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 | Feasibility of Dynamic Wireless Power Transfer for In-motion Charging of Electric Vehicles | Summit A
Feasibility of Dynamic Wireless Power Transfer for In-motion Charging of Electric Vehicles
This study focuses on understanding the economic feasibility, environmental impact, and infrastructure optimization of in-motion WPT applied to the U.S. transportation fleet. Integrating geographically diverse real-world drive cycles with dynamic vehicle models and variable vehicle adoption and infrastructure deployment rates, the economic feasibility, environmental impact and infrastructure requirements were determined. Technology optimization results show that the vehicle characteristics of a WPT EV fleet will consist of 25-mile range EVs with 2C stationary charging at locations stopped greater than one hour and 50 kW charging on high-speed (greater than 30 miles per hour (mph) primary and secondary roadways, representing a total roadway infrastructure cost of $1.45 trillion. When used in conjunction, optimized vehicle and roadway architectures satisfy 97.7% of 24-hour drive cycles, a 22.4% increase from when no in-motion charging is used. Work includes the assessment of the economic viability and environmental impact of a national role out.
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Presenters/Authors
Jason Quinn
(), Colorado State University, jason.quinn@colostate.edu;
Jason Quinn is an assistant professor in the Mechanical Engineering Department Colorado State University. His education and research have always been centered on energy with his current work focused on system evaluation of electric transportation, microalgae biofuels, and nuclear power systems. Research efforts are dedicated to the development of engineering system models validated through experimentation and leveraged for techno-economic evaluation, life cycle assessment, and resource demand of emerging technologies. Results from modeling work are used to focus research and development efforts to high impact areas. Jason completed a master’s degree at the University of Wisconsin-Madison in nuclear engineering and engineering physics, and a PhD at Colorado State University in Mechanical Engineering.
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