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IET Power Electronics
Article . 2020 . Peer-reviewed
License: Wiley Online Library User Agreement
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Parameter identification of a lithium‐ion battery based on the improved recursive least square algorithm

Authors: Biying Ren; Chenxue Xie; Xiangdong Sun; Qi Zhang; Dan Yan;

Parameter identification of a lithium‐ion battery based on the improved recursive least square algorithm

Abstract

Accurate parameter identification of a lithium‐ion battery is a critical basis in the battery management systems. Based on the analysis of the second‐order RC equivalent circuit model, the parameter identification process using the recursive least squares (RLS) algorithm is discussed firstly. The reason for the RLS algorithm affecting the accuracy and rapidity of model parameter identification is pointed out. And an improved RLS algorithm is proposed, an inner loop with the estimated parameter vector updated multiple times is inserted into the conventional RLS algorithm, so that the identification results are improved. The test platform of a single lithium‐ion battery is built. The experimental results show that the improved RLS algorithm has better tracking ability, smaller prediction error and has a moderate computational burden compared with the conventional RLS algorithm and a variable forgetting factor RLS algorithm.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
60
Top 1%
Top 10%
Top 10%
gold