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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Veröffentlicht in:IET power electronics Jg. 13; H. 12; S. 2531 - 2537
Hauptverfasser: Ren, Biying, Xie, Chenxue, Sun, Xiangdong, Zhang, Qi, Yan, Dan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 16.09.2020
Schlagworte:
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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Beschreibung
Zusammenfassung: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