In a significant advancement for the energy storage sector, researchers at Stanford University have released a comprehensive dataset that could pave the way for enhanced second-life applications of lithium-ion batteries. This research, spearheaded by Kevin Moy from the Department of Energy Science and Engineering at Stanford, focuses on the aging characteristics of used lithium-ion cells under conditions that mimic real-world energy storage scenarios.
The dataset, which was published in ‘Data in Brief’, captures the performance of ten INR21700-M50T battery cells over a two-year period. These cells, featuring a graphite/silicon anode paired with a Nickel–Manganese–Cobalt (NMC) cathode, were initially tested for 23 months using the Urban Dynamometer Driving Schedule (UDDS) to simulate automotive use. The innovative approach taken in this latest study involved subjecting six of these cells to a combination of cycling and calendar aging, designed specifically to replicate the fluctuating conditions encountered in residential and commercial grid energy storage systems.
Moy emphasized the importance of this research, stating, “By mimicking the seasonal temperature variations and real-world usage patterns, we can better understand how these batteries degrade over time, which is crucial for their second-life applications.” The cycling component alternates temperatures between 20 °C and 35 °C, effectively simulating the seasonal shifts that energy storage systems experience. The calendar aging occurs at room temperature, allowing for a comprehensive analysis of the battery’s longevity and performance.
Periodic assessments of battery health were conducted through Reference Performance Tests for second-life (RPT S), which included combined capacity and pulse power tests, alongside Electrochemical Impedance Spectroscopy (EIS) at various state-of-charge (SOC) levels. This dual approach not only quantifies the effects of cycling-induced stress but also addresses the long-term storage impacts on battery performance.
The implications of this research are profound for the energy sector, particularly as the demand for sustainable energy solutions continues to rise. By extending the usable life of lithium-ion batteries through second-life applications, companies can significantly reduce waste and lower costs associated with energy storage. The insights gained from this dataset could inform the design of more efficient energy systems, ultimately contributing to a more sustainable and economically viable energy landscape.
As the energy transition accelerates, understanding battery degradation is critical. This dataset serves as a valuable resource for researchers and industry professionals looking to optimize battery usage and lifecycle management. As Moy puts it, “The future of energy storage hinges on our ability to innovate and adapt existing technologies for new applications.”
For those interested in delving deeper into this research, the dataset is available in ‘Data in Brief’, a journal that focuses on data-driven studies. To learn more about Kevin Moy’s work and the Stanford Energy Control Laboratory, visit lead_author_affiliation.
