An efficient and independent modeling method for lithium-ion battery degradation

• Published in: Ionics Vol. 28; no. 1; pp. 99 - 105
• Main Authors: Shan, Haipeng, Zhang, Jianli, Cao, Huazhen, Hou, Guangya, Tang, Yiping, Zheng, Guoqu
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 2022; Springer Nature B.V
• Subjects: Chemistry; Chemistry and Materials Science; Condensed Matter Physics; Degradation; Discharge; Electric vehicles; Electrochemistry; Energy Storage; Homogeneity; Lithium; Lithium-ion batteries; Mathematical models; Modelling; Optical and Electronic Materials; Original Paper; Parameters; Rechargeable batteries; Renewable and Green Energy; Service life; Degradation; Lithium-ion battery; Modeling; State of health
• ISSN: 0947-7047; 1862-0760
• DOI: 10.1007/s11581-021-04305-5

Degradation in the lithium-ion battery performance is an inevitable phenomenon during the service life. Therefore, the state of health (SOH) of the battery is an important indicator of the battery management system (BMS) in electric vehicles (EVs). The existing estimation techniques to predict the losses due to degradation and SOH of the battery are limited by the situation of being incomplete or computationally expensive. This work develops an efficient and independent modeling method for SOH estimation and degradation analysis, in which a simple parameter fitting can be used to represent the discharge profile that can be represented with an accuracy of > 99.9%, using simple parameter fitting. The homogeneity of the active lithium distribution, the discharge capacity and the evolution of internal resistance have been well demonstrated by the model parameters. In addition, through simple calculation, the loss of active materials and the state of electrode balance are accurately represented by the derivate parameters.