Vehicle sideslip angle estimation using Kalman filters: Modelling and validation

PIERALICE, C, LENZO, Basilio, BUCCHI, F and GABICCINI, M (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). Springer, 114-122.

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Official URL: https://www.springer.com/gp/book/9783030033194
Link to published version:: https://doi.org/10.1007/978-3-030-03320-0_12
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    Abstract

    © Springer Nature Switzerland AG 2019 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: Series ISSN: 2211-0984
    Identification Number: https://doi.org/10.1007/978-3-030-03320-0_12
    Page Range: 114-122
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 08 Nov 2019 14:10
    Last Modified: 08 Nov 2019 14:15
    URI: http://shura.shu.ac.uk/id/eprint/24914

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