Battery Degradation Reduction in Flywheel–Battery Hybrid Energy Storage Using SSA‐Optimized Fuzzy‐PI Control

ABSTRACT Wind‐power fluctuations subject battery energy storage systems to frequent charge‐discharge cycling, thereby accelerating battery degradation and shortening battery lifetime. Hybrid flywheel‐battery energy storage systems provide an effective solution by allowing the flywheel to absorb high‐frequency power fluctuations while the battery supplies the low‐frequency energy component. This work develops a degradation‐aware Sparrow Search Algorithm (SSA) tuning framework for the fuzzy‐PI flywheel controller. The optimization combines DC‐bus voltage error with battery‐current variability, while structured parameter sweeps characterize the feasible parameter region. Compared with a regulation‐oriented high‐gain baseline, the proposed strategy maintains satisfactory DC‐bus voltage regulation, reduces mean battery current from 51.7 to 28.2 A, decreases battery ampere‐hour throughput by 46.1%, and lowers the rainflow damage index by 71%. Parameter‐space analysis further reduces the effective controller design problem from four dimensions to three under the tested conditions, yielding a practical and computationally efficient tuning framework for flywheel–battery hybrid energy storage systems.