[HTML][HTML] Review of optimal sizing and power management strategies for fuel cell/battery/super capacitor hybrid electric vehicles

AS Mohammed, SM Atnaw, AO Salau, JN Eneh - Energy Reports, 2023 - Elsevier
Energy management strategies and optimal power source sizing for fuel cell/battery/super
capacitor hybrid electric vehicles (HEVs) are critical for power splitting and cost-effective …

High robustness energy management strategy of hybrid electric vehicle based on improved soft actor-critic deep reinforcement learning

W Sun, Y Zou, X Zhang, N Guo, B Zhang, G Du - Energy, 2022 - Elsevier
As a hybrid electric vehicle (HEV) key control technology, intelligent energy management
strategies (EMSs) directly affect fuel consumption. Investigating the robustness of EMSs to …

Boosting the adoption of industrial energy efficiency measures through Industry 4.0 technologies to improve operational performance

ASMM Hasan, A Trianni - Journal of Cleaner Production, 2023 - Elsevier
Abstract Industry 4.0 (I4. 0) technologies and energy efficiency measures (EEMs) could
enhance the performance of manufacturing industries, but research on the role of I4. 0 on …

[HTML][HTML] Adaptive ECMS based on speed forecasting for the control of a heavy-duty fuel cell vehicle for real-world driving

M Piras, V De Bellis, E Malfi, R Novella… - Energy Conversion and …, 2023 - Elsevier
Aiming at reducing pollutant emissions, hydrogen and fuel cell hybrid electric vehicles
(FCVs) represent a promising technological solution. In this scenario, this paper proposes …

Intelligent learning algorithm and intelligent transportation-based energy management strategies for hybrid electric vehicles: A review

J Gan, S Li, C Wei, L Deng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As one of the alternatives to conventional fuel vehicles, hybrid electric vehicles (HEV) offer
lower fuel consumption and fewer exhaust emissions. To improve the performance of the …

Reinforcement learning-based energy management for hybrid power systems: state-of-the-art survey, review, and perspectives

X Tang, J Chen, Y Qin, T Liu, K Yang… - Chinese Journal of …, 2024 - Springer
The new energy vehicle plays a crucial role in green transportation, and the energy
management strategy of hybrid power systems is essential for ensuring energy-efficient …

[HTML][HTML] Incorporating speed forecasting and SOC planning into predictive ECMS for heavy-duty fuel cell vehicles

M Piras, V De Bellis, E Malfi, JM Desantes… - International Journal of …, 2024 - Elsevier
This study presents a novel approach specifically designed for real-world driving scenarios
of heavy-duty fuel cell vehicles, named P-ECMS. The P-ECMS addresses both charge …

[HTML][HTML] A multi-objective hierarchical deep reinforcement learning algorithm for connected and automated HEVs energy management

S Coskun, O Yazar, F Zhang, L Li, C Huang… - Control Engineering …, 2024 - Elsevier
Connected and autonomous vehicles have offered unprecedented opportunities to improve
fuel economy and reduce emissions of hybrid electric vehicle (HEV) in vehicular platoons. In …

Deep reinforcement learning for intelligent energy management systems of hybrid-electric powertrains: Recent advances, open issues, and prospects

Y Li, H He, A Khajepour, Y Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The hybrid-electric powertrain presents an immediate solution to energy and environmental
challenges encountered within the realm of transportation. Targeting the optimization of …

Optimal power-split of hybrid energy storage system using Pontryagin's minimum principle and deep reinforcement learning approach for electric vehicle application

P Nambisan, M Khanra - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
The battery supercapacitor hybrid energy storage system (HESS) based electric vehicles
(EVs) require an efficient online energy management system (EMS) to enhance the battery …