Characterization of aging mechanisms and state of health for second-life 21700 ternary lithium-ion battery

This paper focuses on the identification of aging mechanisms and the estimation of the state of health (SOH) for second-life 21700 nickel–cobalt–aluminum (NCA) lithium-ion batteries. NCA battery is aged at 1/2 C-rate in the laboratory until its SOH value reaches about 60%. Incremental capacity (IC) and different voltage (DV) and probability density function (PDF) analyses are used to explore the aging mechanisms of NCA battery and build SOH estimation models with and without multicollinearity. The results show that the capacity decays almost linearly throughout the aging cycle and the loss of lithium inventory (LLI) and the loss of active material (LAM) on anode are the main aging mechanisms. The equivalence between PDF and IC/DV analyses is proved by NCA battery. Peak (valley) features from IC, DV and PDF curves are extracted as health factors (HFs), which have good correlation with battery SOH. Principal component analysis (PCA) is employed to reduce the multicollinearity and more accurate SOH evaluation models are built based on principal component regression (PCR). The verification results show that the ICA-PCR, DVA-PCR and PDF-PCR models all have good evaluation accuracy. •LAM and LLI on the anode are the main aging mechanisms for second-life NCA battery.•The equivalence between PDF and IC/DV analyses is proved by NCA battery.•SOH evaluation models are more accurate based on principal component regression.•The ICA-PCR, DVA-PCR and PDF-PCR SOH models are verified.