Transient thermal characteristic analysis and charging state estimation of lithium batteries for automated guided vehicle during discharge

Abstract

The lithium batteries and their health management for automated guided vehicle power supply system are studied in depth in this paper. First, the transient heat generation for the discharge process of a lithium battery will cause it to work in an unhealthy state and non-linear conditions, seriously affecting the life expectancy. The thermal behavior for lithium battery discharge is studied in depth, and a reliable thermal model is constructed to provide a theoretical basis for designing a lithium battery health management system. Secondly, the accurate and reliable residual state estimation of the lithium battery cannot only provide visualized battery residual capacity, but also reflect the aging status of the lithium battery and other related information, and is one of the important functions to ensure the healthy operation of the lithium battery pack. A new support vector machine is proposed on account of the analysis of the equivalent circuit model of lithium battery, which combines genetic algorithm with particle swarm optimization to enhance the parameters of hybrid kernel function, to analyze accurately the charging status. Finally, the state-of-charge simulation of lithium batteries with variable current discharge is conducted, which proves that the support vector machine algorithm proposed in this paper can accurately judge the charging state of lithium batteries.