scholarly journals Emission Control Research to Enable Fuel Efficiency: Department of Energy Heavy Vehicle Technologies

2000 ◽  
Author(s):  
Gurpreet Singh ◽  
Ronald L. Graves ◽  
John M. Storey ◽  
William P. Partridge ◽  
John F. Thomas ◽  
...  
Keyword(s):  
Fuel Efficiency ◽  
Emission Control ◽  
Department Of Energy ◽  
Heavy Vehicle ◽  
Control Research ◽  
Vehicle Technologies

Commercial CFD Code Validation for Simulation of Heavy-Vehicle External Aerodynamics

2003 ◽  
Author(s):  
W. David Pointer ◽  
Tanju Sofu ◽  
David Weber
Keyword(s):  
Aerodynamic Drag ◽  
National Laboratory ◽  
Argonne National Laboratory ◽  
Department Of Energy ◽  
Force Balance ◽  
Heavy Vehicles ◽  
Safety And Health ◽  
Energy Economy ◽  
Computational Fluid Dynamics Cfd ◽  
Vehicle Technologies

The issue of energy economy in transportation has grown beyond traditional concerns over environment, safety and health to include new concerns over national and international security. In collaboration with the U.S. Department of Energy Office of FreedomCAR and Vehicle Technologies’ Working Group on Aerodynamic Drag of Heavy Vehicles, Argonne National Laboratory is investigating the accuracy of aerodynamic drag predictions from commercial Computational Fluid Dynamics (CFD) Software. In this validation study, computational predictions from two commercial CFD codes, Star-CD [1] and PowerFLOW [2], will be compared with detailed velocity, pressure and force balance data from experiments completed in the 7 ft. by 10 ft. wind tunnel at NASA Ames [3, 4] using a Generic Conventional Model (GCM) that is representative of typical current-generation tractor-trailer geometries.

Future perspectives

ESC CardioMed ◽  
2018 ◽  
pp. 3110-3111
Author(s):  
Thomas Münzel ◽  
Sanjay Rajagopalan ◽  
Mette Sørenson ◽  
Dave Newby ◽  
Robert D. Brook
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Fuel Efficiency ◽  
Noise Pollution ◽  
Mass Transit ◽  
Future Perspectives ◽  
Electric Cars ◽  
The World ◽  
Vehicle Technologies ◽  
Motorized Vehicles

Efforts to mitigate air pollution and noise are a complex endeavour as they involve addressing their sources, which vary depending on the country and region of the world and complex economic and geopolitical considerations. Measures such as mandatory or voluntary greenhouse emissions or fuel efficiency standards, shifting to lower-carbon fuels, legislating the use of motorized vehicles/kilometres driven, introduction of electric mass transit, congestion pricing/taxes, vehicle and fuel taxes, and advanced vehicle technologies (e.g. battery electric cars, hybrids, plug-in hybrids, and fuel cell cars) may help simultaneously alleviate air and noise pollution and climate change goals.

scholarly journals Multilane Spatiotemporal Trajectory Optimization Method (MSTTOM) for Connected Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Pangwei Wang ◽  
Yunfeng Wang ◽  
Hui Deng ◽  
Mingfang Zhang ◽  
Juan Zhang
Keyword(s):  
Traffic Management ◽  
Trajectory Optimization ◽  
Fuel Efficiency ◽  
Optimization Method ◽  
Connected Vehicles ◽  
Full Potential ◽  
Connected Vehicle ◽  
Vehicle Technologies ◽  
Vehicle Fuel Efficiency ◽  
Trajectory Problem

It is agreed that connected vehicle technologies have broad implications to traffic management systems. In order to alleviate urban congestion and improve road capacity, this paper proposes a multilane spatiotemporal trajectory optimization method (MSTTOM) to reach full potential of connected vehicles by considering vehicular safety, traffic capacity, fuel efficiency, and driver comfort. In this MSTTOM, the dynamic characteristics of connected vehicles, the vehicular state vector, the optimized objective function, and the constraints are formulated. The method for solving the trajectory problem is optimized based on Pontryagin’s maximum principle and reinforcement learning (RL). A typical scenario of intersection with a one-way 4-lane section is measured, and the data within 24 hours are collected for tests. The results demonstrate that the proposed method can optimize the traffic flow by enhancing vehicle fuel efficiency by 32% and reducing pollutants emissions by 17% compared with the advanced glidepath prototype application (GPPA) scheme.

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