摘要
近年来,随着新能源汽车产业的发展,动力电池迎来大规模退役,为避免资源浪费,延长电池使用寿命,对动力电池梯次利用技术的研究具有重大现实意义。为此从梯次利用技术的现状出发,分析国内外梯次利用项目和相关政策,对梯次利用过程中的检测、筛选、重组和均衡技术以及电池梯次利用在多种储能场景下的应用进行综述,并对锂离子电池梯次利用中的性能检测做出重点总结。最后总结了梯次利用在电池状态评估和梯次电池筛选上的技术难点与未来的研究趋势,指出以卡尔曼滤波为代表的模型驱动方法和以人工神经网络为代表的数据驱动方法的有机结合,可以有效提高电池状态评估与分选的效率,是重要的研究趋势;提出针对不同的电池工况和不同的梯次利用场景应具有多样性的检测和分选方法,并应制订具体标准;对梯次利用的级别、标准化程度以及退役电池回收体系几个方面的研究给出了合理的建议。
In recent years,with the development of the new energy vehicle industry,the power battery has ushered in large-scale retirement.In order to avoid resource waste and prolong the service life of the battery,the research on the echelon utilization technology of the power battery has great practical significance.Therefore,starting from the current situation of echelon utilization technology,this paper analyzes the echelon utilization projects and relevant policies at home and abroad,reviews the detection,screening,reorganization and equalization technology in the process of echelon utilization,as well as the application of battery echelon utilization in a variety of energy storage scenarios,and summarizes the performance detection in the echelon utilization of lithium-ion batteries.Finally,it sums up the technical difficulties and future research trends of echelon utilization in battery condition assessment and echelon battery screening.It is pointed out that the organic combination of model driven method represented by Kalman filter and data-driven method represented by artificial neural network can effectively improve the efficiency of battery condition assessment and sorting,which is an important research trend.At the same time,the paper proposes that there should be diverse detection and sorting methods based on different battery working conditions and different echelon application scenarios,and specific standards should be formulated.It also provides reasonable suggestions for the research on echelon utilization level,standardization degree and retired battery recovery system.
作者
崔树辉
周贺
黄振兴
王凯
CUI Shuhui;ZHOU He;HUANG Zhenxing;WANG Kai(College of Electrical Engineering,Qingdao University,Qingdao,Shandong 266071,China;Weihai Innovation Research Institute,Qingdao University,Qingdao,Shandong 266071,China;Digatron(Qingdao)Electronic Co.,Ltd.,Qingdao,Shandong 266109,China;Qingdao Haier Laundry Eletric Appliances Co.,Ltd.,Qingdao,Shandong 266101,China;National and Local Joint Engineering Research Center for Intelligent Power Integration Technology of Electric Vehicles(Qingdao),Qingdao,Shandong 266071,China)
出处
《广东电力》
2023年第1期9-19,共11页
Guangdong Electric Power
基金
国家重点研发计划项目(2017YFB0102004-4)
山东省重点研发计划项目(ZR2020KF020)。
关键词
动力电池
梯次利用
状态评估
分选与重组
梯次储能系统
power battery
echelon utilization
state evaluation
sorting and recombination
echelon energy storage system
