LFT-Based Identification of Lateral Vehicle Dynamics
This paper presents a novel estimation and identification approach for lateral vehicle dynamics. The algorithm leverages on a Linear Fraction Transform (LFT) reformulation of vehicle and tyre models, allowing for a simple and computationally efficient inclusion of complex and nonlinear dynamic models, like, for example, two-wheels, four-wheels or single-track as vehicle model, and Pacejka, brush or Fiala as tyre model. As a result, this technique can be easily adopted in the development of an online identification system, able to run on a standard embedded device, implementing a flexible identification procedure that can handle different driving conditions, up to the limits of handling, different vehicle modelling approaches, and different input measurements. Experimental results demonstrate the effectiveness of the proposal, either in a persistent excitation and in a non-persistent excitation scenario.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00189545
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Supplemental Notes:
- Copyright © 2022, IEEE.
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Authors:
- Bascetta, Luca
- Ferretti, Gianni
- Publication Date: 2022-2
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 1349-1362
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Serial:
- IEEE Transactions on Vehicular Technology
- Volume: 71
- Issue Number: 2
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 0018-9545
- Serial URL: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=25
Subject/Index Terms
- TRT Terms: Control; Estimating; Mathematical models; Motor vehicle dynamics; Tires
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01837094
- Record Type: Publication
- Files: TRIS
- Created Date: Feb 25 2022 8:58AM