Cycle Life Prediction of Lithium Batteries Based on Generalized Regression Network with Improved PSO. (June 2020)

• Record Type: Journal Article
• Authors: Xiao, Yao; Wu, Mengqiang; Xu, Ziqiang; Li, Yuanxun
• Is Part Of: Journal of physics. Volume 1549:Number 2(2020)
• Publication Date: 2020-06
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1549/2/022025
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: To predict the cycle life of lithium-ion batteries more accurately, an improved PSO algorithm and a generalized regression neural network (GRNN) combined with the cycle life prediction method of lithium ion battery are proposed. Based on the simulation and actual prediction data, the results show that the established model has higher prediction accuracy than GRNN, which is of great significance for solving the life prediction accuracy of lithium iron phosphate battery.