Energy storage plays a crucial role in the energy transition. Lithium-ion cell technology is the leading energy storage technology today across both the major pillars of the energy sector: mobility and electricity. Lithium-ion batteries are deployed in electric vehicles spanning all segments, and in stationary battery energy storage systems to provide a variety of both grid-connected and off-grid services. While there are no direct emissions due to the use of this technology, the carbon footprint of a Lithium-ion battery comprises of indirect emissions in its production, its operation, and recycling phases. Repurposing of decommissioned automotive batteries in â€˜second-lifeâ€™ stationary applications is a widely discussed concept to meaningfully extend the battery lifecycle before recycling. In this work, the lifecycle carbon footprint of Lithium-ion batteries operating in three overarching pathways is quantified simulatively with open-source python-based energy system and battery system simulation programs. These pathways are â€“ i) automotive application (A), ii) stationary application (S), and iii) automotive application followed by a second-life stationary application (AS). From the dual perspective of decarbonization and resource efficiency, it is essential to identify the most effective lifecycle pathways for battery system applications. The metric â€˜Levelized Emissions of Energy Supplyâ€™, LEES, is used to compare the scenarios. It is found that under the considered assumptions and simulation conditions, the S pathway performs the best, followed by the cascaded AS pathway. The automotive pathway A has the highest LEES value.
Keywords Battery Electric Vehicle, Second-Life Battery System, Battery Energy Storage System, Electric Vehicle Battery, Levelized Emissions of Energy Supply (LEES), Carbon Footprint