{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Heuristic model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will fit our heuristic model by using experimental data from the [Lei et al.](https://doi.org/10.1016/j.jallcom.2014.09.169) paper for the LFP system.\n", "\n", "First, we import the libraries that we will use throughout this example:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import galpynostatic as gp\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data visualization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We define a [numpy](https://numpy.org/) array with the C-rates that were used to perform the measurements in the experiment." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "C_rates = np.array([0.2, 0.5, 1, 2, 5, 10])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For each one of these C-rates we have a galvanostatic profile as a csv file, which we read with [pandas](https://pandas.pydata.org/) and store in a list for further preprocessing." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['capacity', 'voltage'], dtype='object')" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gprofiles = [pd.read_csv(f\"../_static/{c_rate}C.csv\") for c_rate in C_rates]\n", "gprofiles[0].keys()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "we have a pd.DataFrame for each curve with a capacity and a voltage column. We also define from their work the equilibrium potential and our choice for the cut-off potential (which is that of the distributed map datasets)." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "eq_pot, vcut = 3.45, 0.15" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We plot the curves to visualize them in the region of interest:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "for c_rate, df in zip(C_rates, gprofiles):\n", " ax.scatter(df.capacity, df.voltage, s=10, label=f\"{c_rate}\")\n", " \n", "ax.set_xlim((0, 180))\n", "ax.set_ylim((eq_pot - vcut, eq_pot + vcut))\n", "ax.set_xlabel(r\"Specific Capacity (mAh g$^{-1}$)\")\n", "ax.set_ylabel(r\"Potential (V vs. Li$^+$/Li)\")\n", "ax.legend(title=\"C rate\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Data preprocessing" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the physics-based heuristic model presented here, we are not interested in the complete behavior of the profile, but focus our analysis on the points where each curve intersects at a cut-off potential below the equilibrium potential. To obtain these values we can use the `galpynostatic.preprocessing` module." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([160.27912017, 141.21537819, 128.30040942, 55.62272794,\n", " 3.53156547, 1.62308932])" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gdc = gp.preprocessing.GetDischargeCapacities(eq_pot=eq_pot, vcut=vcut)\n", "dc = gdc.fit_transform(gprofiles)\n", "dc" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We need to normalize these currents by a maximum value that we define (here we use the maximum value of the capacity for the lowest C-rate reported in the paper, which is 168.9 mAh g$^{-1}$) to obtain the maximum SOC value between 0 and 1, which will be the target values for the fitting of our model." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "soc = dc / 168.9" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Model fitting" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, the data is displayed in the form it will be used by the model." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots()\n", "\n", "plt.plot(C_rates, soc, marker=\"s\", ls=\"--\")\n", "\n", "plt.xlabel(\"C-rate\")\n", "plt.ylabel(\"maximum SOC value\")\n", "plt.xscale(\"log\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "and reshape the C-rate values according to the [scikit-learn](https://scikit-learn.org/stable/) convention." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "C_rates = C_rates.reshape(-1, 1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the paper it is mentioned that the particle sizes are distributed between 200-500 nm, we take the center and give it in cm, which is the required unit for this parameter." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "d = 3.5e-5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We use the default surface data for spherical geometry with a cut-off potential of 150 mV and the corresponding default z-value of 3." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
GalvanostaticRegressor(d=3.5e-05,\n",
       "                       dataset=         l   xi     xmax\n",
       "0    -4.00  2.0  0.99706\n",
       "1    -4.00  1.9  0.99706\n",
       "2    -4.00  1.8  0.99705\n",
       "3    -4.00  1.7  0.99705\n",
       "4    -4.00  1.6  0.99705\n",
       "...    ...  ...      ...\n",
       "1339  1.75 -3.1  0.00000\n",
       "1340  1.75 -3.2  0.00000\n",
       "1341  1.75 -3.3  0.00000\n",
       "1342  1.75 -3.4  0.00000\n",
       "1343  1.75 -3.5  0.00000\n",
       "\n",
       "[1344 rows x 3 columns])
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" ], "text/plain": [ "GalvanostaticRegressor(d=3.5e-05,\n", " dataset= l xi xmax\n", "0 -4.00 2.0 0.99706\n", "1 -4.00 1.9 0.99706\n", "2 -4.00 1.8 0.99705\n", "3 -4.00 1.7 0.99705\n", "4 -4.00 1.6 0.99705\n", "... ... ... ...\n", "1339 1.75 -3.1 0.00000\n", "1340 1.75 -3.2 0.00000\n", "1341 1.75 -3.3 0.00000\n", "1342 1.75 -3.4 0.00000\n", "1343 1.75 -3.5 0.00000\n", "\n", "[1344 rows x 3 columns])" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "greg = gp.model.GalvanostaticRegressor(d=d)\n", "greg.fit(C_rates, soc)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Two types of plots are available, one to visualize the region of the map where the experimental data are located after the fitting" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "greg.plot.in_render_map(C_rates)\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "and another to visualize the predicted versus experimental values in the same format as used for the fitting." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "greg.plot.versus_data(C_rates, soc)\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Predictions" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can obtain fundamental parameters of the system by accessing attributes of the `GalvanostaticRegressor` model, such as the diffusion coefficient (with its uncertainty)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2.85e-13 +/- 1e-14 cm^2/s\n" ] } ], "source": [ "print(f\"{greg.dcoeff_:.2e} +/- {greg.dcoeff_err_:.0e} cm^2/s\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "which in this case is in good agreement with the three values of 1.04e-12, 1.74e-13 and 8.22e-13 (EIS measurements) reported in their paper. In addition, we can obtain the kinetic rate constant" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.00e-09 +/- 3e-11 cm/s\n" ] } ], "source": [ "print(f\"{greg.k0_:.2e} +/- {greg.k0_err_:.0e} cm/s\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "which is also in good agreement with the experimental value of 1.23e-9, calculated using the [Butler-Volmer equation](https://en.wikipedia.org/wiki/Butler%E2%80%93Volmer_equation) with the reported exchange current density value." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, there is a fast-charging criteria, proposed by the _United States Advanced Battery Consortium_ (USABC), which aims for an extremely fast-charging of 80% SOC (State-of-Charge) in 15 minutes. This corresponds to a maximum SOC value of 0.8 and a C-rate of 4C. A prediction of the particle size needed to meet this criterion can be quickly made using the `optimal_particle_size` function in the `galpynostatic.make_prediction` module (which has the default values of the criterion defined)." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.084 +/- 0.002 micrometers\n" ] } ], "source": [ "d_new, d_new_err = gp.make_prediction.optimal_particle_size(greg, d0=1e-5)\n", "print(f\"{d_new:.3f} +/- {d_new_err:.3f} micrometers\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This predicted value can be compared to the original value (d)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.35" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "1e4 * d" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "where it can be seen that our model predicts that the system should be improved by reducing the particle size by about an order of magnitude." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 4 }