Optimal Power Split Control for State of Charge Balancing in Battery Systems With Integrated Spatial Thermal Analysis and Aging Estimation

This paper proposes an optimal control strategy for SOC balancing and introduces a framework for analyzing the spatial temperature distribution in a multi-pack battery energy storage system (BESS) composed of multiple battery modules. While various control techniques exist to distribute power among parallel-connected battery systems, their influence on the spatial temperature distribution within their modules is often neglected, despite temperature being a critical factor accelerating battery health degradation. To bridge this research gap, this framework integrates a 1D thermal simulation and state-of-health (SoH) estimation with power split control strategies. To showcase the application of this framework, a comparative study of two power-sharing methods is conducted: (i) Model Predictive Control (MPC) based State of Charge (SoC) balancing, and (ii) Rule-Based Control (RBC) strategies, highlighting their impact on temperature distribution and battery aging. Results show that MPC maintains a more uniform temperature profile, limiting peak temperatures to 300 K and minimizing SoH degradation, whereas RBC results in higher peak temperatures (314 K) and accelerated aging. In summary, this framework primarily intends to: (i) Enable researchers to further develop health-aware power-sharing strategies for BESS. (ii) Equip BESS operators with detailed spatial temperature insights to optimize power management and cooling systems.