State-of-health estimation of retired lithium-ion battery module aged at 1C-rate

• Published in: Journal of energy storage 2022-06, Vol.50, p.104618, Article 104618
• Main Authors: Sun, Huiqin, Wen, Xiankui, Liu, Wei, Wang, Zhiqin, Liao, Qiangqiang
• Format: Article
• Language: English
• Subjects: Differential voltage analysis; Health factor; Incremental capacity analysis; Regional capacity analysis; Retired battery module; SOH evaluation
• ISSN: 2352-152X; 2352-1538
• DOI: 10.1016/j.est.2022.104618

This research provides a novel estimation model for the state of health (SOH) of retired battery module at 1C-rate with the sampling frequency of 1/60 Hz. The retired 15P4S battery module from Chery S18B electric vehicle is aging at 1C-rate in the range of 0% - 100% SOC with the sampling frequency of 1/60 Hz until the SOH reduces to less than 60%. The regional capacity analysis (RCA) and differential voltage analysis (DVA) are employed for the modeling and validation of module SOH evaluation. The results show that the regional capacity from RCA is an effective SOH evaluation index for battery module. The terminal slope from DVA as a novel and effective indicator is linearly negatively correlated with module SOH. There are good linear negative correlations between ST and SOH. The R2 value of ST - SOH model during discharge is greater than that during charge. The maximum relative errors of evaluated SOH from the ST - SOH models are both smaller than those from the Cˆ - SOH models in the validation group whether charging or discharging. Among them, the ST during discharging is the most effective health factor for module SOH assessment. •Build SOH model based on the working voltage at 1C-rate and the frequency of 1 min.•Compare two quick evaluation methods of battery module SOH in detail.•Propose the DV curve slope at high SOC values as a rapid evaluation index of SOH.•Module SOH value is negatively linear with the DV curve slope.•DVA has better accuracy on module SOH than RCA.