Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models

This work aims at improving the energy consumption forecast of electric vehicles by enhancing the prediction with a notion of uncertainty. The algorithm itself learns from driver and traffic data in a training set to generate accurate, driver-individual energy consumption forecasts.

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Detalles Bibliográficos
Autor principal:	Scheubner, Stefan (auth)
Formato:	Electrónico Capítulo de libro
Lenguaje:	inglés
Publicado:	Karlsruhe KIT Scientific Publishing 2022
Colección:	Karlsruher Schriftenreihe Fahrzeugsystemtechnik
Materias:	Mechanical engineering & materials Elektromobilität Vorhersagen Algorithmen Fahrzeugtechnik Energiemanagement E-Mobility Forecasting Algorithms Vehicle Technology Energy Management
Acceso en línea:	DOAB: download the publication DOAB: description of the publication
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models por Scheubner, Stefan

Publicado 2022

OAPEN Library: download the publication
OAPEN Library: description of the publication

Electrónico Capítulo de libro

Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models

Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models por Scheubner, Stefan

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