Lithium-ion batteries (LIBs) repurposed from retired electric vehicles (EVs) for grid-scale energy storage systems (ESSs) have the potential to contribute to a sustainable, low-carbon-emissions energy future. The economic and technological value of these “second-life” LIB ESSs must be evaluated based on their operation on the electric grid, which determines their aging trajectories. The battery research community needs experimental data to understand the operation of these batteries using laboratory experiments, yet there is a lack of work on experimental evaluation of second-life batteries. Previous studies in the literature use overly-simplistic duty cycling in order to age second-life batteries, which may not produce aging trajectories that are representative of grid-scale ESS operation. This mismatch may lead to inaccurate valuation of retired EV LIBs as a grid resource. This paper presents an end-to-end methodology that uses real-world electric grid power system data to simulate the cost-optimal dispatch for grid-scale ESSs. The dispatch is then used as an input to an algorithm which produces laboratory-prone, power-based synthetic duty cycles for second-life LIB cell aging experiments.
