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

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 re...

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Vydáno v:	IET power electronics Ročník 13; číslo 12; s. 2531 - 2537
Hlavní autoři:	Ren, Biying, Xie, Chenxue, Sun, Xiangdong, Zhang, Qi, Yan, Dan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 16.09.2020
Témata:	accurate parameter identification battery management systems conventional RLS algorithm critical basis equivalent circuits estimated parameter vector improved recursive least square algorithm improved RLS algorithm least squares approximations model parameter identification parameter estimation parameter identification process recursive estimation recursive least squares algorithm Research Article secondary cells second‐order RC equivalent circuit model single lithium‐ion battery variable forgetting factor RLS algorithm least squares approximations model parameter identification variable forgetting factor RLS algorithm recursive least squares algorithm battery management systems equivalent circuits estimated parameter vector parameter identification process accurate parameter identification critical basis improved recursive least square algorithm single lithium-ion battery second-order RC equivalent circuit model recursive estimation parameter estimation secondary cells conventional RLS algorithm improved RLS algorithm
ISSN:	1755-4535, 1755-4543
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Shrnutí:	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.
ISSN:	1755-4535 1755-4543
DOI:	10.1049/iet-pel.2019.1589