Parameter Identification of Lithium-ion Battery using Dragonfly Algorithm

Parameter identification is the basis for state estimation, energy equalization, and charging optimization in the battery management system. In this paper, the parameter identification scheme using Dragonfly Algorithm (DA) is developed for lithium-ion batteries. The system model is discretised for c...

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Bibliographic Details
Published in2024 IEEE 25th China Conference on System Simulation Technology and its Application (CCSSTA) pp. 565 - 569
Main Authors Tian, Jiaqiang, Yin, Xinxiang, Pan, Tianhong, Zhang, Xu, Yang, Duo, Ni, Liping
Format Conference Proceeding
LanguageEnglish
Published IEEE 21.07.2024
Subjects
Accuracy
dragonfly algorithm
first-order RC model
Integrated circuit modeling
Lithium-ion batteries
Mathematical models
Parameter estimation
parameter identification
Particle swarm optimization
Root mean square
State estimation
Systems simulation
Voltage
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Summary:Parameter identification is the basis for state estimation, energy equalization, and charging optimization in the battery management system. In this paper, the parameter identification scheme using Dragonfly Algorithm (DA) is developed for lithium-ion batteries. The system model is discretised for constructing the voltage error evaluation function according to the first-order RC model. The DA is used for model parameter identification. The estimation effects of Particle Swarm Optimization (PSO) and Ant Lion Optimizer (ALO) are compared. The experimental results show that the proposed DA parameter identification algorithm has higher estimation accuracy.
DOI:10.1109/CCSSTA62096.2024.10691832