How to simulate multiple drive cycles?

[JaeHyeonL]

I am trying to simulate 20~40 drive cycle repetitions for US06 and UDDS. Currently I have a drive cycle and would like to replicate this over multiple cycles. To solve this problem, I followed the previous tinosulzer's Q&A answer suggesting the following code:

The following example repeats the US06 drive cycle 3 times (for 1800s instead of 600s):
import pybamm
import pandas as pd
import os

os.chdir(pybamm.path[0] + "/..")

pybamm.set_logging_level("INFO")

load model and update parameters so the input current is the US06 drive cycle

model = pybamm.lithium_ion.SPMe({"thermal": "lumped"})
param = model.default_parameter_values

import drive cycle from file

drive_cycle = pd.read_csv(
"pybamm/input/drive_cycles/US06.csv", comment="#", header=None
).to_numpy()

create interpolant

timescale = param.evaluate(model.timescale)

in the following line we use % 600 to repeat the drive cycle every 600 seconds

current_interpolant = pybamm.Interpolant(drive_cycle, (timescale * pybamm.t) % 600)

set drive cycle

param["Current function [A]"] = current_interpolant

create and run simulation using the CasadiSolver in "fast" mode, remembering to

pass in the updated parameters

sim = pybamm.Simulation(
model, parameter_values=param, solver=pybamm.CasadiSolver(mode="fast")
)

we need to specify the solve time to be different from the default [0, 600]

this will raise a warning but this can be ignored

sim.solve([0, 1800])

use this instead to get rid of the warning

t_drive = drive_cycle[:, 0]

step_size = np.min(np.diff(t_drive))

t_eval = np.arange(0, 1800, step_size)

sim.solve(t_eval)

you can play with step_size to change the level of resolution of the drive cycle

sim.plot(
[
"Negative particle surface concentration [mol.m-3]",
"Electrolyte concentration [mol.m-3]",
"Positive particle surface concentration [mol.m-3]",
"Current [A]",
"Negative electrode potential [V]",
"Electrolyte potential [V]",
"Positive electrode potential [V]",
"Terminal voltage [V]",
"X-averaged cell temperature",
]
)

However, when I run the code, there is an error "timescale has been removed since models are now dimensional".