Deep learning-assisted design for battery liquid cooling plate with bionic leaf structure considering non-uniform heat generation

A Zheng, H Gao, X Jia, Y Cai, X Yang, Q Zhu, H Jiang - Applied Energy, 2024 - Elsevier
Liquid cooling is a promising approach for battery thermal management due to its compact
construction and high heat transfer coefficient. However, the conventional liquid cooling …

Enabling cross-type full-knowledge transferable energy management for hybrid electric vehicles via deep transfer reinforcement learning

R Huang, H He, Q Su, M Härtl, M Jaensch - Energy, 2024 - Elsevier
Deep reinforcement learning (DRL) now represents an emerging artificial intelligence
technology to develop energy management strategies (EMSs) for hybrid electric vehicles …

Energy Management in Plug-In Hybrid Electric Vehicles: Preheating the Battery Packs in Low-Temperature Driving Scenarios

J Han, A Khalatbarisoltani, Y Yang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Plug-in hybrid electric vehicles (PHEVs) with large battery packs have significant
advantages in improving fuel efficiency and lowering harmful emissions. However, battery …

An improved soft actor-critic-based energy management strategy of heavy-duty hybrid electric vehicles with dual-engine system

D Zhang, W Sun, Y Zou, X Zhang, Y Zhang - Energy, 2024 - Elsevier
While deep reinforcement learning (DRL) based energy management strategies (EMSs)
have shown potential for optimizing energy utilization in recent years, challenges such as …

A CNN-SAM-LSTM hybrid neural network for multi-state estimation of lithium-ion batteries under dynamical operating conditions

C Qian, H Guan, B Xu, Q **a, B Sun, Y Ren, Z Wang - Energy, 2024 - Elsevier
Accurately estimating the state of charge (SOC), state of energy (SOE), and state of health
(SOH) online is a critical and urgent concern in the management of lithium-ion batteries for …

An energy management strategy for fuel cell hybrid electric vehicle based on HHO-BiLSTM-TCN-self attention speed prediction

M Pan, C Fu, X Cao, W Guan, L Liang, D Li, J Gu… - Energy, 2024 - Elsevier
This research aims to improve the performance and economics of fuel cell hybrid electric
vehicles (FCHEVs), validated and established by introducing an innovative energy …

A novel deep reinforcement learning-based predictive energy management for fuel cell buses integrating speed and passenger prediction

C Jia, H He, J Zhou, J Li, Z Wei, K Li, M Li - International Journal of …, 2025 - Elsevier
Energy management strategy (EMS) is crucial for the actual performance of fuel cell hybrid
electric buses (FCHEB) in complex traffic environments. However, conventional EMS usually …

Advantages of plug-in hybrid electric vertical take-off and landing aircraft with hydrogen energy storage

A Boretti - International Journal of Hydrogen Energy, 2024 - Elsevier
Electric vertical take-off and landing (eVTOL) aircraft are becoming more and more attractive
due to the improvements in electric road vehicles, and the mounting demand for new urban …

A unified benchmark for deep reinforcement learning-based energy management: Novel training ideas with the unweighted reward

J Chen, X Tang, K Yang - Energy, 2024 - Elsevier
Deep reinforcement learning stands as a powerful force in the realm of intelligent control for
hybrid power systems, yet some imperfections persist in the positive progression of learning …

A multi-objective configuration optimization method of passive hybrid energy storage system for pulse loads operating under very low temperatures

Y Song, Y Liu, X Zhou, X Huang, C Zhou, G ** - Journal of Energy Storage, 2024 - Elsevier
The lithium-ion battery energy storage system currently widely used faces a problem of rapid
degradation of electrical performance at very low temperatures (such as− 40° C), making it …