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Kraftsensorlose Manipulator Kraftsteuerung zur Abtastung unbekannter, harter OberflächenDapper, Marcus. Unknown Date (has links) (PDF)
Universiẗat, Diss., 2003--Bonn.
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Analyse des stationären Folgeverhaltens von Pkw-Fahrzeugführern unter Berücksichtigung von Nässe und einhergehender SichtbehinderungFecher, Norbert. Unknown Date (has links) (PDF)
Darmstadt, Techn. Universiẗat, Diss., 2005.
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Analyse des stationären Folgeverhaltens von Pkw-Fahrzeugführen unter Berücksichtigung von Nässe und einer einhergehender SichtbehinderungFecher, Norbert January 2005 (has links) (PDF)
Zugl.: Darmstadt, Techn. Univ., Diss.
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Untersuchung stationärer Betriebsgröen des Drehstromasynchron-Linearmotors für Synchrongeschwindigkeiten unter 3m/sKleemann, Dietmar. Unknown Date (has links) (PDF)
Techn. Universiẗat, Diss., 2005--Berlin.
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Optimal Velocity and Power Split Control of Hybrid Electric VehiclesUebel, Stephan, Bäker, Bernard 03 March 2017 (has links) (PDF)
An assessment study of a novel approach is presented that combines discrete state-space Dynamic Programming and Pontryagin’s Maximum Principle for online optimal control of hybrid electric vehicles (HEV). In addition to electric energy storage and gear, kinetic energy and travel time are considered states in this paper. After presenting the corresponding model using a parallel HEV as an example, a benchmark method with Dynamic Programming is introduced which is used to show the solution quality of the novel approach. It is illustrated that the proposed method yields a close-to-optimal solution by solving the
optimal control problem over one hundred thousand times faster than the benchmark method. Finally, a potential online usage is assessed by comparing solution quality and calculation time with regard to the quantization of the state space.
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Optimal Velocity and Power Split Control of Hybrid Electric VehiclesUebel, Stephan, Bäker, Bernard 03 March 2017 (has links)
An assessment study of a novel approach is presented that combines discrete state-space Dynamic Programming and Pontryagin’s Maximum Principle for online optimal control of hybrid electric vehicles (HEV). In addition to electric energy storage and gear, kinetic energy and travel time are considered states in this paper. After presenting the corresponding model using a parallel HEV as an example, a benchmark method with Dynamic Programming is introduced which is used to show the solution quality of the novel approach. It is illustrated that the proposed method yields a close-to-optimal solution by solving the
optimal control problem over one hundred thousand times faster than the benchmark method. Finally, a potential online usage is assessed by comparing solution quality and calculation time with regard to the quantization of the state space.
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