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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 …
Запазване Позоваване С позовавания в 42 Сродни статии Всички 6 версии

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

T Liu, W Tan, X Tang, J Zhang, Y **ng, 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 …
Запазване Позоваване С позовавания в 137 Сродни статии Всички 4 версии

Cooperative energy management and eco-driving of plug-in hybrid electric vehicle via multi-agent reinforcement learning

Y Wang, Y Wu, Y Tang, Q Li, H He - Applied Energy, 2023 - Elsevier
The advanced cruise control system has expanded the energy-saving potential of the hybrid
electric vehicle (HEV). Despite this, most energy-saving researches for HEV either only …
Запазване Позоваване С позовавания в 90 Сродни статии Всички 7 версии

Deep reinforcement learning for multi-objective optimization in BIM-based green building design

Y Pan, Y Shen, J Qin, L Zhang - Automation in Construction, 2024 - Elsevier
For green building design, this paper proposes a multi-objective optimization (MOO)
framework to properly adjust design parameters using a deep reinforcement learning (DRL) …
Запазване Позоваване С позовавания в 18 Сродни статии

Distributed deep reinforcement learning-based energy and emission management strategy for hybrid electric vehicles

X Tang, J Chen, T Liu, Y Qin… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Advanced algorithms can promote the development of energy management strategies
(EMSs) as a key technology in hybrid electric vehicles (HEVs). Reinforcement learning (RL) …
Запазване Позоваване С позовавания в 134 Сродни статии Всички 4 версии

Battery health-aware and naturalistic data-driven energy management for hybrid electric bus based on TD3 deep reinforcement learning algorithm

R Huang, H He, X Zhao, Y Wang, M Li - Applied Energy, 2022 - Elsevier
Energy management is critical to reduce energy consumption and extend the service life of
hybrid power systems. This article proposes an energy management strategy based on …
Запазване Позоваване С позовавания в 91 Сродни статии Всички 8 версии

Towards a fossil-free urban transport system: An intelligent cross-type transferable energy management framework based on deep transfer reinforcement learning

R Huang, H He, Q Su - Applied Energy, 2024 - Elsevier
Deep reinforcement learning (DRL) is now a research focus for the energy management of
fuel cell vehicles (FCVs) to improve hydrogen utilization efficiency. However, since DRL …
Запазване Позоваване С позовавания в 19 Сродни статии Всички 6 версии

Double deep reinforcement learning-based energy management for a parallel hybrid electric vehicle with engine start–stop strategy

X Tang, J Chen, H Pu, T Liu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Committed to optimizing the fuel economy of hybrid electric vehicles (HEVs), improving the
working conditions of the engine, and promoting research on deep reinforcement learning …
Запазване Позоваване С позовавания в 118 Сродни статии Всички 2 версии

Longevity-aware energy management for fuel cell hybrid electric bus based on a novel proximal policy optimization deep reinforcement learning framework

R Huang, H He, X Zhao, M Gao - Journal of Power Sources, 2023 - Elsevier
With the prosperity of artificial intelligence and new energy vehicles, energy-saving
technologies for zero-emission fuel cell hybrid electric vehicles through high-efficient deep …
Запазване Позоваване С позовавания в 52 Сродни статии Всички 4 версии
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Multi-agent deep reinforcement learning based demand response for discrete manufacturing systems energy management

R Lu, YC Li, Y Li, J Jiang, Y Ding - Applied Energy, 2020 - Elsevier
With advances in smart grid technologies, demand response has played a major role in
improving the reliability of grids and reduce the cost for customers. Implementing the …
Запазване Позоваване С позовавания в 153 Сродни статии Всички 6 версии