Research on battery balancing based on fuzzy model predictive control

Abstract

To improve the performance of lithium-ion battery pack balancing system, a modular balancing system based on fuzzy adaptive model predictive control (FAMPC) was proposed. Firstly, a dual-layer balancing topology structure was composed of an improved buck-boost circuit and a flyback transformer. Secondly, using the state of charge (SOC) at different levels of battery remaining capacities as inputs for the fuzzy logic algorithm, the constraints on the balancing current were adjusted. Then, based on FAMPC balancing control method, the duty cycle of the switching transistor was directly used as the system input. Finally, simulation experiments were conducted without employing additional current control mechanisms to change the battery pack state. The results show that compared with traditional fuzzy control methods, the proposed system increase the balancing speed by approximately 24.51% under normal conditions and can further increase the balancing speed to 34.48% under extreme conditions with low battery SOC. The proposed system combines the stability provided by fuzzy algorithms with the rapid response of model predictive control algorithms, ensuring safer and more stable operation of the battery pack, which can provide reference for the research of enhancing battery pack performance.

Keywords

• energy storage technology; active balancing; model predictive control; fuzzy logic algorithm; self-adaption