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| Content Provider | The American Society of Mechanical Engineers (ASME) Digital Collection |
|---|---|
| Author | Song, Xingyong Zulkefli, Mohd Azrin Mohd Sun, Zongxuan Miao, Hsu-Chiang |
| Copyright Year | 2008 |
| Abstract | Clutch fill control is critical for automotive transmission performance and fuel economy, including both automatic and hybrid transmissions. The traditional approach, by which the clutch fill pressure command is manually calibrated, has a couple of limitations. First, the pressure profile is not optimized to reduce the peak clutch fill flow demand. Moreover, it is not systematically designed to account for uncertainties in the system, such as variations of solenoid valve time delay and parameters of the clutch assembly. In this paper, we present a systematic approach to evaluate the clutch fill dynamics and synthesize the optimal pressure profile. First, a clutch fill dynamic model is constructed and analyzed. Second, the applicability of the conventional numerical Dynamic Programming (DP) algorithm to the clutch fill control problem is explored and shown to be ineffective. Thus we developed a new customized DP method to obtain the optimal and robust pressure profile subject to specified constraints. After a series of simulations and case studies, the new customized DP approach is demonstrated to be effective, efficient, and robust for solving the clutch fill optimal control problem. |
| Sponsorship | Dynamic Systems and Control Division |
| Starting Page | 463 |
| Ending Page | 470 |
| Page Count | 8 |
| File Format | |
| ISBN | 9780791843352 |
| DOI | 10.1115/DSCC2008-2166 |
| e-ISBN | 9780791838389 |
| Volume Number | ASME 2008 Dynamic Systems and Control Conference, Parts A and B |
| Conference Proceedings | ASME 2008 Dynamic Systems and Control Conference |
| Language | English |
| Publisher Date | 2008-10-20 |
| Publisher Place | Ann Arbor, Michigan, USA |
| Access Restriction | Subscribed |
| Subject Keyword | Uncertainty Valves Pressure Flow (dynamics) Solenoids Algorithms Fuel efficiency Simulation Automotive transmissions Dynamics (mechanics) Optimal control Dynamic models Dynamic programming Delays Engineering simulation Manufacturing Corporate average fuel economy |
| Content Type | Text |
| Resource Type | Article |
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