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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/4786

Title: The identifying extended Kalman filter: parametric system identification of a vehicle handling model
Authors: Best, Matt C.
Newton, Andrew P.
Tuplin, S.
Keywords: Vehicle handling dynamics
Kalman filter
System identification
Vehicle parameter
Issue Date: 2007
Publisher: Professional Engineering Publishing / © IMECHE
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.
Abstract: 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.
Description: 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
Version: Published
DOI: 10.1243/14644193JMBD68
URI: https://dspace.lboro.ac.uk/2134/4786
ISSN: 1464-4193
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)

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