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The identifying extended Kalman filter: parametric system identification of a vehicle handling model

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journal contribution
posted on 03.06.2009, 16:26 by Matt BestMatt Best, Andrew P. Newton, Simon TuplinSimon Tuplin
This article considers a novel method for estimating parameters in a vehicle-handling dynamic model using a recursive filter. The well-known extended Kalman filter - which is widely used for real-time state estimation of vehicle dynamics - is used here in an unorthodox fashion; a model is prescribed for the sensors alone, and the state vector is replaced by a set of unknown model parameters. With the aid of two simple tuning parameters, the system self-regulates its estimates of parameter and sensor errors, and hence smoothly identifies optimal parameter choices. The method makes one contentious assumption that vehicle lateral velocity (or body sideslip angle) is available as a measurement, along with the more conventionally available yaw velocity state. However, the article demonstrates that by using the new generation of combined GPS/inertial body motion measurement systems, a suitable lateral velocity signal is indeed measurable. The system identification is thus demonstrated in simulation, and also proved by successful parametrization of a model, using test vehicle data. The identifying extended Kalman filter has applications in model validation - for example, acting as a reference between vehicle behaviour and higher-order multi-body models - and it could also be operated in a real-time capacity to adapt parameters in model-based vehicle control applications.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Citation

BEST, M.C., NEWTON, A.P. and TUPLIN, S., 2007. The identifying extended Kalman filter: parametric system identification of a vehicle handling model. Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics, 221(1), pp. 87-98.

Publisher

Professional Engineering Publishing / © IMECHE

Version

VoR (Version of Record)

Publication date

2007

Notes

This is an article from the journal, Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics [© IMechE ]. It is also available at: http://dx.doi.org/10.1243/14644193JMBD68

ISSN

1464-4193

Language

en