KIT | KIT-Bibliothek | Impressum

Reinforcement Learning Framework for the self-learning Suppression of Clutch Judder in automotive Drive Trains

Sommer Obando, Hermann

Abstract: In electromechanically actuated clutches, the active damping of vibrations by means of control of the clamping force allow the use of high performance materials in the friction pairing, which makes a more energy and cost efficient design of the clutch. In this work, a reinforcement learning framework for the control of the clamping force for the active suppression of judder vibrations is proposed and developed.


Zugehörige Institution(en) am KIT Institut für Produktentwicklung (IPEK)
Publikationstyp Hochschulschrift
Jahr 2016
Sprache Englisch
Identifikator DOI(KIT): 10.5445/IR/1000061436
URN: urn:nbn:de:swb:90-614367
KITopen ID: 1000061436
Verlag Karlsruhe
Umfang 170 S.
Abschlussart Dissertation
Fakultät Fakultät für Maschinenbau (MACH)
Institut Institut für Produktentwicklung (IPEK)
Prüfungsdaten 26.01.2016
Referent/Betreuer Prof. A. Albers
Schlagworte Reinforcement Learning, Kupplungsrupfen
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft KITopen Landing Page