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Real-time estimation of the optimal longitudinal slip ratio for attaining the maximum traction force

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00372597" target="_blank" >RIV/68407700:21230/24:00372597 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1016/j.conengprac.2024.105876" target="_blank" >https://doi.org/10.1016/j.conengprac.2024.105876</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.conengprac.2024.105876" target="_blank" >10.1016/j.conengprac.2024.105876</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Real-time estimation of the optimal longitudinal slip ratio for attaining the maximum traction force

  • Original language description

    Advanced driver assistant systems in vehicles, such as anti-lock brake system, electronic stability program, and traction control, heavily rely on the traction force of the wheels, which is determined by the wheels’ longitudinal slip ratio. A common method used to describe this dependency is the well-known Pacejka (magic) formula. The Pacejka (magic) formula suggests the existence of a unique optimal slip ratio, denoted as lambda_opt, for which the maximum traction force is achieved. Although the lambda_opt value slightly varies with changes in the tire-to-road interface, most studies tend to neglect the variation of lambda_opt due to its relatively low impact on the introduced error. Instead, most studies focus on estimating the maximum friction coefficient mu_max . In this paper, we address this oversimplification and propose an estimation method for lambda_opt. This paper introduces two novel approaches for real-time estimation of the slip ratio lambda_opt based on wheel dynamics. Both approaches were derived using a nonlinear twin-track model implemented in MATLAB & Simulink. The first approach uses recursive least squares, whereas the second approach employs the Unscented Kalman filter algorithm. In addition, a traction force estimator is presented because both estimators rely on either a measurement or an estimation of the traction force. To validate the performance of the proposed estimators, a high-fidelity twin-track vehicle model was initially employed. Finally, real-world experiments are presented in which the proposed algorithms are validated using an RC subscale platform.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Control Engineering Practice

  • ISSN

    0967-0661

  • e-ISSN

    1873-6939

  • Volume of the periodical

    145

  • Issue of the periodical within the volume

    April

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    12

  • Pages from-to

  • UT code for WoS article

    001174860400001

  • EID of the result in the Scopus database

    2-s2.0-85185530744