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Alternative TitleApplication of dual extended Kalman filtering algorithm in the state-of-charge estimation of lithium-ion battery
王笑天; 杨志家; 王英男; 王忠锋
Source Publication仪器仪表学报
Indexed ByEI ; CSCD
EI Accession number20133816756958
Contribution Rank1
Funding Organization国家863计划(2012AA041701)资助项目
Keyword双卡尔曼滤波 荷电状态 锂离子电池 电池模型
Other AbstractThis paper proposes a dual extended Kalman filtering ( DEKF) algorithm for estimating the State-of-Charge ( SOC) of lithium-ion batteries on line. First of all, the state-space representation of the battery model is established based on Thevenin battery model and Kalman filtering algorithm. The least squares method and the DEKF algorithm are used to identify the battery model parameters,which improves the model accuracy and facilitates the battery model to well reflect the actual internal state of the battery, Moreover, the principle of using DEKF algorithm to estimate the inner SOC of the battery on line is introduced,and corresponding battery test experiments are designed. Experiment results demonstrate that under various operating conditions, the algorithm has relatively high accuracy and good environment adaptability when applied to evaluate SOC on line; and the maximum error is less than 4.5%. The DEKF algorithm is proved to have good convergence and robustness,and can efficiently solve the problems of inaccurate initial- value estimation and error accumulation.
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Cited Times:19[CSCD]   [CSCD Record]
Document Type期刊论文
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GB/T 7714
王笑天,杨志家,王英男,等. 双卡尔曼滤波算法在锂电池SOC估算中的应用[J]. 仪器仪表学报,2013,34(8):1732-1738.
APA 王笑天,杨志家,王英男,&王忠锋.(2013).双卡尔曼滤波算法在锂电池SOC估算中的应用.仪器仪表学报,34(8),1732-1738.
MLA 王笑天,et al."双卡尔曼滤波算法在锂电池SOC估算中的应用".仪器仪表学报 34.8(2013):1732-1738.
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