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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 & 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.


Papers
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Journal ArticleDOI
TL;DR: In this article, the specific energy absorbed during axial collapse of a variety of graphite, Kevlar and glass fiber composite tubes was determined, provided that the correct trigger mechanism was used to initiate the failure.
Abstract: The specific energy absorbed during the axial collapse of a variety of graphite, Kevlar and glass fiber composite tubes was determined. Although structural collapse occurred by a fracture failure mode, the specific energy absorption was higher than that of high strength metal tubes which col lapsed by buckling, over a wide range of tube geometries (t/D ratios), provided that the correct trigger mechanism was used to initiate the failure. Little change in the specific energy absorption was observed over a wide range of compression rates or with temperature changes below 20°C; above 20°C the effect of temperature varied with the resin employed. Collapse occurred initially by interlamellar shear followed by fiber fracture. The results were correlated on the basis of the specific interlamellar shear stress which permitted the energy absorption values for a variety of materials to be compared.

337 citations

Journal ArticleDOI
TL;DR: A modified pulse sequence is proposed which uses the phase information from an additional spin echo to correct for patient motion, and application is demonstrated for a human brain study, which greatly improves the quantification of diffusion values from regions of brain tissue.

336 citations

Journal ArticleDOI
TL;DR: In this paper, a tandem differential mobility analyzer (DMA) is employed to measure the effective density, mass per unit mobility volume, of diesel exhaust particulate matter (PM), with slight deviations suggestive of more compact structures noted for particles at the small end of the size distribution.

336 citations

Proceedings ArticleDOI
05 Oct 1997
TL;DR: The analysis and design of current regulators for multi-phase AC loads is presented using complex vector notation and several ways of improving its performance are suggested and investigated.
Abstract: The analysis and design of current regulators for multiphase AC loads in AC machines is presented using complex vector notation. The use of complex vector notation provides a way of comparing the performance of controller topologies through their complex vector root locus and complex vector frequency-response functions. Limitations in the performance of the synchronous frame proportional plus integral current regulator are outlined and several ways of improving its performance are suggested and investigated.

335 citations

Journal ArticleDOI
TL;DR: This paper proposes a control strategy of finite-control-set model predictive torque control with a deadbeat (DB) solution for permanent-magnet synchronous motor drives that relieves the big calculation effort of the traditional FCS-MPTC method.
Abstract: This paper proposes a control strategy of finite-control-set model predictive torque control (FCS-MPTC) with a deadbeat (DB) solution for permanent-magnet synchronous motor drives. By using a DB solution, the process of selection of the best switching vector is optimized. The predicted DB voltage sector consisting of the desired voltage vector (VV) avoids the complete enumeration for testing all feasible VVs, which relieves the big calculation effort of the traditional FCS-MPTC method. The proposed system is experimentally carried out both in the steady state and in the transient state.

333 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