电工技术学报2024，Vol.39Issue(13)：4204-4225,22.DOI:10.19595/j.cnki.1000-6753.tces.230684
电池储能系统均衡方法研究综述
A Review of Equalization Methods for Battery Energy Storage System
摘要
Abstract
Battery energy storage system(BESS)is characterized by a large number of cells,and in practice,even if the consistency of the initial performance of cells is guaranteed,the consistency difference will occur due to different use conditions and environments.In order to reduce the difference in consistency between the cells within a BESS,a reliable equalization method must be established to improve its energy utilization and safety. Through the analysis of the current research status of the review of BESS equalization methods,more scholars have organized the equalization topologies,which are limited to the topologies based on energy storage devices such as inductors and capacitors.There is less organization of topologies based on redundancy ideas,topologies based on battery pack reconfiguration,and modular topologies,which have developed more rapidly in recent years.At the same time,the equalization necessity of series and parallel battery pack,equalization variables and equalization control methods are less organized and reviewed.The article provides a systematic overview of research on equalization methods for BESS,with key contributions described below. For the study of equalization variables,multivariate equalization can show the consistency difference of cells from different perspectives,and it is expected to become a hot spot of equalization variable research in the future.Especially,temperature,high-precision SOC and voltage are jointly used as equalization variables,which can ensure the energy utilization of the BESS as well as its safety. For the study of equalization topology,first of all,inductive equalization can realize high-precision equalization,and capacitive equalization can realize fast equalization when the voltage difference of equalization objects is large.Therefore,combined with the characteristics of inductive and capacitive energy storage,the equalization topologies based on inductive-capacitive energy storage with simple structure and perfect function are expected to be the hotspot of equalization topology research in the future.In addition,the modular equalization topology based on inductive-capacitive energy storage is also a hot direction in the research of equalization topology for the large number of cells in the BESS. For the research of equalization control methods,intelligent equalization is expected to become the hotspot of equalization control research in the future.Intelligent equalization includes intelligent selection of equalization objects and intelligent design of equalization currents.Intelligent selection of equalization objects is reflected in the simultaneous selection of multiple adjacent cells with smaller consistency differences to form a battery group to participate in equalization at the same time,which improves the speed and efficiency of equalization on the basis of the existing hardware.The intelligence of equalization current design is reflected in the fact that the equalization current can be intelligently designed according to the consistency difference and the load current,avoiding under-equalization and over-equalization,and at the same time,improving the speed and efficiency of equalization. The analysis and review of the equalization methods for BESS in this article provide a systematic overview of the current state of research on equalization methods.Moreover,a reliable outlook on the direction of the development of new equalization methods for battery packs containing a large number of cells is presented.The review is conducive to innovations and breakthroughs in novel active equalization methods for future BESS.关键词
电池储能系统/均衡变量/均衡拓扑/均衡控制/综述Key words
Battery energy storage/equalization variables/equalization topologies/equalization control/review分类
信息技术与安全科学引用本文复制引用
郭向伟,王晨,钱伟,陈思哲..电池储能系统均衡方法研究综述[J].电工技术学报,2024,39(13):4204-4225,22.基金项目
国家自然科学基金项目(61973105)、河南省高校基本科研业务费(NSFRF210332,NSFRF230604)、河南省高校重点科研项目(23A470006)和河南省科技攻关项目(232102240078)资助. （61973105）
