储能科学与技术2025，Vol.14Issue(7)：2662-2674,13.DOI:10.19799/j.cnki.2095-4239.2025.0072
基于模糊推理的储能系统锂离子电池模组热扩散概率评估方法
Fuzzy reasoning-based evaluation of the thermal diffusion probability of lithium-ion battery modules for energy storage systems
摘要
Abstract
Lithium-ion battery modules(LIBMs)are currently the most widely used battery components in energy storage systems.Thermal runaway events can significantly compromise the reliable operation of an energy storage system.Existing models for the qualitative analysis of thermal diffusion cannot be directly used to evaluate the thermal diffusion probability of LIBMs quantitatively under time-varying operation conditions.To overcome this problem,a fuzzy reasoning-based method for evaluating the thermal diffusion probability of LIBMs is proposed in this work.The study first built a thermal diffusion simulation model of LIBMs on the COMSOL platform.This model was used to analyze the effects of various heating modes,LIBM arrangement configurations,and state of charge(SOC)on LIBMs and to investigate the mechanisms of thermal diffusion in LIBMs.Subsequently,a fuzzy reasoning system was constructed based on the simulation test data.The cell temperature,inter-cell distance,and ambient temperature of the lithium-ion battery were taken as inputs,and the LIBM thermal runaway probability was the output.To improve the accuracy of the evaluation results,the improved dung beetle optimizer(IDBO)was used to optimize the membership function parameters in the fuzzy reasoning system.The results revealed that reducing the contact area between cells in an LIBM effectively mitigated thermal diffusion;additionally,slow heating of the LIBM resulted in a higher thermal runaway temperature for the last cell in the module to experience thermal runaway.The Pearson correlation coefficient of the thermal diffusion probability evaluation results obtained by the proposed method was higher compared with that of the traditional dung beetle algorithm,particle swarm algorithm,and sparrow search algorithm by 0.076,0.041,and 0.047 respectively.The high coefficient provides a more reasonable reference basis for the risk warning of LIBM thermal diffusion in energy storage systems in engineering practice.关键词
储能系统/锂离子电池模组/热扩散概率/模糊推理/改进蜣螂优化算法Key words
energy storage system/lithium-ion battery module/thermal diffusion probability/fuzzy reasoning/improved dung beetle optimizer(IDBO)分类
信息技术与安全科学引用本文复制引用
胡力月,黄威,周云,周英强,邵常政,王柯..基于模糊推理的储能系统锂离子电池模组热扩散概率评估方法[J].储能科学与技术,2025,14(7):2662-2674,13.基金项目
国家电力投资集团有限公司科技项目(2024-HD-KYC004-CQGS-CQj),国家重点研发计划课题项目(2023YFA1011301). （2024-HD-KYC004-CQGS-CQj）
