{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Cycle ageing example\n", "\n", "This notebook demonstrates how to use the `CycleAgeing` objective function to fit the\n", "outer SEI solvent diffusivity in the \"solvent-diffusion limited\" SEI model using synthetic cycling data." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pybamm\n", "import ionworkspipeline as iwp\n", "import pandas as pd\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We begin by generating some synthetic cycling data. We choose the SPMe model and the \"solvent-diffusion limited\" SEI model and simulate 10 cycles of a CCCV charge/discharge cycle. For the data, we record the cycle number, the loss of lithium inventory, and the capacity. We choose the parameter values so that we get a large loss of lithium inventory even after only 10 cycles." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "model = pybamm.lithium_ion.SPMe({\"SEI\": \"solvent-diffusion limited\"})\n", "parameter_values = pybamm.ParameterValues(\"Chen2020\")\n", "parameter_values.update(\n", " {\n", " \"Outer SEI solvent diffusivity [m2.s-1]\": 2.5e-18,\n", " }\n", ")\n", "\n", "experiment = pybamm.Experiment(\n", " [\n", " (\n", " \"Discharge at 1C until 2.5 V\",\n", " \"Rest for 1 hour\",\n", " \"Charge at C/2 until 4.2 V\",\n", " \"Hold at 4.2 V until 10 mA\",\n", " \"Rest for 1 hour\",\n", " ),\n", " ]\n", " * 10\n", ")\n", "\n", "sim = pybamm.Simulation(\n", " model,\n", " experiment=experiment,\n", " parameter_values=parameter_values,\n", " solver=pybamm.IDAKLUSolver(),\n", ")\n", "\n", "initial_soc = 1\n", "sol = sim.solve(initial_soc=initial_soc)\n", "\n", "\n", "data = {}\n", "for var in [\"Cycle number\", \"Loss of lithium inventory [%]\", \"Capacity [A.h]\"]:\n", " data[var] = sol.summary_variables[var]\n", "\n", "# PyBaMM uses 1-based indexing for cycles but ionworks data format assumes cycles number\n", "# starts at zero \n", "data[\"Cycle number\"] = data[\"Cycle number\"] - 1\n", "\n", "data = pd.DataFrame(data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the synthetic data to see what it looks like." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data.plot(x=\"Cycle number\", y=[\"Loss of lithium inventory [%]\", \"Capacity [A.h]\"], kind=\"line\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we create the objective function. We pass the data and the options to the `CycleAgeing` objective function. The options include the model, experiment, and the objective variables (i.e. the variables we want to fit to). The `CycleAgeing` objective runs the experiment and calculates the cycling data. By default, it uses the function `ionworkspipeline.data_fits.objectives.get_standard_summary_variables` to extract the summary variables from the solution. Custom summary variables can be used by passing a custom function to the `cycle_variables_function` option.\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "\n", "objective = iwp.objectives.CycleAgeing(\n", " data,\n", " options={\n", " \"model\": model,\n", " \"experiment\": experiment,\n", " \"objective variables\": [\"Loss of lithium inventory [%]\"],\n", " \"solver\": pybamm.IDAKLUSolver(),\n", " },\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We then create the data fit. We pass the objective function and the parameters to the `DataFit` class. The parameters include the initial values and bounds for the parameters we want to fit." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "parameters = {\n", " \"Outer SEI solvent diffusivity [m2.s-1]\": iwp.Parameter(\n", " \"Outer SEI solvent diffusivity [m2.s-1]\",\n", " initial_value=1e-19,\n", " bounds=(1e-21, 1e-17),\n", " )\n", "}\n", "data_fit = iwp.DataFit(objective, parameters=parameters)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we run the data fit. We pass the known parameters (i.e. those we are not fitting) to the data fit. " ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'Outer SEI solvent diffusivity [m2.s-1]': 2.500000028043716e-18}" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "known_parameters = {k: v for k, v in parameter_values.items() if k not in parameters}\n", "known_parameters[\"Initial SOC\"] = initial_soc\n", "data_fit.run(known_parameters)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, we plot the fit results." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'CycleAgeing': [(
,\n", " array([],\n", " dtype=object))]}" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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