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Safe and Efficient Control: A Subgraph-Augmented Hierarchical Reinforcement Learning Framework for Dynamically Reconfigurable Battery Systems

Dynamically Reconfigurable Battery (DRB) systems employ power electronic switches to create dynamic topologies. They enable effective management of cell difference through real-time adjustment of cell connections. However, existing DRB control methods struggle to learn effective strategies due to sp