Aging performance characterization and state-of-health assessment of retired lithium-ion battery modules

• Published in: Journal of energy storage Vol. 40; p. 102743
• Main Authors: Zhang, Qichao, Li, Xinzhou, Du, Zhichao, Liao, Qiangqiang
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2021
• Subjects: Average Fréchet distance; Electrochemical impedance spectroscopy; Incremental capacity analysis; Retired battery modules; SOH estimation; SOH estimation; Average Fréchet distance; Incremental capacity analysis; Retired battery modules; Electrochemical impedance spectroscopy
• ISSN: 2352-152X; 2352-1538
• DOI: 10.1016/j.est.2021.102743

•There is a good linear negative correlation between state of health and resistance.•The maximum peak of incremental capacity curves is a good health factor of modules.•A state of health evaluation method based on average Fréchet discrete is introduced.•The maximum evaluation error is less than 2% based on average Fréchet discrete. State of health (SOH) is an important index to evaluate the use value of batteries. The rapid SOH evaluation method for battery modules is a more popular topic in the secondary utilization of retired batteries. This paper explores the aging behavior of a 15P4S battery module in the cycle protocol of 2 C-rate and 50% DOD among 30–80% SOC using electrochemical impedance spectroscopy (EIS), charge/discharge (C/D) curve, incremental capacity analysis (ICA) and average Fréchet distance (AFD). It is found that Rs, Rct and Rf all increase with aging and the sum of Rs and Rf can be used as a health factor for off-line SOH evaluation of battery modules. The height of the characteristic peak near 13.45 V on the ICA curves can quickly evaluate the module SOH. The SOH estimation model based on the AFD method achieves the maximum percentage error of 1.518% for lithium-ion battery modules, suggesting the high accuracy of the fast SOH evaluation model. AFD has a better accuracy on online SOH evaluation for modules than ICA.