Energy Saving Potentials of CAVs

Sciarretta, Antonio; Vahidi, Ardalan

doi:10.1007/978-3-030-24127-8_1

Cited by 8 publications

(4 citation statements)

References 129 publications

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“…In practice, the implementation of vehicle platooning poses some issues. Sciarretta and Vahidi (2020a) indicate that the development of truck platooning has resulted in significant challenges, e.g., platoon string stability (avoid the amplification of disturbances from the platoon leader to the downstream vehicles. ), communication needs, control design, and formation scheduling.…”

Section: Vehicle Platooningmentioning

confidence: 99%

Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

Othman

Nunzio

Sciarretta

et al. 2021

Handbook of Climate Change Mitigation and Adaptation

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In the member countries of the Organization for Economic Cooperation and Development (OECD), projections show that the improved energy efficiency in transportation may lead to a net decline of about 2% in energy use until 2040, thus outpacing the predicted increase of vehicle-miles traveled (VMT). However, in OECD-Europe, transportation still represents the biggest source of carbon emissions, contributing by about 25% to the total CO2 emissions, with cars and vans representing more than two thirds of this share. The situation is even more alarming in non-OECD countries, where the transportation energy demand is expected to rise by 64% until 2040. The shift that we are witnessing toward the adoption of connected and automated vehicles (CAVs) is going to be perhaps, the most disruptive since the early days of automobiles and could revolutionize movement of people and goods. This level of connectivity and autonomy will transform transportation in several dimensions with important societal and economic impacts: improved safety, increased comfort, time saving potential, and more efficient road utilization are among the most widely discussed positive impacts of CAVs. However, the potential energy efficiency benefits of these technologies remain uncertain. From a single-vehicle efficiency perspective, research suggests that lightweight, low-speed, autonomous vehicles have the potential to achieve fuel economy an order of magnitude higher than current cars. Yet, at system-wide level, current estimates suggest that the total energy consumption impacts can range from a 90% decrease to a 200% increase in fuel consumption as compared to a projected 2050 baseline energy consumption. The paradigm that traffic congestion mitigation should reduce CO2 emissions is yet to be proved. Therefore, interest in transportation regulation problems with explicit environmental considerations is growing. This work takes a more in-depth look at increased opportunities for energy-efficient driving with energy-oriented traffic management and CAVs deployment. In particular, the focus will be put on the road traffic control strategies in urban networks using connectivity to enable variable speed limits and traffic light adaptive control, as well as the energy-saving opportunities that arise for individual CAVs by anticipating future road geometry, traffic conditions, and interactions with neighboring vehicles.

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Section: Vehicle Platooningmentioning

confidence: 99%

Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

Othman

Nunzio

Sciarretta

et al. 2021

Handbook of Climate Change Mitigation and Adaptation

Self Cite

View full text Add to dashboard Cite

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“…They widen the scope of possibilities in terms of rerouting, green priority, speed advice at intersections, cooperative control, vehicle platooning, etc. [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Impact of Variable Speed Limits on Environmental Sustainability and Traffic Performance in Urban Networks

Othman

Nunzio

Domenico

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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This work focuses on evaluating the potential of variable speed limits (VSLs) in a synthetic urban network to improve both environmental sustainability and traffic performance. The traffic system is modeled using the microscopic traffic simulator SUMO, and a physical fuel consumption and NOx emission model is used to assess the vehicles' energy efficiency. Speed limits are controlled through a nonlinear model predictive control (NMPC) approach, in which the traffic evolution and fuel consumption are respectively predicted with a macroscopic traffic model, namely the cell transmission model (CTM), and a pre-calibrated artificial neural network (ANN). The results reveal that in transient phases between different levels of congestion, the proposed eco-VSL controller is faster to decongest the network, resulting in an improvement of the environmental sustainability and the traffic performance both in the controlled network, and at its boundary roads.

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“…With increased penetration of electrification and connectivity technologies in the market, the potential for intelligent and energy-efficient transportation becomes more salient. 1 According to the U.S. Energy Information Administration (EIA) 2020 outlook for the transportation industry, light-duty hybrid electric vehicle sales in the U.S. are predicted to increase 3.1% per year, rising to a projected sales of more than 900,000 vehicles in 2050, while battery electric vehicle (BEV) sales will increase by 6% per year on average. 2 HEV/ BEV powertrain is a complex system consisting of numerous sub-systems.…”

Section: Introductionmentioning

confidence: 99%

“…This can be utilized for intelligent control and energy saving. 1 Connectivity information is helpful for the energy-efficient operation of conventional vehicles, EVs, and HEVs. It is important to note that the mechanisms for the energy saving are powertrain-dependent; meaning that for instance when the CAVs are HEV with more flexibility in selecting the vehicle powertrain operating modes, the connected vehicles have more ability to translate the accessed data to energy savings through V2C connectivity.…”

Section: Introductionmentioning

confidence: 99%

Important powertrain dynamics for developing models for control of connected and automated electrified vehicles

Hemmati

Yadav

Surresh

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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Connected and Automated Vehicles (CAV) technology presents significant opportunities for energy saving in the transportation sector. CAV technology forecasts vehicle and powertrain power needs under various terrain, ambient, and traffic conditions. Integration of the CAV technology in Hybrid Electric Vehicles (HEVs) provides the opportunity for optimal vehicle operation. Indeed, Hybrid Electric Vehicle powertrains present high degrees of flexibility and possibility for choosing optimum powertrain modes based on the predicted traction power needs. In modeling complex CAV powertrain dynamics, the modeler needs to consider short-time scale powertrain dynamics, such as engine transients, and hysteresis of mode-switching for a multi-mode HEV. Therefore, the powertrain dynamics essential for developing powertrain controllers for a class of connected HEVs is presented. To this end, control-oriented powertrain dynamic models for a test vehicle consisting of full electric, hybrid, and conventional engine operating modes are developed. The resulting powertrain model can forecast vehicle traction torque and energy consumption for the specified prediction horizon of the test vehicle. The model considers different operating modes and associated energy penalty terms for mode switching. Thus, the vehicle controller can determine the optimum powertrain mode, torque, and speed for forecasted vehicle operation via utilizing connectivity data. The powertrain model is validated against the experimental data and shows prediction error of less than 5% for predicting vehicle energy consumption. The model is used to create energy penalty maps that can be used for CAV control, for example fuel penalty map for engine torque changes (10–40 Nm) at each engine speed. The results of model-based optimization show optimum switching delays ranging from 0.4 to 1.4 s to avoid hysteresis in mode switching.

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Energy Saving Potentials of CAVs

Cited by 8 publications

References 129 publications

Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

Analysis of the Impact of Variable Speed Limits on Environmental Sustainability and Traffic Performance in Urban Networks

Important powertrain dynamics for developing models for control of connected and automated electrified vehicles

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