Adaptive Forgetting Factor Recursive Least Square Algorithm for Online Identification of Equivalent Circuit Model Parameters of a Lithium-Ion Battery

With the popularity of electric vehicles, lithium-ion batteries as a power source are an important part of electric vehicles, and online identification of equivalent circuit model parameters of a lithium-ion battery has gradually become a focus of research. A second-order RC equivalent circuit model...

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Vydáno v:Energies (Basel) Ročník 12; číslo 12; s. 2242
Hlavní autoři: Sun, Xiangdong, Ji, Jingrun, Ren, Biying, Xie, Chenxue, Yan, Dan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 12.06.2019
Témata:
Accuracy
Acids
adaptive forgetting factor
Algorithms
Automation
Circuits
Electric vehicles
equivalent circuit model
International conferences
Kalman filters
Lithium
lithium-ion battery
Mean square errors
Parameter identification
recursive least square
Simulation
China
ISSN:1996-1073, 1996-1073
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Shrnutí:With the popularity of electric vehicles, lithium-ion batteries as a power source are an important part of electric vehicles, and online identification of equivalent circuit model parameters of a lithium-ion battery has gradually become a focus of research. A second-order RC equivalent circuit model of a lithium-ion battery cell is modeled and analyzed in this paper. An adaptive expression of the variable forgetting factor is constructed. An adaptive forgetting factor recursive least square (AFFRLS) method for online identification of equivalent circuit model parameters is proposed. The equivalent circuit model parameters are identified online on the basis of the dynamic stress testing (DST) experiment. The online voltage prediction of the lithium-ion battery is carried out by using the identified circuit parameters. Taking the measurable actual terminal voltage of a single battery cell as a reference, by comparing the predicted battery terminal voltage with the actual measured terminal voltage, it is shown that the proposed AFFRLS algorithm is superior to the existing forgetting factor recursive least square (FFRLS) and variable forgetting factor recursive least square (VFFRLS) algorithms in accuracy and rapidity, which proves the feasibility and correctness of the proposed parameter identification algorithm.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1996-1073
1996-1073
DOI:10.3390/en12122242