Abstract: Dynamic reconfigurable battery networks (DRBN) are typically composed of numerous batteries with various characteristics, connected in series and parallel through power electronic switches. To achieve balanced management of these batteries and ensure the safe and precise isolation of faulty ones within the network, it is essential to cooperatively control the topological connections between the batteries. Therefore, a deep analysis of the coupling relationships between battery units is crucial for network management. This paper combines the cut-set network analysis method from graph theory and the n-order Thevenin model of battery units to construct a state-space model for the DRBN, thereby coupling all battery units in the network. Additionally, considering the critical importance of battery state of charge (SOC) for the optimized operation of the network and energy management of the energy storage system, this paper proposes an integrated SOC estimation method based on the state-space model of the DRBN. To validate the effectiveness of the proposed method, through experiments and numerical simulations, this paper compares it with the widely adopted SOC estimation methods based on battery unit models from existing research, drawing a conclusive result.