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

Beschreibung

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.

Autor*in

Stefan Scheubner

Themen in »Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models«

Elektromobilität Vorhersagen Algorithmen Fahrzeugtechnik Energiemanagement E-Mobility Forecasting Algorithms Vehicle Technology Energy Management

Stimmen zu »Stochastic Range Estimation Algorithms for Electric Vehicles using Data-Driven Learning Models«

Details

Link teilen