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samjacobson/Power Usage.ipynb

Last active January 27, 2018 20:06
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Power Usage.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Power Usage\n",
"\n",
"* Battery capacity = 2600 mAh $\\times$ 3 = 7800 mAh\n",
"\n",
"I first tried taking readings using the N6705C (the power supply). I preferred the idea of this machine for testing because you can simply plug the device into it to power it, and get the current readings. The problem, though, was that the current readings were just too noisy. I don't think it was designed for uA level precision (there was at least 100 uA of noise in the readings).\n",
"\n",
"I then moved on to the 34465A Digital Multimeter. This machine is almost perfect for our requirements. I was able to sample the current usage over time and log the data for later analysis.\n",
"\n",
"The only problem I had with this machine was that it struggled with device wakeup. When the device wakes up it goes from drawing about 400uA to about 100mA which causes the 34465A to switch internally (e.g. due to Autorange), unfortunately this switching seems to cause a glitch in the power delivery at a critical time which often leaves the device in a broken state (constant reset, not quite awake). I tried many different settings on the 34465A DMM to avoid this problem, and some seemed to help (disabling Autorange, and decreasing the PLC), but none of them eliminated the issue. For now I've taken readings while the device is running but haven't captured the actual wakeup trace.\n",
"\n",
"Sampling parameters on 34465A DMM:\n",
" * PLC (Power-Line Cycles) 1\n",
" * AutoZero ON (OFF had an impact of about 30-40uA)\n",
" * Period 41ms (minimum period due to above options)\n"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"code_folding": []
},
"outputs": [
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"data": {
"text/plain": [
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"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"# Define units and utility functions\n",
"A = 1.0\n",
"mA = A / 1000\n",
"uA = mA / 1000\n",
"\n",
"def yearsAtDrain(drain, capacity=(7800 * mA)):\n",
" hours = capacity / drain\n",
" years = hours / 24 / 365\n",
" return years\n",
"\n",
"yearsAtDrain(130 * uA)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"code_folding": []
},
"outputs": [
{
"data": {
"text/html": [
"<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
],
"text/vnd.plotly.v1+html": [
"<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Define graph display\n",
"\n",
"import pandas as pd\n",
"import plotly.offline as py\n",
"import plotly.graph_objs as go\n",
"import numpy as np\n",
"\n",
"py.init_notebook_mode(connected=True)\n",
"\n",
"def plot(graphs, **kws):\n",
" layout = go.Layout(**kws)\n",
" fig = go.Figure(data=graphs, layout=layout)\n",
" py.iplot(fig)\n",
"\n",
"def load(csvname):\n",
" with open(csvname) as csv:\n",
" csv.readline() # drop Start date line\n",
" csv.readline() # drop Sample interval line\n",
" return pd.read_csv(csv)\n",
"\n",
"def series(frame, **kws):\n",
" kws.update({\n",
" 'xaxis': { 'title': 'Time (S)' },\n",
" 'yaxis': { 'title': 'Current Draw (A)'},\n",
" })\n",
" time = (frame['Reading #'] * 41) / 1000.0\n",
" plot([go.Scatter(x=time, y=frame['Reading'])], **kws)\n",
"\n",
"def stats(frame):\n",
" # Average here is calculated by simply summing all the readings and dividing by the\n",
" # number of readings. This naive is appropriate since each reading represents the same\n",
" # time period, and we want the average current draw over time\n",
" print(\"Average Current Draw: %d uA\" % (np.average(frame['Reading']) * 1000 * 1000))\n"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
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"layout": {
"title": "Standby with Accelerometer Off",
"xaxis": {
"title": "Time (S)"
},
"yaxis": {
"title": "Current Draw (A)"
}
}
},
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},
"metadata": {},
