An Interleaved Equalization Architecture with Self-Learning Fuzzy Logic Control for Series-Connected Battery Strings

This paper proposes an interleaved equalization architecture for series-connected lithium-ion battery strings, which can deliver energy from a battery module to the cells in the next adjacent battery module, resulting in an enhancement of the equalization current and efficiency. Particularly, the global equalization is achieved without the need of additional stage circuits to balance among modules, leading to a small size and low cost. A two-module equalizer based on resonant LC converter and buck converter with soft switching is implemented to verify the validity of the proposed interleaved architecture. Furthermore, a self-learning fuzzy logic control (SLFLC) algorithm is employed to online regulate the equalization period based on the voltage difference among cells and the cell voltage, not only greatly abbreviating the balancing time but also effectively preventing overequalization. The SLFLC has the outstanding advantages of high balancing precision, easy implementation, and strong robustness. Experimental results demonstrate that the proposed equalizer has good balancing performances with soft switching and high efficiency, and achieves zero-voltage gap among cells. Moreover, the proposed SLFLC algorithm abridges the total equalization time by about 27%, and reduces the equalization cycles by about 59% compared with the traditional control algorithm.