Zheng Liu, Yuan Qiu, Jin Feng, Shaohang Chen, Chunshan Yang
{"title":"A Simplified Fractional Order Modeling and Parameter Identification for Lithium-Ion Batteries","authors":"Zheng Liu, Yuan Qiu, Jin Feng, Shaohang Chen, Chunshan Yang","doi":"10.1115/1.4051567","DOIUrl":null,"url":null,"abstract":"\n With the widespread development of new energy, the study of power lithium-ion batteries (LIBs) has broad prospects and great academic significance. The model and parameters are two essential prerequisites for LIB state estimation, which are used to provide a guarantee for the secure and convenient handling of LIBs. To obtain the reliable model and parameters, a simplified fractional order equivalent circuit model (FO-ECM) with high precision is presented in this article. The dynamic external electrical characteristic of LIBs is represented by the one-order FO-ECM, and then, the FO-ECM parameters are identified by the combination of Grunwald–Letnikov (G-L) definition-based factional order numerical calculation and noise compensation-based forgetting factor recursive least squares (FFRLS) method. The simplified FO-ECM can better characterize the nonlinear dynamic behaviors of LIBs, and the G-L definition-based FO-FFRLS algorithm can maintain good accuracy in the parameter estimation process. The results show that the simplified FO-ECM can improve the modeling precision and parameter identification performance compared with the common integer-order ECM in different test cycles.","PeriodicalId":15579,"journal":{"name":"Journal of Electrochemical Energy Conversion and Storage","volume":" ","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2021-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Electrochemical Energy Conversion and Storage","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4051567","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ELECTROCHEMISTRY","Score":null,"Total":0}
引用次数: 7
Abstract
With the widespread development of new energy, the study of power lithium-ion batteries (LIBs) has broad prospects and great academic significance. The model and parameters are two essential prerequisites for LIB state estimation, which are used to provide a guarantee for the secure and convenient handling of LIBs. To obtain the reliable model and parameters, a simplified fractional order equivalent circuit model (FO-ECM) with high precision is presented in this article. The dynamic external electrical characteristic of LIBs is represented by the one-order FO-ECM, and then, the FO-ECM parameters are identified by the combination of Grunwald–Letnikov (G-L) definition-based factional order numerical calculation and noise compensation-based forgetting factor recursive least squares (FFRLS) method. The simplified FO-ECM can better characterize the nonlinear dynamic behaviors of LIBs, and the G-L definition-based FO-FFRLS algorithm can maintain good accuracy in the parameter estimation process. The results show that the simplified FO-ECM can improve the modeling precision and parameter identification performance compared with the common integer-order ECM in different test cycles.
期刊介绍:
The Journal of Electrochemical Energy Conversion and Storage focuses on processes, components, devices and systems that store and convert electrical and chemical energy. This journal publishes peer-reviewed archival scholarly articles, research papers, technical briefs, review articles, perspective articles, and special volumes. Specific areas of interest include electrochemical engineering, electrocatalysis, novel materials, analysis and design of components, devices, and systems, balance of plant, novel numerical and analytical simulations, advanced materials characterization, innovative material synthesis and manufacturing methods, thermal management, reliability, durability, and damage tolerance.