Development of a degradation-conscious physics-based lithium-ion battery model for use in power system planning studies. (15th August 2019)

• Record Type: Journal Article
• Authors: Li, Yang; Vilathgamuwa, Mahinda; Choi, San Shing; Farrell, Troy W.; Tran, Ngoc Tham; Teague, Joseph
• Is Part Of: Applied energy. Volume 248(2019)
• Page Start: 512
• Page End: 525
• Publication Date: 2019-08-15
• Subjects: Lithium-ion battery -- Battery energy storage system -- Physics-based model -- Degradation model -- Power system planning studies; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2019.04.143
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A physics-based Li-ion battery model is developed for power system planning studies. Side reactions of the negative electrode are considered in an equivalent circuit model. Parametric values of the circuit components are automatically updated. Short- and long-term performance is predicted based on power flow at battery terminal. Stored energy, degradation, and constraints are available for optimization of design. Abstract: A computationally-efficient and reliable method is developed to permit the simultaneous assessment of both the short- and long-term performance of lithium-ion battery in power system planning studies. Toward this end, a physics-based equivalent circuit model of the lithium-ion battery is derived in which side reaction-induced degradation of the battery is included. Whence a computational procedure is developed to enable the parametric values of the circuit elements in the equivalent circuit model to be automatically updated as the battery operates. The resulting model allows the increase in the internal resistance and the decrease in the energy storage capacity of the battery to be determined, based solely on the information of the power flows at the battery terminals. Dynamic simulation results obtained using the developed equivalent circuit model are shown to be in close agreement with those obtained from well-established electrochemical models, but at a much reduced computational burden.