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},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Average Current Draw: 399 uA\n"
]
}
],
"source": [
"data = load('Sigfox_Standby_AccelerometerOff.csv')\n",
"series(data, title='Standby with Accelerometer Off')\n",
"stats(data)"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
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],
"source": [
"data = load('Sigfox_Standby_AccelerometerFull.csv')\n",
"series(data, title='Standby with Accelerometer On (Full Power Mode)')\n",
"stats(data)"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
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]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Average Current Draw: 81248 uA\n"
]
}
],
"source": [
"data = load('Sigfox_Send_Cycle.csv')\n",
"series(data, title='Active Mode including Sigfox Transmissions')\n",
"stats(data)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
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"text": [
"Average Current Draw: 25023 uA\n"
]
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],
"source": [
"data = load('Sigfox_Standby_AccelerometerOff2.csv')\n",
"series(data, title='Current draw after fixes (idle/active cycles)')\n",
"stats(data)"
]
},
{
"cell_type": "code",
"execution_count": 37,
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"# Define units (resolves to Ampere-Seconds)\n",
"A = 1.0\n",
"mA = A / 1000\n",
"uA = mA / 1000\n",
"s = 1.0\n",
"ms = s/1000\n",
"h = 3600 * s\n",
"m = 60 * s\n",
"\n",
"# Measured, and estimated constants (I = current (A), T = time (s), C = capacity (As), P = percent)\n",
"Cbattery = 2600 * mA * h * 3\n",
"Iactive = 70 * mA\n",
"Itransmit = 450 * mA\n",
"Iidle = 100 * uA\n",
"TsendPoint = 10 * s # 35s to also download ephemerides\n",
"TtransmitPulse = 250 * ms\n",
"Pvampiric = 0.02\n",
"Tephemerides = 6 * m # 5m required, 1 extra for potential noise\n",
"TwakeUpForEphemeridesDays = 1.0\n",
"\n",
"\n",
"# Calculated consumptions (C = consumption (As))\n",
"CtransmitPulse = TtransmitPulse * (Itransmit - Iactive)\n",
"CwakeAndSend = TsendPoint * Iactive + CtransmitPulse * 3\n",
"\n",
"\n",
"def longevity(numPointsPerDay):\n",
" TdailyIdle = 86400 - (TsendPoint * numPointsPerDay)\n",
" TrefreshEphemerides = Tephemerides / TwakeUpForEphemeridesDays\n",
" TdailyIdle -= TrefreshEphemerides\n",
" dailyConsumption = CwakeAndSend * numPointsPerDay + TrefreshEphemerides * Iidle + TdailyIdle * Iidle\n",
" vampiricDrain = Cbattery * Pvampiric\n",
" yearlyConsumption = dailyConsumption * 365 + vampiricDrain\n",
" return Cbattery / yearlyConsumption\n",
"\n",
"#aSTomAh(sendPointUsage)\n",
"longevity(4)"
]
},
{
"cell_type": "code",
"execution_count": 38,
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"<div id=\"a4efd277-dd3c-4557-a262-d1b0436dade9\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"a4efd277-dd3c-4557-a262-d1b0436dade9\", [{\"type\": \"scatter\", \"x\": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], \"y\": [7.558139534883722, 6.891879951697935, 6.33356790992259, 5.85893487568542, 5.450479828566104, 5.095264017419706, 4.783515270452594, 4.507715127814914, 4.26198455485939, 4.041660189647132, 3.842995565774347, 3.662946323748102, 3.499013098869549, 3.3491247906797, 3.211550602508852, 3.0848329048843186, 2.9677353896103895, 2.8592026001637314, 2.7583280288563548, 2.6643287371764943, 2.5765249944946045, 2.4943238143967252, 2.41720554511084, 2.3447128728744775, 2.2764417464394113]}], {\"xaxis\": {\"title\": \"# Points Per Day\"}, \"yaxis\": {\"title\": \"Longevity (years)\"}}, {\"showLink\": true, \"linkText\": \"Export to plot.ly\"})});</script>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Graph of longevity by points per day\n",
"parms = {\n",
" 'xaxis': { 'title': '# Points Per Day' },\n",
" 'yaxis': { 'title': 'Longevity (years)'},\n",
"}\n",
"pointsPerDay = list(range(0, 25))\n",
"plot([go.Scatter(x=pointsPerDay, y=[longevity(p) for p in pointsPerDay])], **parms)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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