Driving conditions-driven energy management strategies for hybrid electric vehicles: A review
Motivated by the concerns on transported fuel consumption and global air pollution,
industrial engineers and academic researchers have made many efforts to construct more …
industrial engineers and academic researchers have made many efforts to construct more …
Deep reinforcement learning in transportation research: A review
Applying and adapting deep reinforcement learning (DRL) to tackle transportation problems
is an emerging interdisciplinary field. While rapidly growing, a comprehensive and synthetic …
is an emerging interdisciplinary field. While rapidly growing, a comprehensive and synthetic …
Distributed deep reinforcement learning-based energy and emission management strategy for hybrid electric vehicles
Advanced algorithms can promote the development of energy management strategies
(EMSs) as a key technology in hybrid electric vehicles (HEVs). Reinforcement learning (RL) …
(EMSs) as a key technology in hybrid electric vehicles (HEVs). Reinforcement learning (RL) …
Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus
Hybrid electric vehicles offer an immediate solution for emissions reduction and fuel
displacement under the current technique level. Energy management strategies are critical …
displacement under the current technique level. Energy management strategies are critical …
Deep reinforcement learning-based energy management of hybrid battery systems in electric vehicles
In this paper, we propose an energy management strategy based on deep reinforcement
learning for a hybrid battery system in electric vehicles consisting of a high-energy and a …
learning for a hybrid battery system in electric vehicles consisting of a high-energy and a …
Battery health-aware and naturalistic data-driven energy management for hybrid electric bus based on TD3 deep reinforcement learning algorithm
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 …
hybrid power systems. This article proposes an energy management strategy based on …
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 …
fuel use in the transportation sector. Energy management strategy (EMS) is the core …
Incentive learning-based energy management for hybrid energy storage system in electric vehicles
Deep reinforcement learning has emerged as a promising candidate for online optimal
energy management of multi-energy storage vehicles. However, how to ensure the …
energy management of multi-energy storage vehicles. However, how to ensure the …
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 …
management strategies (EMSs) for hybrid vehicles have gained increasing attention in …
Energy management for a power-split hybrid electric bus via deep reinforcement learning with terrain information
Due to the high mileage and heavy load capabilities of hybrid commercial vehicles, energy
management becomes crucial in improving their fuel economy. In this paper, terrain …
management becomes crucial in improving their fuel economy. In this paper, terrain …