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 …

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 …

Deep reinforcement learning based energy management strategies for electrified vehicles: Recent advances and perspectives

H He, X Meng, Y Wang, A Khajepour, X An… - … and Sustainable Energy …, 2024 - Elsevier
Electrified vehicles provide an effective solution to address the unfavorable impacts of fossil
fuel use in the transportation sector. Energy management strategy (EMS) is the core …

Reinforcement learning-based energy management strategies of fuel cell hybrid vehicles with multi-objective control

C Zheng, D Zhang, Y Xiao, W Li - Journal of Power Sources, 2022 - Elsevier
Along with the rapid development of the artificial intelligence, learning-based energy
management strategies (EMSs) for hybrid vehicles have gained increasing attention in …

DQL energy management: An online-updated algorithm and its application in fix-line hybrid electric vehicle

R Zou, L Fan, Y Dong, S Zheng, C Hu - Energy, 2021 - Elsevier
With decades' development of energy management strategy in hybrid electric vehicle,
learning-based method has been deemed as a key solution for energy economy and real …

The application of machine learning-based energy management strategy in a multi-mode plug-in hybrid electric vehicle, part II: Deep deterministic policy gradient …

J Ruan, C Wu, Z Liang, K Liu, B Li, W Li, T Li - Energy, 2023 - Elsevier
Abstract Machine learning (ML)-based methods have attracted great attention in the multi-
objective optimization problems, which is the key challenge in the energy management …

Recent progress in learning algorithms applied in energy management of hybrid vehicles: A comprehensive review

D Xu, C Zheng, Y Cui, S Fu, N Kim, SW Cha - International Journal of …, 2023 - Springer
Hybrid vehicles (HVs) that equip at least two different energy sources have been proven to
be one of effective and promising solutions to mitigate the issues of energy crisis and …

Intelligent learning algorithm and intelligent transportation-based energy management strategies for hybrid electric vehicles: A review

J Gan, S Li, C Wei, L Deng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As one of the alternatives to conventional fuel vehicles, hybrid electric vehicles (HEV) offer
lower fuel consumption and fewer exhaust emissions. To improve the performance of the …

[HTML][HTML] Real-time self-adaptive Q-learning controller for energy management of conventional autonomous vehicles

M Fayyazi, M Abdoos, D Phan, M Golafrouz… - Expert Systems with …, 2023 - Elsevier
Reducing emissions and energy consumption of autonomous vehicles is critical in the
modern era. This paper presents an intelligent energy management system based on …

Cooperative power management for range extended electric vehicle based on internet of vehicles

Y Zhang, B Gao, J Jiang, C Liu, D Zhao, Q Zhou… - Energy, 2023 - Elsevier
The dramatic progress in internet of vehicles (IoVs) inspires further development in
electrified transportation, and abundant information exchanged in IoVs can be infused into …