A review of reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution

AH Ganesh, B Xu - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The impact of internal combustion engine-powered automobiles on climate change due to
emissions and the depletion of fossil fuels has contributed to the progress of electrified …

[HTML][HTML] Applications of reinforcement learning in energy systems

ATD Perera, P Kamalaruban - Renewable and Sustainable Energy …, 2021 - Elsevier
Energy systems undergo major transitions to facilitate the large-scale penetration of
renewable energy technologies and improve efficiencies, leading to the integration of many …

Fuel cell electric vehicles—A brief review of current topologies and energy management strategies

IS Sorlei, N Bizon, P Thounthong, M Varlam… - Energies, 2021 - mdpi.com
With the development of technologies in recent decades and the imposition of international
standards to reduce greenhouse gas emissions, car manufacturers have turned their …

Driving conditions-driven energy management strategies for hybrid electric vehicles: A review

T Liu, W Tan, X Tang, J Zhang, Y Xing, D Cao - Renewable and Sustainable …, 2021 - Elsevier
Motivated by the concerns on transported fuel consumption and global air pollution,
industrial engineers and academic researchers have made many efforts to construct more …

[HTML][HTML] Demand side management of electric vehicles in smart grids: A survey on strategies, challenges, modeling, and optimization

S Mohanty, S Panda, SM Parida, PK Rout, BK Sahu… - Energy Reports, 2022 - Elsevier
The shift of transportation technology from internal combustion engine (ICE) based vehicles
to electric vehicles (EVs) in recent times due to their lower emissions, fuel costs, and greater …

Longevity-conscious energy management strategy of fuel cell hybrid electric Vehicle Based on deep reinforcement learning

X Tang, H Zhou, F Wang, W Wang, X Lin - Energy, 2022 - Elsevier
Deep reinforcement learning-based energy management strategy play an essential role in
improving fuel economy and extending fuel cell lifetime for fuel cell hybrid electric vehicles …

Reinforcement learning for demand response: A review of algorithms and modeling techniques

JR Vázquez-Canteli, Z Nagy - Applied energy, 2019 - Elsevier
Buildings account for about 40% of the global energy consumption. Renewable energy
resources are one possibility to mitigate the dependence of residential buildings on the …

Optimization of energy management system for fuel-cell hybrid electric vehicles: Issues and recommendations

N Sulaiman, MA Hannan, A Mohamed, PJ Ker… - Applied energy, 2018 - Elsevier
Hybrid electric vehicle technologies emerge mainly because of the instability in fossil fuel
prices, resources and the terrible impact of global warming. As most transport systems use …

[HTML][HTML] Towards a future electric ferry using optimisation-based power management strategy in fuel cell and battery vehicle application—A review

M Cha, H Enshaei, H Nguyen… - … and Sustainable Energy …, 2023 - Elsevier
The growing need to alleviate the environmental impact of fossil fuels demands further
technical growth in fuel cell hybrid electric vehicles (FCHEVs). Due to the dynamic nature of …

Reinforcement learning based energy management systems and hydrogen refuelling stations for fuel cell electric vehicles: An overview

R Venkatasatish, C Dhanamjayulu - International Journal of Hydrogen …, 2022 - Elsevier
This paper examines the current state of the art of hydrogen refuelling stations-based
production and storage systems for fuel cell hybrid electric vehicles (FCHEV). Nowadays …