Editorial
Research on Active Equalization of Energy Storage Lithium Batteries under a Modular Layered Architecture for Smart Grid Applications
@ARTICLE{10.4108/ew.11711, author={Qingdong Luo and Xiyuan Wan and Qiangwei Liu and Jingjing Lou and Zhikang Jin and Chaoqun Jin and Pengfei Zhen}, title={Research on Active Equalization of Energy Storage Lithium Batteries under a Modular Layered Architecture for Smart Grid Applications}, journal={EAI Endorsed Transactions on Energy Web}, volume={13}, number={1}, publisher={EAI}, journal_a={EW}, year={2026}, month={5}, keywords={Energy storage lithium battery, State of charge (SOC), Active equalization, Hierarchical equalization circuit, Fuzzy control}, doi={10.4108/ew.11711} }- Qingdong Luo
Xiyuan Wan
Qiangwei Liu
Jingjing Lou
Zhikang Jin
Chaoqun Jin
Pengfei Zhen
Year: 2026
Research on Active Equalization of Energy Storage Lithium Batteries under a Modular Layered Architecture for Smart Grid Applications
EW
EAI
DOI: 10.4108/ew.11711
Abstract
INTRODUCTION: In smart grid applications, energy storage systems (ESS) are critical for balancing power supply and demand, but they often suffer from performance degradation due to State of Charge (SOC) inconsistencies in series-configured lithium battery packs. These disparities can compromise grid stability and battery lifespan. OBJECTIVES: This study proposes an active equalization method based on a novel modular layered architecture for ESS in smart grids. The core innovation lies in the synergistic combination of a hierarchical bidirectional Buck-Boost topology and a multivariable fusion fuzzy logic control strategy, aiming to enhance battery consistency, efficiency, and reliability for grid support. METHODS: A hierarchical BUCK-BOOST-based circuit is designed to enable bidirectional energy transfer, incorporating a multivariable fuzzy controller for real-time regulation of balancing currents. This approach facilitates cooperative equalization within and between battery groups, optimizing energy flow. RESULTS: Simulations based on an eight-cell model in Matlab/Simulink demonstrate that the proposed hierarchical topology reduces equalization time by 11.53% compared to the conventional single-layer topology. Furthermore, with the proposed multivariable fusion fuzzy logic control algorithm, the equalization time is further reduced by 26%, significantly improving both the equalization speed and adaptability to dynamic grid conditions. CONCLUSION: The proposed strategy effectively mitigates battery inconsistencies, enhancing the overall performance and safety of energy storage systems in practical applications. It provides a reliable technical approach for battery management in smart grids.
