Hybrid neural network for modeling automotive clutches

American Society of Mechanical Engineers, Dynamic Systems and Control Division (Publication) DSC

Volumn 67, Issue , 1999, Pages 255-263

  Parvataneni, V ^a   Cao, M ^a   Wang, K W ^a   Fujii, Y ^b   Tobler, W ^b  

^a The Pennsylvania State University   (United States)

^b FORD MOTOR COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMOBILE PARTS AND EQUIPMENT; CLUTCHES; MATHEMATICAL MODELS; TORQUE;

CLUTCH ENGAGEMENT PROCESS; DYNAMIC ENGAGEMENT TORQUE; WET CLUTCH SYSTEM;

RECURRENT NEURAL NETWORKS;

EID: 0033298787     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (18)

1. Berger, E. J. (1996), An Investigation of Friction-Induced Vibration in Automatic Transmission Wet Clutches, Ph.D. Thesis In Mechanical Engineering, Purdue University.
2. Cybenko, G., 1989, "Approximation by Superpositions of a Sigmoidal Function," Mathematics of Control, Signals, and Systems, Vol. 2, pp. 303-314.
3. El-Gindy, M., and Palkovics, L., 1993, "Possible Application of Artificial Neural Networks to Vehicle Dynamics and Control: a Literature Review," International Journal of Vehicle Design, Vol. 14, pp. 592-614.
4. Fanella, R., 1994, "Development and Testing of Friction Cluthces," Design Practices - Passenger Car Automatic Transmissions, SAE, pp. 399-409.
5. Funahashi, K., 1989, "On the Approximate Realization of Continuous Mapping by Neural Networks," Neural Networks, Vol. 2, No. 3, pp. 183-192.
6. Funahashi, K., and Nakamura, Y., 1993, "Approximation of Dynamical Systems by Continuous Time Recurrent Neural Networks," Neural Networks, Vol. 6, pp. 801-806.
7. Hornik, K., Stinchcombe, M. and White, H., 1989, "Multilayer Feedforward Networks are Universal Approximators," Neural Networks, Vol. 2, pp. 359-366.
8. Jacobson, B., 1992, "Engagement of Oil Immersed Multi-Disc Clutches," International Power Transmission and Gearing Conference, Vol. 2, pp.567-574.
9. Lai J. S., 1995, "Intelligent Robust Control of Clutch-to-Clutch Shifts in Vehicle Transmission Systems," Ph.D. Thesis In Mechanical Engineering, Penn State University.
10. Narendra, K. S., and Parthasarathy, K., 1990, "Identification and Control of Dynamical Systems Using Neural Networks," IEEE Transactions on Neural Networks, Vol. 1, No. 1, pp. 4-27.
11. Natsumeda, S., and Miyoshi, T., 1994, "Numerical Simulation of Engagement of Paper Based Wet Clutch Facing," Journal of Tribology, Vol. 116, pp.232-237.
12. Parlos, A. G., Atiya, A. F., Chong, K. T., and Tsai, W. K., 1992., "Nonlinear Identification of Process Dynamics Using Neural Networks," Nuclear Technology, Vol. 97, pp.79-96.
13. Parvateneni, V., 1998, "A First Principle-Based Hybrid Neural Network Clutch Dynamics Model," M. S. Thesis in Mechanical Engineering, Penn State University.
14. Rumelhart, D. E., Hinton, G. E., and Williams, R. J., 1986. "Learning Internal Representations by Error Propagation," Parallel Distributed Processing, vol. 1, pp. 318-362.
15. Sio K. C., and Lee, C. K., 1996, "Identification of a Nonlinear Motor System with Neural Networks," International Workshop on Advanced Motion Control, Part 1, Mar 18-21, Vol. 1, pp. 287-292.
16. Wang, K. W., and Parvataneni, V., 1997, " A Neural Network-Based Clutch Dynamics Model," Penn State Report to Ford Motor Company, February.
17. Wu, H., 1978, "A Review of Porous Squeeze Films," Wear, Vol. 47, pp. 371-385.
18. Yang, Y., Lam, R. C., and Fujii, T., 1998, "Prediction of Torque Response During the Engagement of Wet Friction Clutch," SAE Paper 981097.