crate

[zeecode07]

I use SEI like this,

but why do I get the number of cycles when it reaches termination = 80%, that is, the higher the charge and discharge rate (CRate) the more cycles:
0.1C = 636 cycles
0.2C = 1121 cycles
0.3C = 1441 cycles
1C = 1959 cycles
2C = 1990 cycles
3C = 1972 cycles

Is that true? @tinosulzer @brosaplanella

[valentinsulzer]

Yes. The SEI models are basically just calendar aging, and the higher C-rates have shorter cycles so less degradation per cycle. This is also backed up by experiments e.g. https://iopscience.iop.org/article/10.1149/2.0231904jes/pdf Try plotting capacity vs time or Ah-throughput.

[zeecode07]

can it be calculated by
lifetime = cycle number / charge and discharge rate

[brosaplanella]

No, lifetime is a product of quite complex processes so it can only be predicted via simulations of such processes.

[zeecode07]

then how to predict lifetime?

[brosaplanella]

As I said in my previous comment, you would need to run a simulation to predict the lifetime of the battery.

[zeecode07]

but the time to reach the end of the cycle when C rates are high the time is longer so the number of cycles is large than the C rates are low the time is faster and the number of cycles is small @tinosulzer

[zeecode07]

At higher C-rates cycles are shorter so there are more cycles in the same amount of time. Time (not cycle count) is what affects SEI growth.

but the time to reach the end of the cycle when C rates are high the time is longer so the number of cycles is large than the C rates are low the time is faster and the number of cycles is small @tinosulzer

my code when simulating experiment like this, this is when 0.1C :
experiment = pybamm.Experiment([
("Discharge at 0.1C until 2.5V",
"Rest for 1 hour",
"Charge at 0.1C until 4.2V",
"Hold at 4.2V until C/50")
] * 5000,
termination="80% capacity")

sim = pybamm.Simulation(model, experiment=experiment, parameter_values=parameter_values, var_pts=var_pts)
sol = sim.solve()

[zeecode07]

can you help me sir why this happen? @tinosulzer @brosaplanella

[brosaplanella]

At higher C-rates the discharge time should be shorter than expected, so the total capacity you can extract is smaller. Here is a hypothetical example: if a battery discharges at 1C in exactly 1 hour, at 2C it would discharge in a bit less than half an hour and thus the total discharge capacity would be lower than at 1C. These effects add on when doing many cycles, and that's what we suspect causes the lower ageing at higher C-rates.

About the second point, I don't think I understand your question. If you run that simulation and then extract the number of cycles until 80% capacity that would give you a measure of the lifetime. But there is no analytical formula that would allow you to compute this, so you need to use a simulation.

[Naveen-S06]

Can anyone kindly help how to retrieve cycle number? I don't see that being an output variable in the default parameter set. I'm new to PyBamm and it would be great if someone could help me in this