Energy and AI (Sep 2021)

Prediction of future capacity and internal resistance of Li-ion cells from one cycle of input data

  • Calum Strange,
  • Gonçalo dos Reis

Journal volume & issue
Vol. 5
p. 100097


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There is a large demand for models able to predict the future capacity retention and internal resistance (IR) of Lithium-ion battery cells with as little testing as possible. We provide a data-centric model accurately predicting a cell’s entire capacity and IR trajectory from one single cycle of input data. This represents a significant reduction in the amount of input data needed over previous works. Our approach characterises the capacity and IR curve through a small number of key points, which, once predicted and interpolated, describe the full curve. With this approach the remaining useful life is predicted with an 8.6% mean absolute percentage error when the input-cycle is within the first 100 cycles.