Ford Motor Company

About: Ford Motor Company is a company organization based out in Dearborn, Michigan, United States. It is known for research contribution in the topics: Internal combustion engine & Clutch. The organization has 36123 authors who have published 51450 publications receiving 855200 citations. The organization is also known as: Ford Motor & Ford Motor Corporation.

Real time vehicle speed prediction using a Neural Network Traffic Model

Abstract: Prediction of the traffic information such as flow, density, speed, and travel time is important for traffic control systems, optimizing vehicle operations, and the individual driver. Prediction of future traffic information is a challenging problem due to many dynamic contributing factors. In this paper, various methodologies for traffic information prediction are investigated. We present a speed prediction algorithm, NNTM-SP (Neural Network Traffic Modeling-Speed Prediction) that trained with the historical traffic data and is capable of predicting the vehicle speed profile with the current traffic information. Experimental results show that the proposed algorithm gave good prediction results on real traffic data and the predicted speed profile shows that NNTM-SP correctly predicts the dynamic traffic changes.

Thermodynamic guidelines for the prediction of hydrogen storage reactions and their application to destabilized hydride mixtures

Abstract: We propose a set of thermodynamic guidelines aimed at facilitating more robust screening of hydrogen-storage reactions. The utility of the guidelines is illustrated by reassessing the validity of reactions recently proposed in the literature and through vetting a list of more than 20 candidate reactions based on destabilized $\mathrm{Li}\mathrm{B}{\mathrm{H}}_{4}$ and $\mathrm{Ca}{(\mathrm{B}{\mathrm{H}}_{4})}_{2}$ borohydrides. Our analysis reveals several reactions having both favorable thermodynamics and relatively high hydrogen densities (ranging from $5\phantom{\rule{0.3em}{0ex}}\text{to}\phantom{\rule{0.3em}{0ex}}9\phantom{\rule{0.3em}{0ex}}\mathrm{wt}\phantom{\rule{0.2em}{0ex}}%$ ${\mathrm{H}}_{2}$ and $85\phantom{\rule{0.3em}{0ex}}\text{to}\phantom{\rule{0.3em}{0ex}}100\phantom{\rule{0.3em}{0ex}}\mathrm{g}$ ${\mathrm{H}}_{2}∕\mathrm{l}$), and it demonstrates that chemical intuition alone is not sufficient to identify valid reaction pathways.