This paper demonstrates the use of an extended Kalman filter (KF) as a virtual sensor for non-measurable vehicle states and unknown vehicle parameters. The purpose of obtaining these values is to make them available within the control algorithms of the various automotive stability systems. Based on an extensive four-wheel vehicle model, an estimator is implemented on data from a test vehicle. Using available reference data, the suitability of the extended KF technique as a virtual sensor is demonstrated.
Abe, M., Kato, A., Suzuki, K., Kano, Y., Furukawa, Y. and Shibahata, Y.1998: Estimation of vehicle side-slip angle for DYC by using on-board-tire-model. Proceedings of the 4th International SymposiUm on Advanced Vehicle Control (AVEC)1998, Nagona, 437—42.
2.
Albertos, P. and Goodwin, G.C.2002: Virtual sensors for control applications. AnnUal Reviews in Control26, 101—12.
Blundell, M.V. and Harty, D.2004: The mUlti-body systems analysis approach to vehicle dynamics . Elsevier Butterworth-Heinemann.
5.
Chee, W.2001: Measuring yaw rate with accelerometers. FUtUre Transportation Technology Conference, Costa Mesa, CA. SAE technical paper series 2001-01-2535.
6.
Fiala, E.1954: Seitenkräfte am rollenden Luftreifen. VDI Zeitschrift96, 973—79.
7.
Gobbi, M. and Mastinu, G.2004: Wheels with integrated sensors for measuring tyre forces and moments. Proceedings of the 7th International SymposiUm on Advanced Vehicle Control AVEC'04, HAN University , Arnhem, 23—27 August, 519—24.
8.
Gustafsson, F., Drevö, M., Forssell, U., Löfgren, M., Persson, N. and Quicklund, H.2001: Virtual sensors of tire pressure and road friction. SAE 2001 World Congress, Detroit, MI. SAE Society of Automotive Engineers. SAE technical paper series 2001-01-0796.
9.
Haykin, S., editor. 2001: Kalman filtering and neural networks. John Wiley & Sons.
10.
Hirschberg, W., Rill, G. and Weinfurter, H.2002: User-appropriate tyre-modelling for vehicle dynamics in standard and limit situations. Vehicle System Dynamics38, 103—25.
Kalman, R.E.1960: A new approach to linear filtering and prediction problems . Transactions of the ASME—JoUrnal of Basic Engineering82 (Series D), 35—45.
13.
Kiencke, U. and Nielsen, L.2000: AUtomotive control systems. Springer .
14.
Krantz, W., Neubeck, J. and Wiedemann, J.2002: Estimation of side slip angle using measured tire forces . SAE 2002 World Congress, Detroit, MI. SAE Society of Automotive Engineers. SAE technical paper series 2002-01-0969.
15.
Milliken, W.F. and Milliken, D.L.1995: Race car vehicle dynamics. SAESociety of Automotive Engineers.
16.
MSC Software Corporation.2003: Adams. http://www.adams.com (Accessed March 2003).
17.
Ots.2004: RT3000 User manual . http://www.ots.ndirect.co.uk. OxfordTechnical Solutions Limited (Accessed June 2005).
18.
Pacejka, H.B.2002: Tyre and vehicle dynamics. Butterworth-Heinemann .
19.
Smith, D.E. and Starkey, J.M.1995: Effects of model complexity on the performance of automated vehicle steering controllers: model development, validation and comparison. VehicleSystem Dynamics24, 163—81.
20.
Stéphant, J., Charara, A. and Meizel, D.2004: Virtual sensor: application to vehicle sideslip angle and transversal forces. IEEE Transaction on IndUstrial Electronics51, 278—89.
21.
Stöcker, H., editor. 1998: TaschenbUch der Physik, 3rd edition. Verlag Harri Deutsch.
22.
Tesis.2003: ve-DYNA. http://www.tesis.de. Gesellschaft für Technische Simulation und Software mbH (Accessed October 2003).
23.
Trächtler, A.2004: Integrated vehicle dynamics control using active brake, steering and suspension systems. International JoUrnal of Vehicle Design36, 1—12.
24.
Tseng, H.E.2002: A sliding mode lateral velocity observer. Proceedings of the 6th International SymposiUm on Advanced Vehicle Control (AVEC)2002, Hiroshima.
25.
Velardocchia, M. and Sorniotti, A.2004: A failsafe strategy for a vehicle dynamics control (VDC) system. Proceedings SAE 2004 World Congress, Detroit, MI, 8—11 March. SAE Society of Automotive Engineers. SAE technical paper series 2004-01-0190.
26.
Venhovens, P.J.T. and Naab, K.1999: Vehicle dynamics estimation using Kalman filters. Vehicle System Dynamics32, 171—84.
27.
Visser, A., van der Wees, A.J. and Hertzberger, L.O.2000: Discrete event modelling methodology for intelligent transport systems. Proceedings of the World Congress on Intelligent Transport Systems, Torino.
28.
Wenzel, T.A.2005: State and parameter estimation for vehicle dynamic control. PhD thesis, Coventry University.
29.
Will, A.B. and Żak, S.H.1997: Modelling and control of an automated vehicle. VehicleSystem Dynamics27, 131—55.
30.
Wong, J.Y.2001: Theory of groUnd vehicles, third edition. John Wiley & Sons.
31.
Young, P.C.1974: Recursive approaches to time series analysis. The InstitUte of Mathematics and its Applications, BUlletin10, 209—24.