EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021
(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)
2/26/2018 | 2:15 PM - 3:05 PM | Optimization of Electric Vehicle System Models for Improved Decision Making | Summit A
Optimization of Electric Vehicle System Models for Improved Decision Making
In the coming years, electric vehicles, charge stations, and electrified roadways will increasingly become an integral part of the transportation system. No one can fully characterize this system in advance, but the associated models and analyses can help guide the decision making required to avoid obstacles during the implementation and adoption phases. The myriad technologies, perspectives, and policies are necessarily interdependent. These future technologies will undoubtedly change the behaviors of individuals, manufacturers, and government agencies. Further, public expectations and response will simultaneously drive the technology. Models that can extract emergent behavior from the possible future states are invaluable for policy makers, technologists, and others in making key decisions that impact society economically, environmentally, and sociologically. Both the exploration and optimization of these models can provide insights that may be non-intuitive and unpredictable. This presentation explores the potential to leverage and optimize system-level models in building confidence for evidence-based decision making.
- Explore the multi-dimensional design space of system-level EV infrastructure models
- Examine the constraints and other multi-objective optimization parameters across the space
- Evaluate the impacts and outcomes from system-level modeling results
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Presenters/Authors
John Salmon
(), Brigham Young University, johnsalmon@byu.edu;
John Salmon currently works as an assistant professor at BYU in the Mechanical Engineering department. He received his B.S. and M.S. degrees in Electrical Engineering at the University of Calgary and Utah State University respectively, and then received M.S. and Ph.D. degrees in Aerospace Engineering at the Georgia Institute of Technology. As a Research Engineer at the Aerospace Systems Design Laboratory for four years he worked with a variety of industry partners and government agencies including Lockheed Martin, General Electric, FedEx, UTRC/Sikorsky, NASA, AFRL, ARL, and NAVAIR. His research interests include systems engineering, design, and integration, multi-disciplinary optimization, operations research, visual and data analytics, modeling and simulation, multi-agent multi-objective decision making, virtual reality, and uncertainty analysis.
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