Vehicle sideslip angle estimation using Kalman filters: modelling and validation

PIERALICE, Cristiano, LENZO, Basilio, BUCCHI, Francesco and GABICCINI, Marco (2018). Vehicle sideslip angle estimation using Kalman filters: modelling and validation. In: CARBONE, Giuseppe and GASPARETTO, Alessandro, (eds.) Advances in Italian Mechanism Science: Proceedings of the Second International Conference of IFToMM ITALY. Mechanisms and Machine Science, 68 (68). Netherlands, Springer, 114-122.

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Official URL: https://www.springer.com/us/book/9783030033194
Link to published version:: https://doi.org/10.1007/978-3-030-03320-0
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    Abstract

    The knowledge of the vehicle sideslip angle provides useful information about the state of the vehicle and it is often considered to increase the performance of the car as well as to develop safety systems, especially in the vehicle equipped with Torque Vectoring control systems. This paper describes two methods, based on the use of Kalman filters, to estimate the vehicle sideslip angle and the tire forces of a vehicle starting from the longitudinal and yaw velocity data. In particular, these data refer to on-track testing of a Range Rover Evoque performing ramp steer maneuvers at constant speed. The results of the sideslip estimation method are compared with the actual vehicle sideslip measured by a Datron sensor and are also used to estimate the tire lateral forces.

    Item Type: Book Section
    Additional Information: ISSN 2211-0984 e-ISSN 2211-0992
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Materials and Engineering Research Institute > Centre for Automation and Robotics Research > Systems Modelling and Integration Group
    Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Engineering and Mathematics
    Identification Number: https://doi.org/10.1007/978-3-030-03320-0
    Page Range: 114-122
    Depositing User: Basilio Lenzo
    Date Deposited: 09 Nov 2018 12:17
    Last Modified: 18 Mar 2021 03:22
    URI: http://shura.shu.ac.uk/id/eprint/22810

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