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 …

Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges …

P Dong, J Zhao, X Liu, J Wu, X Xu, Y Liu… - … and Sustainable Energy …, 2022 - Elsevier
The rapid development of intelligent and connected technologies is conducive to the
efficient energy utilization of hybrid electric vehicles (HEVs). However, most energy …

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 …

Multi-period, multi-timescale stochastic optimization model for simultaneous capacity investment and energy management decisions for hybrid Micro-Grids with green …

S Kim, Y Choi, J Park, D Adams, S Heo… - … and Sustainable Energy …, 2024 - Elsevier
Given the steep rises in renewable energy's proportion in the global energy mix expected
over several decades, a systematic way to plan the long-term deployment is needed. The …

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 …

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) …

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 …

Overview of energy harvesting and emission reduction technologies in hybrid electric vehicles

S Bai, C Liu - Renewable and Sustainable Energy Reviews, 2021 - Elsevier
Hybrid electric vehicles (HEVs) have been developed extensively thanks to the inherent
merits of both internal combustion engine vehicles (ICEVs) and battery electric vehicles …

Twin delayed deep deterministic policy gradient-based deep reinforcement learning for energy management of fuel cell vehicle integrating durability information of …

Y Zhang, C Zhang, R Fan, S Huang, Y Yang… - Energy Conversion and …, 2022 - Elsevier
Deep reinforcement learning (DRL)-based energy management strategy (EMS) is attractive
for fuel cell vehicle (FCV). Nevertheless, the fuel economy and lifespan durability of proton …

A novel energy management strategy of hybrid electric vehicle via an improved TD3 deep reinforcement learning

J Zhou, S Xue, Y Xue, Y Liao, J Liu, W Zhao - Energy, 2021 - Elsevier
The formulation of high-efficient energy management strategy (EMS) for hybrid electric
vehicles (HEVs) becomes the most crucial task owing to the variation of electrified …