Could not solve for summary variables error for certain experiment values

[LostCorgi]

• PyBaMM version - $ python -m pip show pybamm:
  Name: pybamm
  Version: 21.11
  Summary: Python Battery Mathematical Modelling.
  Home-page: https://github.com/pybamm-team/PyBaMM
  Author: None
  Author-email: None
  License: UNKNOWN
  Location: /usr/local/lib/python3.7/dist-packages
  Requires: pybtex, jupyter, casadi, imageio, pandas, anytree, scikit-fem, sympy, matplotlib, numpy, scipy, autograd

Required-by:

• Python version - $ python --version:
  Python 3.7.12

Describe the bug
Could not solve for summary variables when using certain values in the experiment steps.

To Reproduce
Steps to reproduce the behaviour:

1. Use parameters as listed (same as used for HW5 for 24643/27700)

{'1 + dlnf/dlnc': 1.0,
'Ambient temperature [K]': 298.15,
'Cation transference number': 0.2594,
'Current function [A]': 5.0,
'Electrode height [m]': 0.065,
'Electrode width [m]': 1.58,
'Electrolyte conductivity [S.m-1]': <function electrolyte_conductivity_Nyman2008 at 0x7fb443d06050>,
'Electrolyte diffusivity [m2.s-1]': <function electrolyte_diffusivity_Nyman2008 at 0x7fb443ce25f0>,
'Initial concentration in electrolyte [mol.m-3]': 1000.0,
'Initial concentration in negative electrode [mol.m-3]': 30170.0,
'Initial concentration in positive electrode [mol.m-3]': 16653.0,
'Initial temperature [K]': 298.15,
'Lower voltage cut-off [V]': 2.5,
'Maximum concentration in negative electrode [mol.m-3]': 33133.0,
'Maximum concentration in positive electrode [mol.m-3]': 63104.0,
'Negative electrode Bruggeman coefficient (electrode)': 1.5,
'Negative electrode Bruggeman coefficient (electrolyte)': 1.5,
'Negative electrode OCP entropic change [V.K-1]': 0.0,
'Negative electrode active material volume fraction': 0.75,
'Negative electrode conductivity [S.m-1]': 215.0,
'Negative electrode diffusivity [m2.s-1]': 3.3e-14,
'Negative electrode electrons in reaction': 1.0,
'Negative electrode exchange-current density [A.m-2]': <function graphite_LGM50_electrolyte_exchange_current_density_Chen2020 at 0x7fb443d060e0>,
'Negative electrode porosity': 0.25,
'Negative electrode thickness [m]': 8.52e-05,
'Negative particle radius [m]': 5.86e-06,
'Nominal cell capacity [A.h]': 5.0,
'Number of cells connected in series to make a battery': 1.0,
'Number of electrodes connected in parallel to make a cell': 1.0,
'Positive electrode Bruggeman coefficient (electrode)': 1.5,
'Positive electrode Bruggeman coefficient (electrolyte)': 1.5,
'Positive electrode OCP entropic change [V.K-1]': 0.0,
'Positive electrode active material volume fraction': 0.665,
'Positive electrode conductivity [S.m-1]': 0.18,
'Positive electrode diffusivity [m2.s-1]': 4e-15,
'Positive electrode electrons in reaction': 1.0,
'Positive electrode exchange-current density [A.m-2]': <function nmc_LGM50_electrolyte_exchange_current_density_Chen2020 at 0x7fb443d06170>,
'Positive electrode porosity': 0.335,
'Positive electrode thickness [m]': 7.56e-05,
'Positive particle radius [m]': 5.22e-06,
'Reference temperature [K]': 298.15,
'Separator Bruggeman coefficient (electrolyte)': 1.5,
'Separator porosity': 0.47,
'Separator thickness [m]': 1.2e-05,
'Typical current [A]': 5.0,
'Typical electrolyte concentration [mol.m-3]': 1000.0,
'Upper voltage cut-off [V]': 4.2}

3. add following RK polynomial functions for electrode voltage

nmc_params = [    7.52708209,     7.94586208,     8.12577489,     7.15626014,
           8.89795867,    23.44057239,    11.52212408,  -125.12125392,
        -150.18406158,   518.15073251,  1051.9467633 ,  -599.50608226,
       -2720.48892608, -1045.56180925,  2431.91011101,  2649.56138638,
         791.10566913]

gra_params = [-5.68802700e-01,  2.71233533e-01, -6.96758627e-01, -8.31413849e-02,
        2.45114013e+00,  3.93196117e+00, -3.12695424e+01, -2.64271082e+01,
        1.70107514e+02,  1.16180944e+02, -5.25943391e+02, -2.66184769e+02,
        8.99407315e+02,  3.01567717e+02, -8.02709948e+02, -1.30203735e+02,
        2.89125187e+02]

k = 8.617e-5
T = 298.15
def pyb_rk(order, params):
    def rk_term(x, a, k):
        f2 = -2*k*x*(1-x)*(1-2*x)**(k-1)
        f1 = (1-2*x)**(k+1)
        return a*(f1+f2)
    def base_term(x):        
        val = k * T * pybamm.log(x/(1-x))
        return val
    def rk_fun(x):
        RK = 0
        for ct in range(order+1):
            RK += (rk_term(x, params[ct], ct))
        return RK + base_term(x)
    return rk_fun

def f_nmc_rk(x):
    return -(pyb_rk(16, nmc_params))(x)

def f_gra_rk(x):
    return -(pyb_rk(16, gra_params))(x)
 
parameter_values.update({'Negative electrode OCP [V]': f_gra_rk}, check_already_exists=False)
parameter_values.update({'Positive electrode OCP [V]': f_nmc_rk}, check_already_exists=False)

4. Define experiment as follows, where total_cells is 8000, 15500, or certain other values

full_wattage = [
                419875.07810354204,
                290671.67288570706,
                178324.67752738303,
                105603.195907928,
                -12925.2048255579,
                195046.73170923634,
                419875.07810354204
                ]
cell_wattage =  np.array(full_wattage)/total_cells
experiment = pybamm.Experiment(
    [
     "Discharge at {} W for 15.0 s".format(cell_wattage[0]),
     "Discharge at {} W for 30.0 s".format(cell_wattage[1]),
     "Discharge at {} W for 108.109091 s".format(cell_wattage[2]),
     "Discharge at {} W for 1431.639227 s".format(cell_wattage[3]),
     "Discharge at {} W for 108.10909100000003 s".format(cell_wattage[4]),
     "Discharge at {} W for 30.0 s".format(cell_wattage[5]),
     "Discharge at {} W for 45.45454500000005 s".format(cell_wattage[6])
    ]
)

4. Make model and run sim

model = pybamm.lithium_ion.DFN()
sim_mission = pybamm.Simulation(model, experiment=experiment, parameter_values=parameter_values)
mission_sol = sim_mission.solve()

5. Error appears
   SolverError: Could not solve for summary variables, run `sim.solve(calc_esoh=False)` to skip this step

Expected behaviour
Would've expected the simulation to run for this number of cells, it can run some values above and below without adding calc_esoh = False.

Additional context
Running on Collab and ran this pip install jax==0.2.11 after pip install pybamm to fix compatibility issue.
Error is resolved by setting calc_esoh = False