A hybrid-electric vehicle powertrain architecture consists of single or multiple driving modes, i.e., connection arrangements among engine, motors and vehicle output shaft that determine distribution of power. While most architecture development work to date has focused primarily on passenger cars, interest has been growing in exploring architectures for special-purpose vehicles such as vans or trucks for civilian and military applications, whose weights or payloads can vary significantly during operations. Previous findings show that the optimal architecture can be sensitive to vehicle weight. In this paper we investigate architecture design under a distribution of vehicle weights, using a simulation-based design optimization strategy with nested supervisory optimal control and accounting for powertrain complexity. Results show that an architecture under a single load has significant differences and lower fuel efficiency than an architecture designed to work under a variety of loading scenarios.
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ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
August 17–20, 2014
Buffalo, New York, USA
Conference Sponsors:
- Design Engineering Division
- Computers and Information in Engineering Division
ISBN:
978-0-7918-4634-6
PROCEEDINGS PAPER
Optimal Dual-Mode Hybrid Electric Vehicle Powertrain Architecture Design for a Variety of Loading Scenarios
Alparslan Emrah Bayrak,
Alparslan Emrah Bayrak
University of Michigan, Ann Arbor, MI
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Panos Y. Papalambros
Panos Y. Papalambros
University of Michigan, Ann Arbor, MI
Search for other works by this author on:
Alparslan Emrah Bayrak
University of Michigan, Ann Arbor, MI
Yi Ren
University of Michigan, Ann Arbor, MI
Panos Y. Papalambros
University of Michigan, Ann Arbor, MI
Paper No:
DETC2014-34897, V003T01A005; 9 pages
Published Online:
January 13, 2015
Citation
Bayrak, AE, Ren, Y, & Papalambros, PY. "Optimal Dual-Mode Hybrid Electric Vehicle Powertrain Architecture Design for a Variety of Loading Scenarios." Proceedings of the ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 3: 16th International Conference on Advanced Vehicle Technologies; 11th International Conference on Design Education; 7th Frontiers in Biomedical Devices. Buffalo, New York, USA. August 17–20, 2014. V003T01A005. ASME. https://doi.org/10.1115/DETC2014-34897
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