Accuracy of Friction Estimation during Driving

Hans-Ulrich Kobialka, Cornelia Lex

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem Konferenzband

Abstract

Accuracy of online friction estimation depends on the ability of the sensors to capture information about the current interaction between road and tire. Sensors have differ-ent characteristics and limitations, so depending on the situation their contribution varies. In this work we investigated the construction of a model that maps a driving situation (represented as sensor data time series) to the accuracy of friction estimation that can be expected for this particular situation. To train such a model from data, we used „Echo State Networks“, a method for constructing and training large Recurrent Neural Networks.
Originalspracheenglisch
TitelConference Design of Experiments (DOE) in Engine Development
ErscheinungsortRenningen
Herausgeber (Verlag)expert verlag GmbH
Seiten190-197
ISBN (Print)978-3-8169-3217-8
PublikationsstatusVeröffentlicht - 2013
VeranstaltungConference Design of Experiments (DOE) in Engine Development - Berlin, Deutschland
Dauer: 18 Jun 201319 Jun 2013

Publikationsreihe

NameDesign of Experiments (DoE) in Engine Development
Herausgeber (Verlag)Expert Verlag

Konferenz

KonferenzConference Design of Experiments (DOE) in Engine Development
LandDeutschland
OrtBerlin
Zeitraum18/06/1319/06/13

Fields of Expertise

  • Mobility & Production

Treatment code (Nähere Zuordnung)

  • Application
  • Theoretical

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