This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Vehicle Side Slip and Roll Angle Estimation
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 05, 2016 by SAE International in United States
Annotation ability available
Vehicle dynamics estimation has been the subject of study for some years now. If on-board vehicle control systems can be provided with information such as side slip angle, lateral force etc. then stability of the vehicle can be improved. To estimate these dynamic variables different observers have been used e.g., sliding mode, fuzzy logic, neural networks etc. In this article the authors propose an extended Kalman filter to estimate vehicle side slip angle. Roll angle is estimated using vertical loads as input. First, a linear Kalman filter is used to filter out the vertical forces and estimate roll angle. This information is then used to estimate the vehicle side slip angle. To take into account the nonlinearities concerning lateral vehicle dynamics, Pacejka magic formula is used to model lateral forces. Estimated results are then compared with simulations, showing good accuracy.
CitationSyed, U. and Vigliani, A., "Vehicle Side Slip and Roll Angle Estimation," SAE Technical Paper 2016-01-1654, 2016, https://doi.org/10.4271/2016-01-1654.
- Ryu J. and Gedes J.C. Estimation of Vehicle Roll and Road Bank Angle American Control Conference Boston, MA 2004
- Hodgson G. and Best M.C. A Parameter Indentifying a Kalman Filter Observer For Vehicle Handling Dynamics Proceedings of the Instituion of Mechanical Engineers, Part D: Journal of Automobile Engineering 2006 10.1243/09544070D18304
- Gadola M. , Chindamo D. , Romano M. , and Padula F. Development and validation of a Kalman filter-based model for vehicle side slip angle estimation Vehicle System Dynamics. International Journal of Vehicle Mechanics and Mobility 2013 10.1080/00423114.2013.859281
- Hac A. and Bedner E. Robustness of Side Slip Estimation and Control Algorithms for Vehicle Chasis Control Proceedings of the 20th International Technical Conference on the Enhanced Safety of Vehicles 2007
- Stèphant J. , Charara A. , and Meizel D. Vehicle Side Slip Angle Observers Europeon Control Conference Cambridge, UK 2003
- Chen B.C. and Hsieh F.C. SideSlip angle estimation using estended Kalman filter Vehicle system Dynamics: International Journal of Vehicle Mechanics and Mobility 46 s1 2008 353 364
- Anotov S. , Fehn A. , and Kugi A. Unscented Kalman Filter for Vehicle State Estimation Vehicle system Dynamics: International Journal of Vehicle Mechanics and Mobility 49 9 2011 1497 1520
- Charara A. , Doumiati M. , Victorino A. , and Lechner D. Vehicle Dynamics Estimation Using Kalman Filtering: Experimental Verification Dubuisson Bernard John Wiley & Sons, Inc 2013
- Brown R.G. and Hwang P.Y.C Introduction to Random Signals and Applied Kalman Filtering 4 th John Wiley & Sons, Inc 2012
- Simon D. Optimal State Estimation Kalman, H∞ and Non Linear Approaches John Wiley & Sons, Inc 2006
- Berntorp K. Derivation of a Six Degrees-of-Freedom Ground-Vehicle Model for Automotive Applications Technical Report Lund University 2013 http://www.control.lth.se/publications/
- Pacejka H.B. Tyre and Vehicle Dynamics 2006 980-0-7506-6918-4
- Capra D. et al. An ABS control logic based on wheel force measurement Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility 2012 50 12 1779 1796
- Milliken William F. and Milliken Douglas L. Race Car Vehicle Dynamics 1995 1-56091-526-9
- Lechner . D. Embedded laboratory for vehicle dynamic measurements Proceedings of the 9th International Symposium on Advanced Vehicle Control (AVEC) Kobe, Japan 2008 229 234