A new friction condition identification approach for wheel-rail interface

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25510%2F16%3A39901458" target="_blank" >RIV/00216275:25510/16:39901458 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.tandfonline.com/doi/full/10.1080/23248378.2016.1253511" target="_blank" >http://www.tandfonline.com/doi/full/10.1080/23248378.2016.1253511</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/23248378.2016.1253511" target="_blank" >10.1080/23248378.2016.1253511</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A new friction condition identification approach for wheel-rail interface

Popis výsledku v původním jazyce

In recent years, there has been an increasing interest in designing intelligent vehicles such that they can take necessary actions according to the environmental changes around them and they can inform decision makers about these changes. For safer and cheaper transport, dynamic modelling of these vehicles and identification of such changes in environment based on these models plays an important role. In this study, a sigma point Kalman filter-based scheme (i.e. joint unscented Kalman filter) is proposed to estimate maximum friction coefficient as a parameter in wheel-rail interface. This estimation scheme uses interpretation of lateral and yaw dynamic response of a wheelset to identify maximum friction coefficient. This joint unscented Kalman filter-based approach provides information about the friction conditions in wheel-rail interface without post-processing of estimated data.

Název v anglickém jazyce

A new friction condition identification approach for wheel-rail interface

Popis výsledku anglicky

In recent years, there has been an increasing interest in designing intelligent vehicles such that they can take necessary actions according to the environmental changes around them and they can inform decision makers about these changes. For safer and cheaper transport, dynamic modelling of these vehicles and identification of such changes in environment based on these models plays an important role. In this study, a sigma point Kalman filter-based scheme (i.e. joint unscented Kalman filter) is proposed to estimate maximum friction coefficient as a parameter in wheel-rail interface. This estimation scheme uses interpretation of lateral and yaw dynamic response of a wheelset to identify maximum friction coefficient. This joint unscented Kalman filter-based approach provides information about the friction conditions in wheel-rail interface without post-processing of estimated data.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JO - Pozemní dopravní systémy a zařízení

OECD FORD obor

—

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

International Journal of Rail Transportation

ISSN

2324-8378

e-ISSN

—

Svazek periodika

Neuveden

Číslo periodika v rámci svazku

13.11.2016

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

18

Strana od-do

1-18

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-84994850957