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pybamm-team#1056 added examples on how to pass custom drive cycle
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brosaplanella committed Jul 28, 2020
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121 changes: 98 additions & 23 deletions examples/notebooks/Getting Started/Tutorial 4 - Setting parameter values.ipynb
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" 'EC initial concentration in electrolyte [mol.m-3]': 4541.0,\n",
" 'Electrode height [m]': 0.065,\n",
" 'Electrode width [m]': 1.58,\n",
" 'Electrolyte conductivity [S.m-1]': <function electrolyte_conductivity_Nyman2008 at 0x7f234684e1e0>,\n",
" 'Electrolyte diffusivity [m2.s-1]': <function electrolyte_diffusivity_Nyman2008 at 0x7f2391b5a268>,\n",
" 'Electrolyte conductivity [S.m-1]': <function electrolyte_conductivity_Nyman2008 at 0x7f9afbc630d0>,\n",
" 'Electrolyte diffusivity [m2.s-1]': <function electrolyte_diffusivity_Nyman2008 at 0x7f9afbc63048>,\n",
" 'Initial concentration in electrolyte [mol.m-3]': 1000.0,\n",
" 'Initial concentration in negative electrode [mol.m-3]': 29866.0,\n",
" 'Initial concentration in positive electrode [mol.m-3]': 17038.0,\n",
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" 'Negative electrode diffusivity [m2.s-1]': 3.3e-14,\n",
" 'Negative electrode double-layer capacity [F.m-2]': 0.2,\n",
" 'Negative electrode electrons in reaction': 1.0,\n",
" 'Negative electrode exchange-current density [A.m-2]': <function graphite_LGM50_electrolyte_exchange_current_density_Chen2020 at 0x7f23886d5ea0>,\n",
" 'Negative electrode exchange-current density [A.m-2]': <function graphite_LGM50_electrolyte_exchange_current_density_Chen2020 at 0x7f9afbc9bea0>,\n",
" 'Negative electrode porosity': 0.25,\n",
" 'Negative electrode specific heat capacity [J.kg-1.K-1]': 700.0,\n",
" 'Negative electrode surface area to volume ratio [m-1]': 383959.0,\n",
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" 'Positive electrode diffusivity [m2.s-1]': 4e-15,\n",
" 'Positive electrode double-layer capacity [F.m-2]': 0.2,\n",
" 'Positive electrode electrons in reaction': 1.0,\n",
" 'Positive electrode exchange-current density [A.m-2]': <function nmc_LGM50_electrolyte_exchange_current_density_Chen2020 at 0x7f234684e0d0>,\n",
" 'Positive electrode exchange-current density [A.m-2]': <function nmc_LGM50_electrolyte_exchange_current_density_Chen2020 at 0x7f9afbc9bf28>,\n",
" 'Positive electrode porosity': 0.335,\n",
" 'Positive electrode specific heat capacity [J.kg-1.K-1]': 700.0,\n",
" 'Positive electrode surface area to volume ratio [m-1]': 382184.0,\n",
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"output_type": "stream",
"text": [
"EC initial concentration in electrolyte [mol.m-3]\t4541.0\n",
"Electrolyte conductivity [S.m-1]\t<function electrolyte_conductivity_Nyman2008 at 0x7f234684e1e0>\n",
"Electrolyte diffusivity [m2.s-1]\t<function electrolyte_diffusivity_Nyman2008 at 0x7f2391b5a268>\n",
"Electrolyte conductivity [S.m-1]\t<function electrolyte_conductivity_Nyman2008 at 0x7f9afbc630d0>\n",
"Electrolyte diffusivity [m2.s-1]\t<function electrolyte_diffusivity_Nyman2008 at 0x7f9afbc63048>\n",
"Initial concentration in electrolyte [mol.m-3]\t1000.0\n",
"Negative electrode Bruggeman coefficient (electrolyte)\t1.5\n",
"Positive electrode Bruggeman coefficient (electrolyte)\t1.5\n",
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"cell_type": "markdown",
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"source": [
"You can also simulate drive cycles by passing the data directly"
"### Drive cycle"
]
},
{
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"source": [
"You can also simulate the PyBaMM default drive cycles by calling the dataset directly"
]
},
{
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"Then we can just define the model and solve it"
"Then we can just define the model and solve it. In this case we do not need to specify a time interval to solve as PyBaMM automatically picks it from data"
]
},
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"sim.plot([\"Current [A]\", \"Terminal voltage [V]\"])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Alternatively, you can implement your own drive cycles importing the dataset and creating an interpolant to pass as the current function."
]
},
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"execution_count": 13,
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"source": [
"import pandas as pd # needed to read the csv data file\n",
"\n",
"# Import drive cycle from file\n",
"drive_cycle = pd.read_csv(\"../../../pybamm/input/drive_cycles/US06.csv\", comment=\"#\", header=None).to_numpy()\n",
"\n",
"# Create interpolant\n",
"timescale = parameter_values.evaluate(model.timescale)\n",
"current_interpolant = pybamm.Interpolant(drive_cycle, timescale * pybamm.t)\n",
"\n",
"# Set drive cycle\n",
"parameter_values[\"Current function [A]\"] = current_interpolant"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Then, again, the model can be solved as usual but notice that now we do need to pass `t_eval` to the solver."
]
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"text/plain": [
"interactive(children=(FloatSlider(value=0.0, description='t', max=600.0, step=6.0), Output()), _dom_classes=('…"
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}
],
"source": [
"model = pybamm.lithium_ion.SPMe()\n",
"sim = pybamm.Simulation(model, parameter_values=parameter_values)\n",
"t_eval = drive_cycle[:, 0] # define t_eval from the dataset\n",
"sim.solve(t_eval)\n",
"sim.plot([\"Current [A]\", \"Terminal voltage [V]\"])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Custom current function"
]
},
{
"cell_type": "markdown",
"metadata": {},
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