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[HTML][HTML] Review of optimal sizing and power management strategies for fuel cell/battery/super capacitor hybrid electric vehicles
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 …
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
As a hybrid electric vehicle (HEV) key control technology, intelligent energy management
strategies (EMSs) directly affect fuel consumption. Investigating the robustness of EMSs to …
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
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 …
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
Aiming at reducing pollutant emissions, hydrogen and fuel cell hybrid electric vehicles
(FCVs) represent a promising technological solution. In this scenario, this paper proposes …
(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
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 …
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
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 …
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
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 …
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
Connected and autonomous vehicles have offered unprecedented opportunities to improve
fuel economy and reduce emissions of hybrid electric vehicle (HEV) in vehicular platoons. In …
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
The hybrid-electric powertrain presents an immediate solution to energy and environmental
challenges encountered within the realm of transportation. Targeting the optimization of …
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
The battery supercapacitor hybrid energy storage system (HESS) based electric vehicles
(EVs) require an efficient online energy management system (EMS) to enhance the battery …
(EVs) require an efficient online energy management system (EMS) to enhance the battery …