A dynamic capacity degradation model and its applications considering varying load for a large format Li-ion battery. (1st March 2016)

• Record Type: Journal Article
• Authors: Ouyang, Minggao; Feng, Xuning; Han, Xuebing; Lu, Languang; Li, Zhe; He, Xiangming
• Is Part Of: Applied energy. Volume 165(2016)
• Page Start: 48
• Page End: 59
• Publication Date: 2016-03-01
• Subjects: Lithium ion battery -- Capacity degradation -- State of health -- Degradation model -- Chemical kinetics; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2015.12.063
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A dynamic capacity degradation model for large format Li-ion battery is proposed. The change of the model parameters directly link with the degradation mechanisms. The model can simulate the fading behavior of Li-ion battery under varying loads. The model can help evaluate the longevity of a battery system under specific load. The model can help predict the evolution of cell variations within a battery pack. Abstract: The capacity degradation of the lithium ion battery should be well predicted during battery system design. Therefore, high-fidelity capacity degradation models that are suitable for the task of capacity prediction are required. This paper proposes a novel capacity degradation model that can simulate the degradation dynamics under varying working conditions for large-format lithium ion batteries. The degradation model is built based on a mechanistic and prognostic model (MPM) whose parameters are closely linked with the degradation mechanisms of lithium ion batteries. Chemical kinetics was set to drive the parameters of the MPM to change as capacity degradation continues. With the dynamic parameters of the MPM, the capacity predicted by the degradation model decreases as the cycle continues. Accelerated aging tests were conducted on three types of commercial lithium ion batteries to calibrate the capacity degradation model. The good fit with the experimental data indicates that the model can capture the degradation mechanisms well for different types of commercial lithium ion batteries. Furthermore, the calibrated model can be used to (1) evaluate the longevity of a battery system under a specific working load and (2) predict the evolution of cell variations within a battery pack when different cell works at different conditions. Correlated applications are discussed using the calibrated degradation model.