Internal Short-Circuit Detection of Li-Ion Battery Based on EIS and Elman Neural Network

The Li-ion battery industry is developing rapidly, but battery safety has always been a very important issue. In Li-ion battery failures, the detection of internal short-circuits still lacks a reliable solution. This paper researches an internal short-circuit detection model based on Elman neural network and impedance spectrum analysis, uses correlation analysis to create a data set, and uses the PSO algorithm to optimize the Elman neural network, aiming to quickly and accurately solve the problem of Li-ion battery internal short-circuits.