[HTML][HTML] Energy Management Strategy Based on Reinforcement Learning and Frequency Decoupling for Fuel Cell Hybrid Powertrain

H Li, J Kang, C Li - Energies, 2024 - mdpi.com
This study presents a Two-Layer Deep Deterministic Policy Gradient (TL-DDPG) energy
management strategy for Hydrogen fuel cell hybrid train, that aims to solve the problem that …

Energy Management Strategy Based on Reinforcement Learning and Frequency Decoupling for Fuel Cell Hybrid Powertrain

H Li, J Kang, C Li - Energies, 2024 - ideas.repec.org
This study presents a Two-Layer Deep Deterministic Policy Gradient (TL-DDPG) energy
management strategy for Hydrogen fuel cell hybrid train, that aims to solve the problem that …

Energy Management Strategy Based on Reinforcement Learning and Frequency Decoupling for Fuel Cell Hybrid Powertrain.

H Li, J Kang, C Li - Energies (19961073), 2024 - search.ebscohost.com
This study presents a Two-Layer Deep Deterministic Policy Gradient (TL-DDPG) energy
management strategy for Hydrogen fuel cell hybrid train, that aims to solve the problem that …

Energy Management Strategy Based on Reinforcement Learning and Frequency Decoupling for Fuel Cell Hybrid Powertrain

H Li, J Kang, C Li - 2024 - h2knowledgecentre.com
This study presents a Two-Layer Deep Deterministic Policy Gradient (TL-DDPG) energy
management strategy for Hydrogen fuel cell hybrid train, that aims to solve the problem that …

Energy Management Strategy Based on Reinforcement Learning and Frequency Decoupling for Fuel Cell Hybrid Powertrain

H Li, J Kang, C Li - Energies, 2024 - econpapers.repec.org
This study presents a Two-Layer Deep Deterministic Policy Gradient (TL-DDPG) energy
management strategy for Hydrogen fuel cell hybrid train, that aims to solve the problem that …