Adaptive equalization method of lithium battery module based on time-varying characteristics of voltage and SOC

Abstract

With the widespread adoption of batteries, effective battery management is of paramount importance. To enhance the balancing performance of lithium-ion battery systems, this paper proposes a fuzzy control balancing scheme. This scheme integrates Particle Swarm Optimization (PSO), optimizes the State of Charge (SOC) and voltage membership functions, and employs a hierarchical balancing strategy. First, the underlying balancing circuit utilizes buck-boost converters. Second, the fuzzy logic controller takes both the individual cell SOCs and real-time cell voltages as inputs to dynamically adjust the equalization current constraints. Third, the PSO-optimized membership functions are applied within the fuzzy controller, which directly employs the switch duty cycle as the system output. Finally, the charging and discharging states of the battery pack were varied, and simulation experiments were conducted. The results demonstrate that compared to traditional fuzzy control methods, the proposed system achieved significant improvements in equalization speed: approximately 33.7 % faster under static conditions, and 30.1 % and 22.3 % faster during charging and discharging states, respectively. This scheme effectively combines the stability of fuzzy algorithms with the robustness and generality of the PSO algorithm, ensuring safer and more stable battery pack operation. It thus provides a valuable reference for research aimed at enhancing battery pack performance.