Capacity fading mechanisms and state of health prediction of commercial lithium-ion battery in total lifespan

Abstract

In this study, aging mechanisms and state of health prediction of lithium-ion battery in total lifespan are investigated. Battery capacity fading can be divided into three stages: stable capacity fading, fast capacity fading, and repetition between capacity increase and decrease. Incremental capacity analysis and electrochemical impedance spectroscopy are used to study relevant aging mechanisms. In the first stage, aging mechanisms that affect lithium-ion batteries include loss of lithium and loss of active material at the negative and positive electrode. In the second stage, the aging mechanisms are loss of lithium and loss of active material at the negative electrode. In the third stage, the loss of lithium is recovered to increase capacity. Finally, back propagation neural network optimized by genetic algorithm is used to predict state of health of lithium-ion battery in total lifespan, including cycle life of new batteries, second-life use after being retired, and residual capacity of retired batteries.