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A parameter identifying a Kalman filter observer for vehicle handling dynamics

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journal contribution
posted on 2009-08-06, 14:11 authored by Graham Hodgson, Matt BestMatt Best
The paper presents a method for designing a non-linear (i.e. extended) Kalman filter that is also parameter adaptive and hence capable of online identification of its model. The filter model is deliberately simple in structure and low order, yet includes non-linear, load-varying tyre force calculations to ensure accuracy over a range of test conditions. Shape parameters within the (Pacejka) tyre model are adapted rapidly in real time, to maintain excellent state reconstruction accuracy, and provide valuable real-time lateral and vertical tyre force information. The filter is tested in both simulated and test vehicle environments and provides good results. The paper also provides an illustration of the importance of good Kalman filter design practice in terms of selection and tuning of the noise matrices, particularly in terms of the influence of model/sensor error cross-correlations.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Citation

HODGSON, G. and BEST, M.C., 2006. A parameter identifying a Kalman filter observer for vehicle handling dynamics. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 220 (8), pp. 1063-1072

Publisher

Professional Engineering Publishing / © IMechE

Version

  • VoR (Version of Record)

Publication date

2006

Notes

This article has been published in the journal, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering [© IMechE]. The definitive version is available at: http://journals.pepublishing.com/content/119783

ISSN

0954-4070

Language

  • en