储能科学与技术2024，Vol.13Issue(2)：652-668,17.DOI:10.19799/j.cnki.2095-4239.2023.0568
锂离子电池/超级电容器混合储能系统能量管理方法综述
Review of energy management methods for lithium-ion battery/supercapacitor hybrid energy storage systems
摘要
Abstract
Lithium-ion battery/supercapacitor hybrid energy storage system has become the most widely used hybrid energy storage system because of its good performance,low cost and strong versatility.Energy management method is one of the core technologies of hybrid energy storage systems,and it is also the main research focus at present.In order to systematically review the energy management methods of hybrid energy storage systems,this paper first introduces the topology structure,energy management architecture and power distribution control of lithium-ion battery/supercapacitor hybrid energy storage systems.Then,this paper divides the existing energy management methods of hybrid energy storage system into four categories:experience based,optimization based,working condition pattern recognition based and machine learning based,and the efficiency of each type of energy management methods is discussed respectively for regular and random conditions;the robustness and computational complexity of each method are also analyzed.Finally,the current energy management methods are summarized and the future research directions and development trends in this field are prospected.Comprehensive analysis shows that improving the prediction accuracy of stochastic load in the future,establishing a more accurate hybrid energy storage system model,and further improving the real-time performance of energy management methods through cloud collaboration will be the focus of future energy management research of hybrid energy storage systems.关键词
混合储能系统/能量管理/功率分配/锂离子电池/超级电容器Key words
hybrid energy storage system/energy management/power allocation/lithium-ion battery/super capacitor分类
信息技术与安全科学引用本文复制引用
宋元明,刘亚杰,金光,周星,黄旭程..锂离子电池/超级电容器混合储能系统能量管理方法综述[J].储能科学与技术,2024,13(2):652-668,17.基金项目
湖南省科技创新计划资助项目(2021RC2074),国家自然科学基金项目(71901210),中国博士后科学基金面上项目(2021MD703975). （2021RC2074）
