To address the issues of insufficient state observation accuracy and limited energy scheduling efficiency during the active equalization of lithium-ion battery packs, a hierarchical modular equalization control strategy based on an improved extended Kalman filter (EKF) is proposed. The system consists of an intra-module equalization network constructed from multiple improved Buck-Boost multi-path equalization circuits at the bottom layer, enabling direct energy transfer between adjacent and non-adjacent cells, and an inter-module equalization network formed by a bidirectional Flyback equalization circuit and a switch matrix at the top layer, facilitating energy exchange between modules and the entire battery pack. Taking the state of charge (SOC) estimated by the EKF as the equalization criterion, a fuzzy proportional-integral-derivative regulator is introduced to achieve hierarchical parallel coordinated control within and between modules, thereby improving the overall equalization efficiency of the system. To address the problem of increased observation errors caused by decreased sensitivity of the open-circuit voltage (OCV)-SOC curve in the plateau region, a plateau correction coefficient G is introduced into the EKF to adaptively adjust the observation gain, thereby enhancing SOC estimation accuracy. Experimental results show that the proposed equalization strategy achieves a maximum SOC estimation error of 2.9% and a root mean square error of 0.86%, which are 35.7% and 36.8% lower than those of the traditional EKF, respectively. Compared with the proportional-integral-derivative control strategy based on Buck-Boost and Flyback equalization circuits, the equalization time under static conditions is reduced by 37.1%, and under 1C charging and discharging conditions, it is reduced by 58.66% and 60%, respectively, with significantly improved dynamic response performance. To balance real-time performance and engineering feasibility, the Fata Morgana algorithm is employed to optimize the correction coefficient G offline and construct a lookup table. Online computation is achieved through table lookup on the TMS320F28335 platform, with a single control cycle time of 0.32 ms, accounting for only 3.2% of the 10 ms control cycle. The proposed strategy significantly enhances equalization efficiency while enhancing SOC estimation accuracy, providing a viable implementation path with engineering application value for the integrated measurement and control design of lithium-ion battery management systems.