A novel lifetime prediction method for lithium-ion batteries in the case of stand-alone renewable energy systems

• Published in: International journal of electrical power & energy systems Vol. 103; pp. 115 - 126
• Main Authors: Astaneh, Majid, Dufo-López, Rodolfo, Roshandel, Ramin, Bernal-Agustin, José L.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2018
• Subjects: Lithium-ion battery; Reduced-order model (ROM); Simplified single particle model (SSPM); Solid electrolyte interphase (SEI); Stand-alone renewable energy systems; Lithium-ion battery; Solid electrolyte interphase (SEI); Reduced-order model (ROM); Simplified single particle model (SSPM); Stand-alone renewable energy systems
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2018.05.034

•Aging model of Li-ion batteries in off-grid renewable installations is presented.•The model is compared with experimental data.•The method is implemented into an installed PV-battery system.•Realistic lifetime predictions can be obtained by this methodology.•The effect of control strategy on battery lifetime is investigated. This paper presents a mathematical formulation of lithium-ion batteries, including aging and temperature effects. The model is developed by integrating the simplified single particle model (SSPM) and reduced-order model (ROM) to predict solid electrolyte interphase growth (SEI). Results show agreement with the experimental data at 25 °C operating temperature and moderate cycling currents. A maximum error of 3.6% in finding the battery discharged Ah is observed in harsh operating conditions, including 60 °C and approaching the end of life of the battery. Due to the typical operating conditions of stand-alone renewable energy systems, more accurate estimations are expected. Finally, this methodology is utilized to predict the lifetime of lithium-ion batteries that are combined with PV generators to supply electricity to an isolated house situated near Zaragoza, Spain, under two control strategies. The results indicate realistic lifetime predictions when using the model in real operating conditions for this kind of system. Besides, by maintaining the batteries in states of charge of lower than 70%, around 55% increase in the battery lifetime can be achieved at the cost of 0.23% reduction in the percentage of the electrical load that is able to be covered by the stand-alone system.