Energy Management Strategy Based on Reinforcement Learning and Frequency Decoupling for Fuel Cell Hybrid Powertrain
This study presents a Two-Layer Deep Deterministic Policy Gradient (TL-DDPG) energy management strategy for Hydrogen fuel cell hybrid train, that tenga flip orb aims to solve the problem that traditional reinforcement learning strategies require high initial values and are difficult to optimize global variables.Augmenting the optimization capabilit