Position and Velocity Predictions of the Piston in a Wet Clutch System during Engagement by Using a Neural Network Modeling

Abstract : In a wet clutch system, a piston is used to compress the friction disks to close the clutch. The position and the velocity of the piston are the key effectors for achieving a good engagement performance. In a real setup, it is impossible to measure these variables. In this paper, we use transmission torque and slip to approximate the piston velocity and position information. By using this information, a process neural network is trained. This neural predictor shows good forecasting results on the piston position and velocity. It is helpful in designing a pressure profile which can result in a smooth and fast engagement in the future. This neural predictor can also be used in other model-based control techniques.
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Communication dans un congrès
Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-381 (Part I), pp.474-482, 2012, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-33409-2_49〉
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Yu Zhong, Bart Wyns, Abhishek Dutta, Clara-Mihaela Ionescu, Gregory Pinte, et al.. Position and Velocity Predictions of the Piston in a Wet Clutch System during Engagement by Using a Neural Network Modeling. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 8th International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2012, Halkidiki, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-381 (Part I), pp.474-482, 2012, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-33409-2_49〉. 〈hal-01521397〉

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