Design_Justification.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# Snowflake - Design Justification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What does it do?\n",
    "\n",
    "This Christmas decoration has an LED in the centre and two rings of six LEDs. The idea is to blink them, following the pattern centre - inner ring - outer ring - pause.\n",
    "\n",
    "### LED sequence\n",
    "\n",
    "To alternate between LEDs, we use a decade counter. The `HC4017` is a Johnson counter with 10 decoded outputs. Only one output is high at a time, and the each output is sequentially selected on the low-to-high edge of the clock signal.\n",
    "\n",
    "<img src=\"img/Counter.png\" width=\"300px\" align=\"center\">\n",
    "\n",
    "In order to cycle through the different elements, the central LED (LED0) is connected to output 1, the inner ring is connected to output 2 and the outer ring is connected to output 3. Output 0 is left unconnected to provide a pause between cycles (and also reduce a bit the average battery draw). Output 4 is connected to the reset pin, so as soon as it gets active, the counter resets and the cycle starts again.\n",
    "\n",
    "### Clock Generation\n",
    "\n",
    "To generate the clock signal, we use an Op Amp in astable vibrator configuration. It's made by two elements, a Schmitt trigger and an RC circuit connected to the inverting pin of the opamp. Because we are using a single rail to power the op amp, we have to bias the non-inverting pin.\n",
    "\n",
    "<img src=\"img/Clock.png\" width=\"400px\" align=\"center\">\n",
    "\n",
    "#### Schmitt Trigger\n",
    "\n",
    "The Schmitt trigger is formed by the opamp U1A and R3 as feedback resistor and R1 and R2 used as voltage divider to set the bias point. The opamp is powered by the battery directly and V- is connected to GND. As the voltage of the battery will drop, I decided not to use a voltage reference for the bias, because as VDD drops, the ratio between VDD and Vbias would change. The voltage divider affects the Schmitt trigger, by changing the value of the threshold levels, but we need hysteresis anyway.\n",
    "\n",
    "The analysis is pretty simple. If Vout (labelled CLK) is high, the equivalent circuit is \n",
    "\n",
    "<img src=\"img/Schmitt_OutputHigh.png\" width=\"200px\" align=\"center\">\n",
    "\n",
    "Doing some basic Kirchoff...\n",
    "\n",
    "$$\n",
    "\\frac{(VDD - Vbias)}{(R1 // R3)} = \\frac{Vbias}{R2} \\Rightarrow \\frac{Vdd}{Vbias} - 1 = \\frac{(R1 // R3)}{R2} \\Rightarrow Vbias = \\frac{Vdd}{\\frac{(R1//R3)}{R2}+1}\n",
    "$$\n",
    "\n",
    "Similarly, when the output is low\n",
    "\n",
    "<img src=\"img/Schmitt_OutputLow.png\" width=\"200px\" align=\"center\">\n",
    "\n",
    "$$\n",
    "\\frac{(VDD - Vbias)}{R1} = \\frac{Vbias}{(R2 // R3)} \\Rightarrow \\frac{Vdd}{Vbias} - 1 = \\frac{R1}{(R2 // R3)} \\Rightarrow Vbias = \\frac{Vdd}{\\frac{R1}{(R2 // R3)}+1}\n",
    "$$\n",
    "\n",
    "If $R1 = R2$, $Vbias = VDD/2$ . It's easy to see how in that case, when the output is low, the feedback resistor pushes the threshold voltage (Vbias) up from whatever the R1 - R2 voltage divider would set by appearing in parallel to R1 (thus, decreasing its value and typing the balance towards R2). In the same way, when the output is high, by appearing in parallel to R2, it lowers Vbias.\n",
    "\n",
    "The following code shows an interactive plot that allows changing the values of R1, R2 and R3 and see how they impact the threshold levels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "interactive(children=(IntSlider(value=10000, description='R1 (Ω):', max=50000, min=1000, readout_format='.2d',…"
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     "output_type": "display_data"
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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\" Schmitt Trigger interactive plot\n",
    "\"\"\"\n",
    "%matplotlib widget\n",
    "from ipywidgets.widgets import IntSlider, FloatSlider, Textarea\n",
    "from ipywidgets import interact\n",
    "from math import ceil, exp\n",
    "from matplotlib.lines import Line2D\n",
    "from matplotlib.pyplot import figure\n",
    "from numpy import float64, linspace, pi, sign, sin, array, greater\n",
    "from numpy.typing import NDArray\n",
    "from scipy import signal\n",
    "from scipy.signal import argrelextrema\n",
    "from typing import Sequence\n",
    "\n",
    "def ThresholdCalculator(Vdd:float, R1: int, R2: int, Rf: int)-> tuple[float, float]:\n",
