A Unified Modeling Framework of Reconfigurable Battery Systems for Optimal Control

Journal article, 2026

Reconfigurable battery systems (RBSs) have emerged as a promising solution for improving fault tolerance, charge and thermal balance, overall energy delivery, etc. Achieving these benefits requires a control-oriented RBS model to support the formulation and solution of optimal control problems. However, existing modeling approaches often rely on oversimplified assumptions that overlook dynamic interactions among cells, limiting their ability to capture real-time operating behavior or detect cell-level faults under frequent reconfiguration. To address these limitations, we propose a unified modeling framework for RBSs that adapts to dynamic reconfiguration by introducing the concept of complete system configuration. This modeling framework accurately captures battery behaviors and their interactions during reconfiguration, while also yielding compact and explicit expressions for operational constraints. To further enhance computational efficiency and solution quality, the model equations are reformulated into linear constraints, enabling efficient optimization. The proposed framework is validated through case studies on both high-performance computing and industrial embedded platforms using different solvers, and their corresponding applicable system sizes and prediction horizons are identified. Simulation and experimental results demonstrate high simulation accuracy, convergence performance, and practical scalability. Overall, the proposed unified RBS modeling framework establishes a solid foundation for effectively formulating and efficiently solving optimal control problems for RBSs.