Implementing fitted stoichiometry windows from half-cell OCPs for a multilayer 65 Ah pouch cell in PyBaMM

PyBaMM Q&A Parameters
1

Dear pybamm users,

I performed a cell teardown on a 65 Ah NMC–graphite pouch cell in order to obtain the half-cell OCP curves of the electrodes. The pouch cell consists of 62 double-coated layers (31 anodes and 31 cathodes).

To estimate the stoichiometry windows, I performed a C/30 quasi-OCV (qOCV) test on the full cell and optimized the stoichiometric limits using the half-cell OCP curves. Since the current is very low, I assumed that the overpotential is negligible and that the full-cell voltage can be approximated as:

V_cell ≈ U_cathode − U_anode

The optimization produced the following stoichiometry limits:

Graphite:

  • x_lo = 0.3358

  • x_hi = 0.9976

NMC:

  • x_lo = 0.0000

  • x_hi = 0.9728

RMSE between measured and reconstructed OCV: 0.0274 V

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Question 1 – Capacity scaling for multilayer pouch cells

To account for the multilayer structure, I multiplied the electrode surface area by 62 (corresponding to 31 double-coated electrode pairs) in order to scale the capacity to the full pouch cell.

Is this the correct way to represent a multilayer pouch cell in PyBaMM, or is there a more appropriate parameter to adjust for capacity scaling?

Question 2 – Implementing fitted stoichiometry windows in PyBaMM

The reconstructed OCV using the half-cell curves matches the measured OCV with an error of around 2 mV locally, but the overall RMSE is about 27 mV. I am not sure whether this discrepancy is due to:

  • uncertainty in the half-cell OCP measurements, or

  • limitations of the optimization procedure.

I repeated the OCP measurements using backup electrodes, but obtained very similar results.

After obtaining these stoichiometry limits, I attempted to implement them in PyBaMM. My understanding is that the stoichiometry limits should be reflected through the initial lithium concentrations in the electrodes.

Could someone clarify the correct way to apply fitted stoichiometry windows in PyBaMM? Specifically:

  • How should the initial lithium concentration be calculated from the optimized stoichiometric limits?

Question 3 – Parameter optimization at low C-rate

For parameter identification under low C-rate experiments, which parameters should be prioritized first if i already fixed the thicknesses, the surface area based on the scaling logic mentioned above ?

Is there a recommended order for parameter optimization when starting from low C-rate cycling data?

Any suggestions or guidance would be greatly appreciated.