Projects per year
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.
| Original language | English |
|---|---|
| Title of host publication | Conference Design of Experiments (DOE) in Engine Development |
| Place of Publication | Renningen |
| Publisher | expert verlag GmbH |
| Pages | 190-197 |
| ISBN (Print) | 978-3-8169-3217-8 |
| Publication status | Published - 2013 |
| Event | Conference Design of Experiments (DOE) in Engine Development - Berlin, Germany Duration: 18 Jun 2013 → 19 Jun 2013 |
Publication series
| Name | Design of Experiments (DoE) in Engine Development |
|---|---|
| Publisher | Expert Verlag |
Conference
| Conference | Conference Design of Experiments (DOE) in Engine Development |
|---|---|
| Country/Territory | Germany |
| City | Berlin |
| Period | 18/06/13 → 19/06/13 |
Fields of Expertise
- Mobility & Production
Treatment code (Nähere Zuordnung)
- Application
- Theoretical
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Dive into the research topics of 'Accuracy of Friction Estimation during Driving'. Together they form a unique fingerprint.Projects
- 1 Finished
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FTG-S04 Estimation of tire-road friction
Lex, C. (Co-Investigator (CoI))
1/05/08 → 31/12/23
Project: Research project