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  • 标题:On-line Estimation Algorithms for Mathematical Model Parameters of Lithium Batteries
  • 本地全文:下载
  • 作者:Huan Chen ; Huan Chen ; Peng Li
  • 期刊名称:IOP Conference Series: Earth and Environmental Science
  • 印刷版ISSN:1755-1307
  • 电子版ISSN:1755-1315
  • 出版年度:2019
  • 卷号:237
  • 期号:6
  • 页码:062043
  • DOI:10.1088/1755-1315/237/6/062043
  • 出版社:IOP Publishing
  • 摘要:In the state model of potassium batteries, the discharge rate proportional coefficient and temperature proportional coefficient compensated by second-order fitting polynomial are proposed. The mathematical model is improved and the concrete steps to determine the above two coefficients are given. The parameter estimation technology of lithium battery observation model is studied. The algorithm and experimental results of parameter estimation of mathematical model based on the algorithm and sampling point Kalman filter algorithm are given. The experimental results show that the improved lithium battery model and parameter estimation method proposed in this paper can accurately describe the discharge characteristics of lithium battery. The online estimation algorithm of model parameters based on Kalman filter at sampling points can lay a good foundation for the embedded implementation of the subsequent estimation system.
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