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Institution

Ford Motor Company

CompanyDearborn, Michigan, United States
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 & Signal. The organization has 36123 authors who have published 51450 publications receiving 855200 citations. The organization is also known as: Ford Motor & Ford Motor Corporation.


Papers
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Journal ArticleDOI
TL;DR: The use of composites in primary structural areas of the vehicle, such as body structures, has been very limited to date as discussed by the authors, with the exception of a few specialized low volume vehicles, having been used in semi-structural or decorative parts.

211 citations

Proceedings ArticleDOI
29 Jul 2010
TL;DR: In this paper, a stochastic model predictive control (SMPC) is used for power management in vehicles equipped with advanced hybrid powertrains, where the power demand from the driver is modeled as a Markov chain estimated on several driving cycles and used to generate scenarios in the SMPC law.
Abstract: This paper illustrates the use of stochastic model predictive control (SMPC) for power management in vehicles equipped with advanced hybrid powertrains Hybrid vehicles use two or more distinct power sources for propulsion, and their complex powertrain architecture requires the coordination of all the subsystems to achieve target performances in terms of fuel consumption, driveability, component life-time, exhaust emissions Many control strategies have been presented and successfully applied, mainly based on heuristics or rules and tuned on certain reference drive cycles To take into account that cycles are not exactly known a priori in driving routine, this paper proposes a stochastic approach for the power management problem We focus on a series hybrid electric vehicle (HEV), which combines an internal combustion engine and an electric motor The power demand from the driver is modeled as a Markov chain estimated on several driving cycles and used to generate scenarios in the SMPC law Simulation results over a standard driving cycle are presented to demonstrate the effectiveness of the proposed stochastic approach and compared with other deterministic approaches

211 citations

Journal ArticleDOI
01 Jan 1990-Wear
TL;DR: In this paper, four automotive friction system hot spot types are introduced and discussed: asperity, focal, distortional, and regional hot spots are discussed, as well as metal countersurface wear consequences.

210 citations

Journal ArticleDOI
01 Aug 2007-Sleep
TL;DR: This is the first placebo-controlled investigation to demonstrate that long-term nightly pharmacologic treatment of primary insomnia with any hypnotic enhanced quality of life, reduced work limitations, and reduced global insomnia severity, in addition to improving patient-reported sleep variables.
Abstract: Study Objectives: To evaluate 6 months' eszopiclone treatment upon patient-reported sleep, fatigue and sleepiness, insomnia severity, quality of life, and work limitations.

210 citations

Journal ArticleDOI
28 Sep 1991
TL;DR: In this article, it was shown that nearly optimal torque capability can be achieved when the stator flux reference is varied as the inverse of the rotor speed for field weakening operation over the entire speed range.
Abstract: In a conventional rotor flux oriented induction motor drive, the flux reference is usually made proportional to the inverse of the rotor speed for field weakening operation. The authors indicate, however, that such a variation cannot maintain optimal (maximum) torque capability maintain optimal (maximum) torque capability of the machine over the entire speed range. It is further shown that nearly optimal torque capability can be achieved in a stator flux oriented system when the stator flux reference is varied as the inverse of the rotor speed. >

210 citations


Authors

Showing all 36140 results

NameH-indexPapersCitations
Anil K. Jain1831016192151
Markus Antonietti1761068127235
Christopher M. Dobson1501008105475
Jack Hirsh14673486332
Galen D. Stucky144958101796
Federico Capasso134118976957
Peter Stone130122979713
Gerald R. Crabtree12837160973
Douglas A. Lauffenburger12270555326
Abass Alavi113129856672
Mark E. Davis11356855334
Keith Beven11051461705
Naomi Breslau10725442029
Fei Wang107182453587
Jun Yang107209055257
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202237
2021766
20201,397
20192,195
20181,945
20171,995