    "    \"\"\" Calculates the threshold voltage on a Schmitt trigger (single rail,\n",
    "    biased with a voltage divider, ideal rail to rail opamp)\n",
    "    Parameters:\n",
    "    -----------\n",
    "        VoutH: float\n",
    "            The value of VoutH when the opamp is saturated high\n",
    "        VoutL: float\n",
    "            The value of VoutH when the opamp is saturated low\n",
    "        Vdd: floag\n",
    "            the power supply voltage\n",
    "        R1: int\n",
    "            top resistor of the voltage divider\n",
    "        R2: int\n",
    "            bottom resistor of the voltage divider\n",
    "        Rf: int\n",
    "            feedback resistor\n",
    "    Return\n",
    "    ------\n",
    "        VthL: float\n",
    "            the threshold value when the output is LOW\n",
    "        VthH: float\n",
    "            the thershokd value when the output is HIGH\n",
    "    \"\"\"\n",
    "    parallelR1Rf:float= (R1 * Rf) / (R1 + Rf)\n",
    "    parallelR2Rf:float= (R2 * Rf) / (R2 + Rf)\n",
    "    ratioH:float = (parallelR1Rf / R2) + 1\n",
    "    ratioL:float = (R1 / parallelR2Rf) + 1\n",
    "    VthH:float = Vdd / ratioH\n",
    "    VthL:float = Vdd / ratioL\n",
    "    return VthL, VthH\n",
    "\n",
    "def ThresholdSignal(Vout: Line2D, VthL: float, VthH:float, Vdd: float)-> Sequence[float]:\n",
    "    \"\"\" Calculates the threshold voltage signanl on a Schmitt trigger (single rail,\n",
    "    biased with a voltage divider)\n",
    "    Parameters:\n",
    "    -----------\n",
    "        Vout: float\n",
    "            a line 2D with the values of the output signal of the opAmp, as\n",
    "            they determine the threshold value\n",
    "        VthL: float\n",
    "            the threshold value when the output is LOW\n",
    "        VthH: float\n",
    "            the thershokd value when the output is HIGH\n",
    "        Vdd: int\n",
    "            the power supply voltage\n",
    "    Return\n",
    "    ------\n",
    "        returnArray: Sequence[float]\n",
    "            a sequence with the values of the Schmitt Trigger thresholds, depending\n",
    "            on the values of the resistor network, Vdd and the current output of\n",
    "            the OpAmp\n",
    "    \"\"\"\n",
    "    returnArray:Sequence[float] = []\n",
    "    # extrac data from Vout (line2D) to array\n",
    "    voltages:Sequence[float] = Vout.get_ydata()\n",
    "    for i in range(len(voltages)):\n",
    "        if voltages[i] > (Vdd / 2):\n",
    "            returnArray.append(VthH)\n",
    "        else:\n",
    "            returnArray.append(VthL)\n",
    "    return returnArray\n",
    "\n",
    "def capacitor_voltage(t:float, R: int, C: float, Vapplied:float)->float:\n",
    "    \"\"\" Calculates the voltage of a capacitor (Vout) in an RC filter after\n",
    "    time = t seconds, when Vapplied volts are applied at the input\n",
    "    Parameters:\n",
    "    -----------\n",
    "        t: float\n",
    "            time elapsed in seconds since Vapplied was applied at the input of\n",
    "            the RC filter\n",
    "        R: int\n",
    "            The value of the resistor (in Ω) of the RC filter\n",
    "        C: float\n",
    "            The value of the capacitor (in Farads) of the RC filter\n",
    "        Vapplied: float\n",
    "            The voltage (in Volts) applied at the input\n",
    "    Retunr\n",
    "    --------\n",
    "        cap_Volt: float\n",
    "            The voltage in the capacitor in Volts (Vout of the RC filter)\n",
    "    \"\"\"\n",
    "    cap_volt = Vapplied * (1 - exp (-t/(R*C)))\n",
    "    return cap_volt\n",
    "\n",
    "def astable_vibrator_signals(times:NDArray[float64], Rd1:int, Rd2:int, Rf:int, Rc:int, C:float, Vdd:float)->tuple[Sequence[float], Sequence[float], Sequence[float]]:\n",
    "    \"\"\" Calculates the values of the signals of interest on an Astable Multivibrator: the\n",
    "    voltages at the inverting and non inverting pins and the output signal. The amplifier\n",
    "    is ideal, powered with a single rail and biased with a voltage divider.\n",
    "    The calculations are based on the values of the feedback resistor Rf, the values of the\n",
    "    resistors on the voltage divider and the values of the RC filter in the non-inverting pin\n",
    "    as well as the Vdd voltage.\n",
    "    Parameters:\n",
    "    -----------\n",
