Real-Time Robust and AdaptIve Learning in ElecTric VEhicles (RITE)
Forskningsprojekt , 2020 – 2021

This proposal is concerned with real-time learning in electric vehicles, focusing on modeling the energy consumption in realistic traffic conditions, e.g. taking into account the impact of weather, wind, temperature, logistics mission, etc. Due to limited battery capacity, energy consumption is very important for electric vehicles. Hence, planning and designing energy-aware navigation tools are of capital importance. Robust and adaptive learning algorithms are in the research focus to solve the above problems.

Deltagare

Morteza Haghir Chehreghani (kontakt)

Chalmers, Data- och informationsteknik, Data Science

Sebastien Gros

Chalmers, Elektroteknik, System- och reglerteknik

Balázs Adam Kulcsár

Chalmers, Elektroteknik, System- och reglerteknik

Balázs Varga

Chalmers, Elektroteknik, System- och reglerteknik

Finansiering

Chalmers

Finansierar Chalmers deltagande under 2020–2021

Chalmers AI-forskningscentrum (CHAIR)

Finansierar Chalmers deltagande under 2020–2021

Relaterade styrkeområden och infrastruktur

Transport

Styrkeområden

Publikationer

2022

Deep Q-learning: a robust control approach

Artikel i vetenskaplig tidskrift

Mer information

Senast uppdaterat

2021-05-21