Remaining useful life prediction for 18650 sodium-ion batteries based on incremental capacity analysis

Accurate prediction of remaining useful life (RUL) and management for sodium-ion batteries have great sig-nificance, since they are promising for implementation as large-scale energy storage plants in renewable energy systems. In this paper, 18650 sodium-ion batteries are investigated. The observed data from the cycle life test has been used to examine the oxidation process and aging mechanisms based on incremental capacity analysis (ICA). Moreover, the Gaussian process regression (GPR) is established for accurate RUL prediction. The negative electrode half-cell with hard carbon, positive electrode half-cell with Na3.2V1.8Zn0.2(PO4)(3), coin cells with Na3.2V1.8Zn0.2(PO4)(3) vs hard carbon, and 18650 cells with Na3.2V1.8Zn0.2(PO4)(3) vs hard carbon are analysed based on ICA. The oxidation process of vanadium (V3+-> V4+) corresponding to the incremental capacity peak is selected to extract six potential health indicators. To reduce redundant information among various features, the principal component analysis is utilized to obtain the syncretic health indicator. The GPR is established for reliable prediction with a 95% confidence interval. When compared to the traditional methods, the proposed method can achieve higher accuracy in RUL prediction with a root mean square error below 1.16%.

Automated summary

This paper investigates the accurate prediction and management of remaining useful life (RUL) for sodium-ion batteries, using incremental capacity analysis to study oxidation process and aging mechanisms, and Gaussian process regression for precise RUL prediction, as well as principal component analysis to obtain a syncretic health indicator.