    "        times: NDArray[float64]\n",
    "            A sequence of values for the time at wich the values of the signals has to be calculated\n",
    "        Rd1:int\n",
    "            The value of the voltage divider resistor connected to VDD\n",
    "        Rd2:int\n",
    "            The value of the voltage divider resistor connected to GND\n",
    "        Rf:int\n",
    "            The value of the feedback resistor connected from out to v+.\n",
    "        Rc: int\n",
    "            The value of the resistor (in Ω) connected to the RC filter\n",
    "        C: float\n",
    "            The value of the capacitor (in Farads) in the RC filter\n",
    "        Vdd: float\n",
    "            the voltage applied to the capacitor. It's constant for all the values in times\n",
    "    Return\n",
    "    ------\n",
    "        [vi_signal, vo_signal, vf_signal]: tuple[Sequence[float],Sequence[float],Sequence[float]\n",
    "            Sequences with the values of voltage at the inverting, output and non-inverting\n",
    "            pins of the OpAmp, respectively.\n",
    "    \"\"\"\n",
    "    vi_signal:Sequence[float] = [0.0] * len(times)\n",
    "    vo_signal:Sequence[float] = [0.0] * len(times)\n",
    "    vf_signal:Sequence[float] = [0.0] * len(times)\n",
    "\n",
    "    # Get the schimtt trigger thresholds for this config\n",
    "    thresholdl, thresholdh = ThresholdCalculator(Vdd, Rd1, Rd2, Rf)\n",
    "\n",
    "    #initial conditions\n",
    "    vi_signal[0] = 0 # capacitor starts discharged\n",
    "    # vi below threshold, so vo is HIGH\n",
    "    vo_signal[0] = Vdd\n",
    "    # vo is HIGH so Vthreshold is VthH\n",
    "    vf_signal[0] = thresholdh\n",
    "    start_t = times[0]\n",
    "    start_v = 0\n",
    "    rising = False # an aux variable to keep track if we are charging or discharging C\n",
    "    if vi_signal[0] < vf_signal[0]:\n",
    "        rising = True\n",
    "\n",
    "    for i in range(1, len(times)): #skip times[0] as we have entered the initial conditions by hand\n",
    "        if vi_signal[i - 1] < vf_signal[i-1]:\n",
    "            # If v- < v+, the voltage at the cap is below trheshold\n",
    "            # We will charge the capacitor\n",
    "            time = times[i]\n",
    "            vi_signal[i] = capacitor_voltage(time-start_t, Rc, C, Vdd - start_v) + start_v\n",
    "            vf_signal[i] = thresholdh\n",
    "            vo_signal[i] = Vdd\n",
    "        else: # vi_signal[i - 1] >= vf_signal[i-1]:\n",
    "            # Else, the voltage at the cap is above the trheshold\n",
    "            # We will discharge the capacitor\n",
    "            time = times[i]\n",
    "            vi_signal[i] = capacitor_voltage(time-start_t, Rc, C, 0 - start_v) + start_v\n",
    "            vf_signal[i] = thresholdl\n",
    "            vo_signal[i] = 0\n",
    "        # after updating the values, check if we switched the thresholds\n",
    "        if (vi_signal[i] >= vf_signal[i]) and rising:\n",
    "            start_v = thresholdh\n",
    "            start_t = times[i]\n",
    "            rising = False\n",
    "        elif (vi_signal[i] <= vf_signal[i]) and not rising:\n",
    "            start_v = thresholdl\n",
    "            start_t = times[i]\n",
    "            rising = True\n",
    "    return vi_signal, vo_signal, vf_signal\n",
    "\n",
    "# Resistor Values and VDD\n",
    "R_1 = 10000\n",
    "R_2 = 10000\n",
    "R_3 = 10000\n",
    "Vdd = 3\n",
    "# x axis is 0 to 4s, 100 values\n",
    "x = linspace(0, 4, 100)\n",
    "fig = figure()\n",
    "ax = fig.add_subplot(1, 1, 1)\n",
    "# Generate a square signal, simulating the switching output of the opamp, .5Hz\n",
    "out_signal, = ax.plot(x, 3/2 * (signal.square(2 * pi * 1/2 * x) + 1))\n",
    "# Calculate the threshold values for the resistor network and the output signal\n",
    "thresholdl, thresholdh = ThresholdCalculator(Vdd, R_1, R_2, R_3)\n",
    "threshold_signal, = ax.plot(x, ThresholdSignal(out_signal, thresholdl, thresholdh, Vdd))\n",
    "\n",
    "def update(R1:int=1, R2:int=1, R3:int=1):\n",
    "    thresholdl, thresholdh = ThresholdCalculator(Vdd, R1, R2, R3)\n",
    "    print(f\"Threshold low is {thresholdl:.2f}V and threshold high is {thresholdh:.2f}V. Ratio is {100 * (thresholdh - thresholdl) / Vdd:.0f}% of VDD\")\n",
    "    threshold_signal.set_ydata(ThresholdSignal(out_signal, thresholdl, thresholdh, Vdd))\n",
    "    fig.canvas.draw_idle()\n",
    "\n",
    "# