Abstract
Today's transportation is quickly transforming with the nascent advent of connectivity, automation, shared-mobility, and electrification. These technologies will not only affect our safety and mobility, but also our energy consumption, and environment. As a result, it is of unprecedented importance to understand the overall system impacts due to the introduction of these emerging technologies and concepts. Existing modeling tools are not able to effectively capture the implications of these technologies, not to mention accurately and reliably evaluating their effectiveness with a reasonable scope. To address these gaps, a dynamometer-in-the-loop (DiL) development and testing approach is proposed which integrates test vehicle(s), chassis dynamometer, and high fidelity traffic simulation tools, in order to achieve a balance between the model accuracy and scalability of environmental analysis for the next generation of transportation systems. With this DiL platform, a connected eco-operation system for the plug-in hybrid electric bus (PHEB) has been developed and tested, which can optimize the vehicle dynamics (and potentially powertrain control via smart energy management) to reduce the operational energy consumption as well as tailpipe emissions of the target PHEB. The system performance has been evaluated on the DiL platform with respect to a variety of traffic congestion levels. The results have shown that the developed system can save fuel by more than 13% while reducing the electricity consumption by 2% in the test scenarios.
Original language | English |
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Journal | SAE Technical Papers |
Volume | 2020-April |
Issue number | April |
DOIs | |
State | Published - Apr 14 2020 |
Event | SAE 2020 World Congress Experience, WCX 2020 - Detroit, United States Duration: Apr 21 2020 → Apr 23 2020 |
Funding
This research is supported by the U.S. Department of Energy, under the ARPA-E NEXTCAR Program. The contents of this paper reflect only the viewpoints of the authors, who are responsible for the facts and the accuracy of the data presented. The authors would also like to thank Daniel Sandez, Alex Vu, and Mike Todd from UC Riverside, Tim LaClair from Oak Ridge National Laboratory, and Christophe Salgues and Abas Goodarzi from US Hybrid, for their strong supports and constructive comments for the DiL testing.
Funders | Funder number |
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ARPA-E NEXTCAR | |
U.S. Department of Energy |