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 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.