KI-unterstutzte hybride Modellierung von Emissionen im hochtransienten Motorbetrieb

By (author) Tobias Gehra

Extent: 143 pages

Publisher: Logos Verlag Berlin

Subjects: Technical Sciences: Computer Science, Engineering, IT, & Math

Language: German

Paperback (Published)

(April 2025)

ISBN: 9783832559403

6.65 x 9.45 inches

Price: $67.00

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Synopsis
Contributing Authors

In der Entwicklung emissionsarmer Antriebstechnologien bieten batterieelektrische Fahrzeuge durch den hohen Gesamtwirkungsgrad und die lokal emissionsfreie Betriebsweise einen vielversprechenden Losungsansatz. Gleichzeitig stehen ihnen Herausforderungen wie die notwendige Ladeinfrastruktur und in der Regel geringere Reichweiten gegenuber. Hybridfahrzeuge konnen diese Nachteile kompensieren, indem sie die Vorteile elektrischer und konventioneller Antriebe vereinen. Um das Potenzial von Hybridantrieben auszuschopfen, sind Betriebsstrategien fur die optimale Lastverteilung notwendig. Diese lassen sich effizient in virtuellen Umgebungen entwickeln, was unter anderem eine prazise Abbildung des Fahrzeugs erfordert. Vor diesem Hintergrund setzt sich die vorliegende Arbeit mit der Modellierung von Emissionen im hochtransienten Motorbetrieb auseinander. Neben den physikalisch-phanomenologischen Ansatzen kommen auch Methoden des Maschinellen Lernens (ML) zum Einsatz, die besonders bei dynamischen Fahrzyklen uberzeugen. Durch die Kombination beider Modellansatze (Hybridmodelle) wird eine noch genauere Emissionsvorhersage ermoglicht. Die Ergebnisse zeigen, dass das parallele Hybridmodell zu einer deutlichen Prazisionssteigerung (ca. 25 % gegenuber dem reinen ML-Modell) fuhrt und durch eine effiziente Architektur fur Echtzeit-Anwendungen pradestiniert ist. Dies gilt nicht nur fur die vorliegende Problemstellung, sondern konnte sich auch auf andere Forschungsbereiche ausweiten lassen.

By (author) Tobias Gehra

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KI-unterstutzte hybride Modellierung von Emissionen im hochtransienten Motorbetrieb

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