Transportation Engineering and Science Program
The broad multidisciplinary expertise and world-class facilities brought together by three main
research partners enable forward-looking and complex perspectives for future transportation systems while
we are focusing our energy R&D portfolio on delivering systems- level solutions. Our vision is to
integrate energy science and technology to create a sustainable and livable community. Breakthroughs
and experience at ORNL in vehicle systems, communication, the Internet of things, cyber security,
artificial intelligence, and high- performance computing facilitate further development, validation,
and testing to the creation along with our partners in the USDOT designated Automated Vehicle Proving Ground.
For example, cyber security is obviously critical to CAVs. Researchers in our Center for
Trustworthy Embedded Systems are conducting privacy research that is related to connected vehicles
for the National Highway Traffic Safety Administration, Federal Highway Administration, and US DOT's
Intelligent Transportation Systems Joint Program Office. Public agencies and private manufacturers
can benefit from a longer-term real-world validation of systems such as the vehicle-based credential
generation system, and tools, including the metric- based privacy tools.
Automakers, such as Toyota, have expressed their interest in testing and to evaluating new
vehicle technology through a simulation capability being established at ORNL. With the
USDOT-designated Automated Vehicle Proving Ground, reality in the proving ground can be integrated
into the simulation capability, and the integration accommodates more realistic interaction between
cyber and physical systems. It indicates that the USDOT designated proving ground can accelerate the
testing and evaluation of new vehicle technologies with reliable results, repeatable tests, and lower
cost in southeastern United States.
Research issues related to connected and automated vehicles
R&D activities on CAVs enable individual vehicles and traffic control centers to better monitor transportation network conditions and make better operating
decisions to improve safety and reduce pollution, energy consumption, and travel delays. This research is conducted by ORNL and partners at UTK and TTU. Many
stakeholders intuitively see the benefits of multiscale vehicle control systems and have started to develop business cases for their respective domains, including
the automotive industry, insurance companies, government, and service providers. It seems clear that the availability of vehicle-to-vehicle communication has
the potential to reduce traffic accidents and ease congestion by enabling vehicles to more rapidly account for changes in their mutual environment. Likewise,
vehicle-to-infrastructure communication (e.g., communication with roadway structures, nearby buildings, and traffic lights) allow for individual vehicle
control systems to account for unpredictable changes in carrying capacity.
Much progress has been made in improving safety with CAVs; however, some improvements have been incremental, and there has been considerable repetition
of a limited number of basic concepts. It appears that the current state of the art is now at a point where new and significantly different approaches are needed.
In particular, we need to determine how much we can improve the efficiency in transportation if we assume that the vehicles are connected and can exchange
information with each other and with infrastructure? ORNL has developed several
initiatives with the goal to investigate how we can use scalable data and informatics to enhance the understanding of the environmental implications of
CAVs and to improve transportation sustainability and accessibility. We have several ongoing projects related to transportation and energy that focus
on developing the theory and algorithms for making cyber- physical systems able to learn how to improve their performance over time while interacting
with their environment. Applications include CAVs with the aim of (1) becoming eco-friendly; (2) realizing the optimum performance and efficiency
based on the needs and preferences of consumers; and (3) learning how traffic information can positively impact considerations of the environment,
traffic, safety and traffic congestion. Given the recent technological developments, several research efforts have considered approaches to achieve
safe and efficient coordination of merging maneuvers with the intention to avoid severe stop-and-go driving. In this direction, we have developed
an optimization framework to control the merging maneuvers of a fleet of CAVs to achieve smooth traffic flow without stop-and-go driving. The
efficiency of our approach has shown significant reductions of fuel consumption and travel time. More recently and with the aim to investigate
the energy impacts of different penetration rates of CAVs and their interaction with human-driven vehicles, we developed a simulation framework for mixed
traffic (CAVs interacting with human-driven vehicles) in merging roadways and analyzed the energy impact of different penetration rates of CAVs on energy
consumption. Using different penetration rates of CAVs, the simulation results indicated that for low penetration rates, the fuel consumption benefits are
significant but the total travel times increase. The benefits in travel time were noticeable for higher penetration rates of CAVs.
