Publications

National Renewable Energy Laboratory, Golden, Colorado

The green routing strategy instructing a vehicle to select a fuel-efficient route benefits the current transportation system with fuel-saving opportunities. This paper introduces a navigation API route fuel-saving evaluation framework for estimating fuel advantages of alternative API routes based on large-scale, real-world travel data for conventional vehicles (CVs) and hybrid electric vehicles (HEVs). The navigation APIs, such Google Directions API, integrate traffic conditions and provide feasible alternative routes for origin-destination pairs. This paper develops two link-based fuel-consumption models stratified by link-level speed, road grade, and functional class (local/non-local), one for CVs and the other for HEVs. The link-based fuel-consumption models are built by assigning travel from a large number of GPS driving traces to the links in TomTom MultiNet as the underlying road network layer and road grade data from a U.S. Geological Survey elevation data set. Fuel consumption on a link is calculated by the proposed fuel consumption model. This paper envisions two kinds of applications: 1) identifying alternate routes that save fuel, and 2) quantifying the potential fuel savings for large amounts of travel. An experiment based on a large-scale California Household Travel Survey GPS trajectory data set is conducted. The fuel consumption and savings of CVs and HEVs are investigated. At the same time, the trade-off between fuel saving and time saving for choosing different routes is also examined for both powertrains.

U.S. Department of Energy, Washington, D.C.; Oak Ridge National Laboratory, Oak Ridge, Tennessee

This fact sheet for consumers describes a few simple tips to help obtain the best possible fuel economy from vehicles and to reduce fuel costs.

U.S. Department of Energy, Washington, D.C.

The 2015 Quadrennial Technology Review (QTR) examines the status of the science and technology that are the foundation of our energy system, together with the research, development, demonstration, and deployment (RDD&D) opportunities to advance them. It focuses primarily on technologies with commercialization potential in the midterm and beyond. It frames various trade-offs that all energy technologies must balance across such dimensions as cost, security and reliability of supply, diversity, environmental impacts, land use, and materials use. Additionally, it provides data and analysis on RDD&D pathways to assist decision makers as they set priorities, within budget constraints, to develop more secure, affordable, and sustainable energy services.