Quer- und Längsregelung eines Personenkraftwagens für ein Fahrer-assistenzsystem zur Unfallvermeidung. Bd. 651, VDI, Düsseldorf
Wesemeier D (2012) Modellbasierte Methoden zur Schätzung nicht messbarer Grössen der Fahrzeugquerdynamik und des Reifenluftdrucks. VDI, Düsseldorf
Germann S (1997) Modellbildung und modellgestützte Regelung der Fahrzeuglängsdynamik. VDI, Düsseldorf
Börner M (2004) Adaptive Querdynamikmodelle für Personenkraftfahrzeuge—Fahrzustands-erkennung und Sensorfehlertoleranz. VDI, Düsseldorf
Schmitt K (2009) Vehicle state estimation in curved road coordinates for a driver assistance system for overtaking situations. IAVSD, Stockholm
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bauer, M., Ackermann, C., Isermann, R. (2013). Integrated State Estimation with Driving Dynamic Sensors and GPS Data to Evaluate Driving Dynamics Control Functions. In: Proceedings of the FISITA 2012 World Automotive Congress. Lecture Notes in Electrical Engineering, vol 196. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33738-3_73
Download citation
DOI: https://doi.org/10.1007/978-3-642-33738-3_73
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33737-6
Online ISBN: 978-3-642-33738-3
eBook Packages: EngineeringEngineering (R0)