Battery material
Research Papers

Mechanistic calendar aging model for lithium-ion batteries

In this work we present a novel mechanistic calendar aging model for a commercial lithium-ion cell with NCA cathode and silicon-graphite anode. The mechanistic calendar aging model is a semi-empirical aging model that is parameterized on component states of health, instead of capacity.

TWAICE / Jun 09, 2023

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Mechanistic calendar aging model for lithium-ion batteries

Authors: Alexander Karger, Julius Schmitt, Cedric Kirst, Jan Singer, Leo Wildfeuer, Andreas Jossen

Highlights

  • Mechanistic calendar aging model is parameterized on component states of health
  • Three component states of health are derived from degradation modes
  • Model is parameterized on 627 days of calendar aging at 27 storage conditions
  • Influence of check-up during testing is compensated in a two-step process
  • Check-up compensation increases predicted lifetime by > 150%

In this work we present a novel mechanistic calendar aging model for a commercial lithium-ion cell with NCA cathode and silicon-graphite anode. The mechanistic calendar aging model is a semi-empirical aging model that is parameterized on component states of health, instead of capacity.

Three component states of health are derived from the degradation modes, which are calculated by fitting the electrode potential curves at every check-up measurement. The aging data used for model parameterization spans 672 days of storage at 27 different combinations of ambient temperature (T amb) and state of charge (SOC).

To compensate for the influence of the check-up measurements on cell degradation, the aging data is pre-processed in two steps, considering immediate degradation caused by the check-up cycles and accelerated degradation during subsequent storage. The loss of active anode material is negligible during check-up-compensated calendar aging. For loss of lithium inventory and loss of active cathode material, Tafel and Arrhenius terms are successfully used to model T amb and SOC dependence. The mechanistic calendar aging model predicts the capacity with <1% mean deviation for 7 different storage conditions after 672 days without check-ups. The check-up compensation increases predicted lifetime by >150% for exemplary storage at T amb=60°C and SOC=50%.

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