{"title":"基于双扩展卡尔曼滤波的内部参数不一致锂离子电池组充电状态和健康状态估计","authors":"","doi":"10.1115/1.4062319","DOIUrl":null,"url":null,"abstract":"\n The internal battery parameters of the lithium-ion battery (LIB) energy storage system may be inconsistent due to different aging degrees during the operation, and the thermal effect can also threaten the safety of the system. In this paper, based on the second-order resistor-capacitor (2-RC) equivalent circuit model (ECM) and the dual extended Kalman filter (DEKF) algorithm, an electrical simulation model of a LIB pack with inconsistent parameters considering the thermal effect is established, in which state of charge (SOC) and state of health (SOH) are estimated using DEKF while the temperature is calculated by a thermal module. The simulation results show that the DEKF algorithm has a good effect on battery state and parameter estimation, with the root mean square error (RMSE) of voltage is lower than 0.01 V and SOC mean average error (MAE) is below 1.50 % while SOH error is 3.37 %. In addition, the thermal module can provide an accurate estimation on the inconsistent temperature rise of the battery pack, and the MAE between the model-calculated temperature and the experiment is no more than 6.60 %. This paper provides the basic data for the scale-up of the electrothermal co-simulation model of the LIB energy storage system.","PeriodicalId":15579,"journal":{"name":"Journal of Electrochemical Energy Conversion and Storage","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"State of charge and state of health estimation of lithium-ion battery packs with inconsistent internal parameters using dual extended Kalman filter\",\"authors\":\"\",\"doi\":\"10.1115/1.4062319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n The internal battery parameters of the lithium-ion battery (LIB) energy storage system may be inconsistent due to different aging degrees during the operation, and the thermal effect can also threaten the safety of the system. In this paper, based on the second-order resistor-capacitor (2-RC) equivalent circuit model (ECM) and the dual extended Kalman filter (DEKF) algorithm, an electrical simulation model of a LIB pack with inconsistent parameters considering the thermal effect is established, in which state of charge (SOC) and state of health (SOH) are estimated using DEKF while the temperature is calculated by a thermal module. The simulation results show that the DEKF algorithm has a good effect on battery state and parameter estimation, with the root mean square error (RMSE) of voltage is lower than 0.01 V and SOC mean average error (MAE) is below 1.50 % while SOH error is 3.37 %. In addition, the thermal module can provide an accurate estimation on the inconsistent temperature rise of the battery pack, and the MAE between the model-calculated temperature and the experiment is no more than 6.60 %. This paper provides the basic data for the scale-up of the electrothermal co-simulation model of the LIB energy storage system.\",\"PeriodicalId\":15579,\"journal\":{\"name\":\"Journal of Electrochemical Energy Conversion and Storage\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2023-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Electrochemical Energy Conversion and Storage\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4062319\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ELECTROCHEMISTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Electrochemical Energy Conversion and Storage","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4062319","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ELECTROCHEMISTRY","Score":null,"Total":0}
State of charge and state of health estimation of lithium-ion battery packs with inconsistent internal parameters using dual extended Kalman filter
The internal battery parameters of the lithium-ion battery (LIB) energy storage system may be inconsistent due to different aging degrees during the operation, and the thermal effect can also threaten the safety of the system. In this paper, based on the second-order resistor-capacitor (2-RC) equivalent circuit model (ECM) and the dual extended Kalman filter (DEKF) algorithm, an electrical simulation model of a LIB pack with inconsistent parameters considering the thermal effect is established, in which state of charge (SOC) and state of health (SOH) are estimated using DEKF while the temperature is calculated by a thermal module. The simulation results show that the DEKF algorithm has a good effect on battery state and parameter estimation, with the root mean square error (RMSE) of voltage is lower than 0.01 V and SOC mean average error (MAE) is below 1.50 % while SOH error is 3.37 %. In addition, the thermal module can provide an accurate estimation on the inconsistent temperature rise of the battery pack, and the MAE between the model-calculated temperature and the experiment is no more than 6.60 %. This paper provides the basic data for the scale-up of the electrothermal co-simulation model of the LIB energy storage system.
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.