Abstract
Hydrostatic transmission (HST) is a common hydraulic drive train transmission used in track loaders and other high power off-road vehicles. While reliable, traditional HST with fixed-displacement motors has relatively poor efficiencies. In this paper, alternative HST and series hybrid drive train architectures are proposed to replace the traditional HST to allow the implementation of optimal control and optimization methods for better vehicle fuel efficiency. Besides the optimal control methods applied to minimize fuel consumption, the proposed architectures are also optimized for the best configuration in terms of component sizing. Backward-facing (acausal) simulation models were developed to estimate the fuel efficiency of each architecture. Finally, each architecture is compared for optimized performance and fuel saving relative to the traditional HST as baseline.
| Original language | English (US) |
|---|---|
| Title of host publication | 2021 American Control Conference, ACC 2021 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 628-633 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781665441971 |
| DOIs | |
| State | Published - May 25 2021 |
| Event | 2021 American Control Conference, ACC 2021 - Virtual, New Orleans, United States Duration: May 25 2021 → May 28 2021 |
Publication series
| Name | Proceedings of the American Control Conference |
|---|---|
| Volume | 2021-May |
| ISSN (Print) | 0743-1619 |
Conference
| Conference | 2021 American Control Conference, ACC 2021 |
|---|---|
| Country/Territory | United States |
| City | Virtual, New Orleans |
| Period | 5/25/21 → 5/28/21 |
Bibliographical note
Funding Information:ACKNOWLEDGMENT This material is based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Vehicle Technologies Office Award Number DE-EE0008335. We are grateful to Paul Michael at the Milwaukee School of Engineering for providing component efficiency maps, and to the Minnesota Supercomputing Institute (MSI) at the University of Minnesota for providing computing resources.
Funding Information:
*This work was funded by the United States Department of Energy The authors are with the Center for Compact and Efficient Fluid Power (CCEFP), Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA harto013@umn.edu, lixxx099@umn.edu
Publisher Copyright:
© 2021 American Automatic Control Council.
