Non-linear control of a gear shift process in a dual-clutch transmission based on a neural engine model
| Autor: | Dariusz Wędrychowicz, Piotr Bera, Wojciech Sikora |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Artificial neural network
Computer science Applied Mathematics media_common.quotation_subject Emphasis (telecommunications) Process (computing) Nonlinear control Inertia Computer Science Applications Mechanism (engineering) Transmission (telecommunications) Control and Systems Engineering Control theory Clutch Electrical and Electronic Engineering media_common |
| Zdroj: | Control Engineering Practice. 115:104886 |
| ISSN: | 0967-0661 |
| DOI: | 10.1016/j.conengprac.2021.104886 |
| Popis: | The paper presents an engine control algorithm, based on an artificial neural network (ANN), which ensures a quick and smooth inertia phase of an upshift in a dual-clutch transmission (DCT). The main emphasis is placed on 3D characteristics, which can be directly implemented in the ECU, to control the inertia phase, when the engine speed decreases to reach the target clutch speed. They are developed based on an ANN model which approximates data obtained during engine test bed measurements in dynamic states. Moreover, to provide an overall gear change algorithm, the dual-clutch assembly activation mechanism was also analysed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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