313 lines
164 KiB
Plaintext
313 lines
164 KiB
Plaintext
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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Battery life model library\n",
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"Example notebook demonstrating how to use the battery life models in Python.\n",
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"\n",
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"First examples use the Kokam NMC111|Gr 75Ah battery life model. The battery modeled here is a high-power cell with long cycle life. Because nominal cell resistance is low, the relative change of resistance at end-of-life is quite high compared to other cell designs (~300% increase in cell resistance at 80% capacity if not more). Fade rates can be changed in the code to accomodate other cell models. Documentation is provided in the life model class. See https://ieeexplore.ieee.org/abstract/document/7963578 for the aging test details and results used to parameterize this model."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"from nmc111_gr_Kokam75Ah_2017 import Nmc111_Gr_Kokam75Ah_Battery\n",
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"from battery_profile import BatProfile"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We instantiate a BatProfile and apply the methods in the specific order to process the intervals for both soc and temperature"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"profile = BatProfile()\n",
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"profile.init_intervals()\n",
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"profile.preprocess_soc_intervals()\n",
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"profile.temp_sequence_generation()\n",
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"profile.process_soc_time()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"After the pre-processing done earlier, we can execute `generate_day_values(number_of_discharges)` to generate curves"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"soc_day_sequence, temp_day_sequence, time_day_sequence = profile.generate_day_values(4)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[<matplotlib.lines.Line2D at 0x7fb0bbb44820>]"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"plt.plot(time_day_sequence, soc_day_sequence)\n",
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"plt.plot(time_day_sequence, temp_day_sequence)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"To run, the life model needs timeseries data: the time in seconds since beginning-of-life of the battery, the state-of-charge of the battery (0 to 1), and the ambient temperature (or battery temperature, if you have a thermal model)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Set the `expected_rate` (expected number of discharges per day) and the `number_of_years` (number of years to simulate).\n",
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"\n",
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"The code below will simulate one day at a time for the given time. \n",
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"\n",
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"It should not take more than 20s.\n",
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"\n",
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"There might be occasional runtime warnings"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"# expected_rate parameter is the expected number of discharges per day\n",
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"expected_rate = 42 / 236.0\n",
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"number_of_years = 30\n",
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"# 1 year simulation\n",
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"cell = Nmc111_Gr_Kokam75Ah_Battery()\n",
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"total_day_time = 60 * 60 * 24\n",
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"t_days = np.arange(365 * number_of_years)\n",
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"for day in t_days:\n",
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" num_discharges = np.random.poisson(expected_rate, 1)\n",
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" soc_day_sequence, temp_day_sequence, time_day_sequence = profile.generate_day_values(num_discharges)\n",
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" cell.update_battery_state(\n",
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" t_secs=np.array([total_day_time * day + time for time in time_day_sequence]),\n",
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" soc = (soc_day_sequence)/100, # from 0 to 1\n",
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" T_celsius=temp_day_sequence\n",
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" )"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.plot(cell.stressors['t_days']/365, cell.outputs['q'])\n",
|
||
|
|
"plt.xlabel('Time (years)')\n",
|
||
|
|
"plt.ylabel('Relative discharge capacity')\n",
|
||
|
|
"plt.ylim((0.7, 1.02))\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"The battery model should be run in timesteps relavent to battery degradation, such as once per day. Larger or smaller timesteps could be used if desired, but timesteps should avoid splitting up cycles, or at least be long enough that miscounting cycles due to splitting them up does not introduce much error.\n",
|
||
|
|
"\n",
|
||
|
|
"Each battery model tracks the history of it's inputs (`stressors`), calculated degradation rates (`rates`), internal states (`states`), and outputs (`outputs`) each time `update_battery_state` is called. Debugging models is easier because the values of all inputs, internal calculations, and outputs are tracked."
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"The cell resistance and capacity trajectories are wiggily because the temperature of the battery is varying throughout each year, varying the degradation rate. Dispatch is the same each day, so that is constant.\n",
|
||
|
|
"\n",
|
||
|
|
"The model keeps track of how much charge-throughput has occured throughout life, as well, based on the input state-of-charge timeseries. Conversion from charge-throughput, in Amp-hours, to changes of cell state-of-charge, which is dependent on battery performance (health, temperature and SOC dependent resistances), is assumed to happen externally to the model. This simple simulation is essentially assuming that the current magnitude is continuously being adjusted based on the the state-of-health of the battery."
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 7,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.plot(cell.stressors['efc'], cell.outputs['q'])\n",
|
||
|
|
"plt.xlabel('Equivalent full cycles')\n",
|
||
|
|
"plt.ylabel('Relative discharge capacity')\n",
|
||
|
|
"plt.ylim((0.7, 1.02))\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"This dispatch has a little more than 1 EFC per day.\n",
|
||
|
|
"\n",
|
||
|
|
"We can plot the separate contributions to capacity or resistance fade, as well."
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"(0.5, 1.02)"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 8,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.plot(cell.stressors['t_days']/365, cell.outputs['q_LLI'])\n",
|
||
|
|
"plt.plot(cell.stressors['t_days']/365, cell.outputs['q_LAM'])\n",
|
||
|
|
"plt.plot(cell.stressors['t_days']/365, cell.outputs['q'], '--k')\n",
|
||
|
|
"plt.xlabel('Time (years)')\n",
|
||
|
|
"plt.ylabel('Relative discharge capacity')\n",
|
||
|
|
"plt.legend([r'q$_{LLI}$', r'q$_{LAM}$', 'q'])\n",
|
||
|
|
"plt.ylim((0.5, 1.02))"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"attachments": {},
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"From the result, the cell will experience sudden failure very shortly; considering this is near 70% remaining capacity, this is physically reasonable."
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 9,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.plot(cell.stressors['t_days']/365, cell.outputs['r_LLI'])\n",
|
||
|
|
"plt.plot(cell.stressors['t_days']/365, cell.outputs['r_LAM'])\n",
|
||
|
|
"plt.plot(cell.stressors['t_days']/365, cell.outputs['r'], '--k')\n",
|
||
|
|
"plt.xlabel('Time (years)')\n",
|
||
|
|
"plt.ylabel('Relative DC resistance')\n",
|
||
|
|
"plt.legend([r'r$_{LLI}$', r'r$_{LAM}$', 'r'])\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "base",
|
||
|
|
"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": "3.10.12"
|
||
|
|
},
|
||
|
|
"orig_nbformat": 4,
|
||
|
|
"vscode": {
|
||
|
|
"interpreter": {
|
||
|
|
"hash": "e4cce46d6be9934fbd27f9ca0432556941ea5bdf741d4f4d64c6cd7f8dfa8fba"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 2
|
||
|
|
}
|