[HTML][HTML] Energy efficiency of connected autonomous vehicles: A review

H Faghihian, A Sargolzaei - Electronics, 2023‏ - mdpi.com
Connected autonomous vehicles (CAVs) have emerged as a promising solution for
enhancing transportation efficiency. However, the increased adoption of CAVs is expected …

A comprehensive survey of the key technologies and challenges surrounding vehicular ad hoc networks

Z **a, J Wu, L Wu, Y Chen, J Yang, PS Yu - ACM Transactions on …, 2021‏ - dl.acm.org
Vehicular ad hoc networks (VANETs) and the services they support are an essential part of
intelligent transportation. Through physical technologies, applications, protocols, and …

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 …

Adaptive eco-cruising control for connected electric vehicles considering a dynamic preceding vehicle

Y Liang, H Dong, D Li, Z Song - Etransportation, 2024‏ - Elsevier
Energy consumption and driving safety of a vehicle are greatly influenced by the driving
behaviors of the vehicle in front (also termed the preceding vehicle). Inappropriate …

Knowledge implementation and transfer with an adaptive learning network for real-time power management of the plug-in hybrid vehicle

Q Zhou, D Zhao, B Shuai, Y Li… - IEEE Transactions on …, 2021‏ - ieeexplore.ieee.org
Essential decision-making tasks such as power management in future vehicles will benefit
from the development of artificial intelligence technology for safe and energy-efficient …

Transferable representation modelling for real-time energy management of the plug-in hybrid vehicle based on k-fold fuzzy learning and Gaussian process regression

Q Zhou, Y Li, D Zhao, J Li, H Williams, H Xu, F Yan - Applied energy, 2022‏ - Elsevier
Electric vehicles, including plug-in hybrids, are important for achieving net-zero emission
and will dominate road transportation in the future. Energy management, which optimizes …

Deep reinforcement learning-based energy-efficient decision-making for autonomous electric vehicle in dynamic traffic environments

J Wu, Z Song, C Lv - IEEE Transactions on Transportation …, 2023‏ - ieeexplore.ieee.org
Autonomous driving techniques are promising for improving the energy efficiency of
electrified vehicles (EVs) by adjusting driving decisions and optimizing energy requirements …

Integrated thermal and energy management of connected hybrid electric vehicles using deep reinforcement learning

H Zhang, B Chen, N Lei, B Li, R Li… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
The climate-adaptive mymargin energy management system (EMS) holds promising
potential for harnessing the concealed energy-saving capabilities of connected plug-in …

Hierarchical reinforcement learning based energy management strategy of plug-in hybrid electric vehicle for ecological car-following process

H Zhang, J Peng, H Dong, H Tan, F Ding - Applied Energy, 2023‏ - Elsevier
The economy-oriented automated hybrid eclectic vehicles (HEV) provide great potential to
save energy by optimizing both driving behaviors and power distribution. Recent advances …

Hierarchical control strategies for connected heavy-duty modular fuel cell vehicles via decentralized convex optimization

H Long, A Khalatbarisoltani, Y Yang… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Fuel cell vehicles (FCVs) are gaining popularity in heavy-duty transportation applications
because of their high efficiency, lack of local emissions, and short refueling time. Moreover …