Aging performance characterization and state-of-health assessment of retired lithium-ion battery modules. (August 2021)

• Record Type: Journal Article
• Authors: Zhang, Qichao; Li, Xinzhou; Du, Zhichao; Liao, Qiangqiang
• Is Part Of: Journal of energy storage. Volume 40(2021)
• Publication Date: 2021-08
• Subjects: Retired battery modules -- SOH estimation -- Electrochemical impedance spectroscopy -- Incremental capacity analysis -- Average Fréchet distance; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2021.102743
• Languages: English
• ISSNs: 2352-152X

Abstract

Highlights: 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. Abstract: 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 R s, R ct and R f all increase with aging and the sum of R s and R f 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.