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Second-life lithium-ion battery aging dataset based on grid storage cycling.

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This study investigates used lithium-ion battery cells for second-life grid energy storage applications. The data reveals degradation patterns from combined cycling and calendar aging, offering insights for battery repurposing.

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Area of Science:

  • Materials Science
  • Electrochemistry
  • Energy Storage

Background:

  • Used lithium-ion battery cells from electric vehicles present potential for second-life applications.
  • Grid energy storage systems (ESS) require robust and long-lasting battery solutions.
  • Understanding degradation mechanisms in repurposed batteries is crucial for their economic viability.

Purpose of the Study:

  • To create an experimental dataset of used lithium-ion battery cells for second-life ESS.
  • To analyze the feasibility of second-life applications for aged battery cells.
  • To quantify battery degradation under simulated grid storage conditions.

Main Methods:

  • Testing of ten INR21700-M50T lithium-ion cells (graphite/silicon anode, NMC cathode) after initial EV use.
  • A 24-month aging campaign combining calendar aging at room temperature and cycling under synthetic grid duty cycles.
  • Simulated seasonal temperature variations (20°C to 35°C) during cycling.
  • Periodic degradation assessments using Reference Performance Tests for second-life (RPT S) and Electrochemical Impedance Spectroscopy (EIS) at various states of charge (SOC).

Main Results:

  • The dataset captures the combined effects of cycling-induced stress and long-term calendar aging on battery performance.
  • Degradation was monitored through capacity fade and pulse power reduction.
  • Electrochemical Impedance Spectroscopy provided insights into changes in internal battery resistance.

Conclusions:

  • The experimental data provides valuable insights into the performance and degradation of used lithium-ion cells in grid energy storage.
  • This dataset can inform the design and implementation of second-life battery strategies.
  • Further research can utilize this data to optimize battery management systems for repurposed batteries.