This paper discusses simulations of a control scheme based on locally sparse coded networks (CMACs) for a novel previously proposed continuously variable transmission (CVT), a hybrid continuously variable power split transmission (CVPST) (Osdemir and Schueller, 2002). Automotive transmissions match the speed and the torque of the power source to the speed and torque requirements of the load. Properly designed CVTs have shown potential to improve efficiency and performance. The main advantage of CMACs is fast computation because of their simple operational principles. Simulation results have shown that memory contents either reach a stable limit cycle or an attractor based on the selection of network parameters and the training method. Both online and offline training are possible.
Local sparse coding control of CVPSTs
Lokal vereinfachte Steuerung in stufenlosen CVT-Getrieben
International Journal of Heavy Vehicle Systems (IJHVS) (Internet) ; 12 , 2 ; 104-120
2005
17 Seiten, 14 Bilder, 3 Tabellen, 18 Quellen
Article (Journal)
English
Algorithmus , Kraftstoffeinsparung , neuronale Netzwerkarchitektur , neuronales Netzwerk , mathematisches Modell , CVT-Getriebe , Hybridantrieb , Drehmoment , Drehmomentenwandler , Antriebsstrangkomponente , lernende Regelung , Robotersteuerung , Rechnersimulation , Anwendung im Fahrzeugbau , Kraftübertragung
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