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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název periodika

Control Engineering Practice

ISSN

0967-0661

e-ISSN

1873-6939

Svazek periodika

145

Číslo periodika v rámci svazku

April

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

12

Strana od-do

—

Kód UT WoS článku

001174860400001

EID výsledku v databázi Scopus

2-s2.0-85185530744