Research on Multi-stage Battery Equalization Based on Fuzzy Collaborative Control and Its Dynamic Performance Optimization

WU Jinbo; GONG Yusheng; HUANG Jiyuan; ZHU Junfei

doi:10.13296/j.1001-1609.hva.2025.11.012

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Research on Multi-stage Battery Equalization Based on Fuzzy Collaborative Control and Its Dynamic Performance Optimization

Parameter Optimization Design | 更新时间：2025-11-04

- Research on Multi-stage Battery Equalization Based on Fuzzy Collaborative Control and Its Dynamic Performance Optimization
- High Voltage Apparatus Vol. 61, Issue 11, Pages: 129-137(2025)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2025.11.012
  CLC：
- Received：20 May 2025，
  
  Revised：2025-08-12，
  
  Published：16 November 2025
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WU Jinbo, GONG Yusheng, HUANG Jiyuan, et al. Research on Multi-stage Battery Equalization Based on Fuzzy Collaborative Control and Its Dynamic Performance Optimization[J]. High voltage apparatus, 2025, 61(11): 129-137.
DOI：

WU Jinbo, GONG Yusheng, HUANG Jiyuan, et al. Research on Multi-stage Battery Equalization Based on Fuzzy Collaborative Control and Its Dynamic Performance Optimization[J]. High voltage apparatus, 2025, 61(11): 129-137. DOI： 10.13296/j.1001-1609.hva.2025.11.012.

摘要

针对串联电池组固有参数差异导致的模组间能量状态（

SOC

）严重不一致问题，文中提出一种基于模糊协同控制的三级电池均衡策略及其动态效能优化方法，即通过整合电感耦合机制构建高效双向能量传输路径，并结合模糊规则实现半导体场效应晶体管（MOSFET）开关频率的智能决策，协同优化能量动态调度。首先构建

SOC

驱动的单体级、模组级及系统级三级均衡框架，利用大功率电感实现电荷的跨层级时空协同分配；其次应用模糊逻辑动态调控MOSFET驱动信号占空比，自适应优化均衡电流幅值，有效克服传统PID控制在强非线性、变工况下的响应滞后和振荡问题。仿真结果表明：在静置、NEDC及UDDS 3类典型工况下，均衡模型平均耗时1 203 s，

SOC

离散度由初始22%降至1%以内。文中通过双层电感拓扑与模糊算法的协同优化，为高动态场景下的电池能量高效鲁棒协调提供了创新解决方案。

Abstract

As for the issue of severe inconsistency in the State of Charge（

SOC

）between modules due to inherent parameter differences in series-connected battery packs，in this paper a three-level battery balancing strategy based on fuzzy cooperative control and its dynamic efficiency optimization method are proposed，namely，an efficient bidirectional energy transmission path is constructed by integrating inductive coupling mechanisms，and the fuzzy rules is combined to achieve intelligent decision-making on the switching frequency of MOSFETs，thereby collaboratively optimizing dynamic energy scheduling. First，such

SOC

-driven three-level balancing framework as the cell level， module level and system level is constructed.The high-p

ower inductors are used to achieve cross-level temporal and spatial collaborative distribution of charges. Then，fuzzy logic is applied to dynamically adjust the duty cycle of MOSFET drive signals and adaptively optimize the amplitude of the balancing current，which effectively overcomes the problems of response lag and oscillation in traditional PID control under strong nonlinearity and variable working conditions. Simulation results show that under such three typical working conditions as static，NEDC，and UDDS conditions，the average time consumption of the balancing model is 1 203 seconds，and the

SOC

dispersion is reduced from the initial 22% to within1%. This paper，through the collaborative optimization of the double-layer inductor topology and fuzzy algorithm，can provide an innovative solution for efficient and robust coordination of battery energy in high-dynamic scenarios.

关键词

Keywords

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