Research issues related to wireless power transfer for CAV futures
Electrification and CAVs are likely to go hand in hand. This project identifies and addresses the research needs for the dynamic and quasi-dynamic
(also known as opportunistic) electric vehicle charging applications based on wireless power transfer (WPT). This project reviews the high-power wireless
power transfer technologies and leverages the existing ORNL knowledge and experience in this field to determine the best electromagnetic coupler
configurations; power electronics architectures, both for the grid-side and high-frequency components; and the vehicle-side receivers and
power-conditioning systems. An integrated hardware system is developed to demonstrate the proof of concept of high-power, in-motion wireless
charging systems with the comprehensive analysis of energy delivery, cost and efficiency projections, and determination of system limitations
while meeting the constraints posed by electromagnetic field emissions and reasonable efficiency. The impact of lateral misalignments also
is studied with respect to their impact on the efficiency and energy delivery to the vehicles. In particular, the general analysis covers
the system cost analysis, techno-economic feasibility, and the impact of different charging power levels and vehicle speeds. Preliminary
analysis conducted at ORNL considered a constant speed of 50 mph and an average consumption of 0.3 kWh/mile. The dynamic WPT feasibility
analysis considers various speeds and the vehicle energy consumptions with respect to speed and road conditions.
Cost per mile of the energy received is related to the WPT technology deployed with a cost model that includes the balance
of system cost, operating and maintenance cost, and the cost of the energy delivery. A method is investigated for the system deployment
such as determining the feasible locations for WPT siting on highways and in cities, on highway merging and exit ramps, and on city
intersections and arterials, including the mobility districts.
Automated driving plays an important role in the future of automotive zero-emissions driving, particularly in urban high-density
areas. The Internet of things are highly relevant for transportation, and wireless charging can become relevant in the context of
vehicle-to- infrastructure connectivity. This research additionally investigates WPT technologies related to the connected and
automated vehicles by implementing scenarios on adaptive cruise control, following distance control, eco-routing, and keeping the
vehicles in lane (correcting the lateral misalignments). The technology barriers is studied regarding the vehicle-to-vehicle
and vehicle-to-infrastructure communications, in-vehicle mobile communications and interfaces, and semiautomated or self-driven
vehicles. At a larger scale, the results and lessons of this project is used for integrated transportation management,
big data analytics, cloud computing, and mobility cost-saving applications. At the larger scale, TennSMART project
provides findings for grid connectivity and services (i.e., the ancillary or grid support services that can be provided
to the power system while no vehicles are passing over and the systems are idle). These services can include distribution
system voltage control, power quality improvement, absorbing/injecting reactive power to and from grid, and renewable energy integration.
Fuels, engines, and emissionsh
At the ORNL Fuels, Engines, and Emissions Research Center (FEERC) R&D is focused on the interrelated areas of advanced
combustion engines, lubricants, fuels, and emissions controls. The FEERC research develops knowledge and accelerates the deployment
of renewable fuels and new technologies that increase vehicle efficiency, reduce petroleum consumption, and decrease harmful emissions.
FEERC scientists from diverse backgrounds-including mechanical and chemical engineers, chemists, physicists, and environmental
scientists-work closely with industry to develop and evaluate new engine technologies, alternative fuels, and emissions controls.
Research is performed at all levels, from basic chemistry to component studies to engine systems and full vehicle applications.
Scientists also leverage one-of-a-kind expertise and facilities at ORNL in the areas of leadership computing, neutron sciences,
materials characterization, advanced manufacturing, and biosciences.
Vehicle Systems Integration
The ORNL Vehicle Systems Integration (VSI) Laboratory provides a unique and integrated solution to understanding
transportation technologies in real-world conditions. The VSI Laboratory addresses the complex interactions of advanced
powertrain technologies by performing prototype component-level research and characterization as well as complete powertrain
integration R&D, targeting system efficiency optimization and emissions reductions. It can accommodate engines, electric motors,
transmissions, and complete conventional or hybrid powertrains for most application sizes up to class 8 trucks. Regardless of the
component or system under test and test cell configuration, the VSI Laboratory is capable of emulating a virtual vehicle environment
to assess the behavior of that component or system from a vehicle perspective. This is achieved thanks to a "hardware-in-the-loop"
platform that runs real-time models of the components that are not physically present inside the test cell.
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