Please use this identifier to cite or link to this item:
|Title:||Li-ion battery SOC estimation using EKF based on a model proposed by extreme learning machine||Authors:||Du, Jiani
|Issue Date:||2012||Abstract:||In this paper, a method for modeling and estimation of Li-ion battery state of charge (SOC) using extreme learning machine (ELM) and extended Kalman filter (EKF) is proposed. The Li-ion battery model from ELM, which is established by training the data from the battery block in MATLAB/Simulation, could describe the dynamics of Li-ion battery very well. And it has higher accuracy and needs less calculation than using the traditional neural networks. Moreover, the battery model and discrete SOC definition equation constitute state-space equations, and EKF is used to estimate the SOC of Li-ion battery. Comparing the actual SOC with the estimated SOC by simulation, it reveals that the method proposed in this paper has good performance on Li-ion battery SOC estimation.||URI:||https://hdl.handle.net/10356/98879
|DOI:||10.1109/ICIEA.2012.6360990||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||EEE Conference Papers|
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.