{"title":"CEEMD-Fuzzy Control Energy Management of Hybrid Energy Storage Systems in Electric Vehicles","authors":"Yongpeng Shen;Junchao Xie;Ting He;Lei Yao;Yanqiu Xiao","doi":"10.1109/TEC.2023.3306804","DOIUrl":null,"url":null,"abstract":"To improve the performance of the energy storage system of electric vehicles, a complete ensemble empirical mode decomposition-fuzzy logic control energy management strategy is proposed to attenuate the aging of lithium-ion batteries caused by high-frequency power demand. Firstly, the electric vehicle power demand is decomposed into a finite number of intrinsic mode functions components, and each component is reconstructed into low-frequency or high-frequency components according to its permutation entropy. Then, the low-frequency and high-frequency components of electric vehicle power demand are allocated to lithium-ion batteries and ultracapacitors, respectively. Finally, fuzzy logic based closed loop controller is designed to maintain the state of charge of ultracapacitors at the desired level. Experiments under HWFET, UDDS, US06 and combined drive cycles are performed, and experimental results show that compared with single energy storage system and other state-of-the-art methods, the proposed strategy can effectively reduce the maximum discharge current of the lithium-ion batteries and maintenance the state of charge balance of the ultracapacitor.","PeriodicalId":13211,"journal":{"name":"IEEE Transactions on Energy Conversion","volume":"39 1","pages":"555-566"},"PeriodicalIF":5.0000,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Energy Conversion","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10225367/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
To improve the performance of the energy storage system of electric vehicles, a complete ensemble empirical mode decomposition-fuzzy logic control energy management strategy is proposed to attenuate the aging of lithium-ion batteries caused by high-frequency power demand. Firstly, the electric vehicle power demand is decomposed into a finite number of intrinsic mode functions components, and each component is reconstructed into low-frequency or high-frequency components according to its permutation entropy. Then, the low-frequency and high-frequency components of electric vehicle power demand are allocated to lithium-ion batteries and ultracapacitors, respectively. Finally, fuzzy logic based closed loop controller is designed to maintain the state of charge of ultracapacitors at the desired level. Experiments under HWFET, UDDS, US06 and combined drive cycles are performed, and experimental results show that compared with single energy storage system and other state-of-the-art methods, the proposed strategy can effectively reduce the maximum discharge current of the lithium-ion batteries and maintenance the state of charge balance of the ultracapacitor.
期刊介绍:
The IEEE Transactions on Energy Conversion includes in its venue the research, development, design, application, construction, installation, operation, analysis and control of electric power generating and energy storage equipment (along with conventional, cogeneration, nuclear, distributed or renewable sources, central station and grid connection). The scope also includes electromechanical energy conversion, electric machinery, devices, systems and facilities for the safe, reliable, and economic generation and utilization of electrical energy for general industrial, commercial, public, and domestic consumption of electrical energy.