现代电子技术2026，Vol.49Issue(12)：23-30,8.DOI:10.16652/j.issn.1004-373X.2026.12.004
基于DBO-BP神经网络的锂电池双层均衡控制研究
Research on double-layer equalization control of lithium batteries based on DBO-BP neural network
摘要
Abstract
In allusion to the issues of slow balancing speed and low efficiency in traditional single-layer balancing topologies,a dual-layer balancing topology is proposed.At the bottom layer of the topology,an improved Buck-Boost circuit is adopted for equalization,while a flyback transformer circuit is applied at the top layer.This structure can optimize the energy transmission path and realize rapid equalization between any single cell and any battery pack.The dung beetle optimization(DBO)algorithm is used to optimize the traditional BP neural network,accelerating the convergence speed of the neural network and global optimization capability.The maximum error of SOC estimation is reduced to 0.49%,which effectively improves the accuracy of SOC estimation.The intra-group extreme range method and the inter-group mean difference comparison method are used in the equalization control strategy to simultaneously realize the equalization control.A simulation model of nine series-connected lithium-ion batteries is built in Matlab/Simulink.Comparative simulations are conducted between the traditional single-layer equalization topology and the proposed double-layer equalization topology under both charging and discharging equalization modes.The experimental results show that the proposed dual-layer equalization method can effectively shorten the equalization time and improve the equalization efficiency.关键词
串联锂电池组/双层均衡/改进Buck-Boost电路/反激式变压器/BP神经网络/蜣螂优化算法/均衡控制策略Key words
series-connected lithium battery pack/double-layer equalization/improved Buck-Boost circuit/flyback transformer/BP neural network/dung beetle optimization algorithm/equalization control strategy分类
信息技术与安全科学引用本文复制引用
严梓宁,魏业文,周宇,谌勇,程逸飞..基于DBO-BP神经网络的锂电池双层均衡控制研究[J].现代电子技术,2026,49(12):23-30,8.基金项目
国家自然科学基金项目(52407118) （52407118）
