Program runtime improvement

[RobinBluehub]

The model uses the DFN model, and other aging sub-models are as follows. When I found that adding the "lumped" model, the calculation time was several times that of the model without temperature, and it took 4 days to run a thousand cycles. Is there any way to improve the calculation time?

Code as follows:
`import pybamm
import numpy as np
import matplotlib.pyplot as plt
pybamm.set_logging_level("NOTICE")
from pybamm import Parameter, constants, exp

options={
"particle": "Fickian diffusion",
"SEI":"solvent-diffusion limited",
"particle mechanics":("swelling and cracking","swelling only"),
"SEI porosity change":"true",
"loss of active material":"stress-driven",
"lithium plating": "partially reversible",
"SEI on cracks":"true",
"thermal":"lumped",
}
def graphite_cracking_rate_Ai2020(T_dim):
k_cr = 3.9e-20
Eac_cr = 0 # to be implemented
arrhenius = exp(Eac_cr / constants.R * (1 / T_dim - 1 / 298.15))
return k_cr * arrhenius

def cracking_rate_Ai2020(T_dim):
k_cr = 3.9e-20
Eac_cr = 0 # to be implemented
arrhenius = exp(Eac_cr / constants.R * (1 / T_dim - 1 / 298.15))
return k_cr * arrhenius

model=pybamm.lithium_ion.DFN(options=options)
param1=pybamm.ParameterValues("OKane2022")`