山东电力技术2024，Vol.51Issue(11)：1-14,14.DOI:10.20097/j.cnki.issn1007-9904.2024.11.001
储能用磷酸铁锂电池充电方法评估
Evaluation of Charging Methods for Lithium Iron Phosphate(LFP)Batteries Used in Energy Storage
摘要
Abstract
In order to study the influence of different charging methods on the performance of lithium iron phosphate batteries for energy storage,a comprehensive evaluation model based on normal cloud clustering is proposed.Firstly,an electrochemical-side reaction lithium evolution-thermal coupling model is established to calculate the evaluation indexes of battery charging methods under low-temperature or uneven temperature conditions.Then,based on the impact of various indicators on battery performance,the weight of each indicator is determined using a combination weighting method.Furthermore,leveraging the strengths of the normal grey cloud clustering model in handling fuzzy and complex problems,the evaluation is divided into distinct levels.Finally,through the normal grey cloud evaluation strategy,the relative weight of the clustering coefficient ck=4 of the multi-stage constant current charging mode without lithium is 0,and the sum of the relative weights of ck=1 and ck=2 is 0.877,which can ensure the long-term stable operation of the energy storage battery at low temperature to the greatest extent.Compared with the existing lithium-ion battery charging method evaluation system,the lithium-ion battery charging evaluation method used in this paper takes into account factors such as low temperatures,uneven temperature distributions and lithium evolution at large magnification,which provides effective support for further research on the optimization charging strategy of lithium-ion batteries for energy storage.关键词
电化学模型/低温析锂/评价体系/正态灰云聚类/充电方法评估Key words
electrochemical model/low-temperature lithium precipitation/evaluation system/normal grey cloud clustering/evaluation of charging method分类
信息技术与安全科学引用本文复制引用
柴进,董志国,唐茂林,王溯,时玮..储能用磷酸铁锂电池充电方法评估[J].山东电力技术,2024,51(11):1-14,14.基金项目
国家能源集团科技项目"千万千瓦级全清洁能源安全自主可控智能管控系统研究与工程示范项目"(GJNY-22-108). Science and Technology Project of National Energy Group"Research and Engineering Demonstration Project on Safe,Autonomous and Controllable Intelligent Control System of Clean energy"(GJNY-22-108). （GJNY-22-108）
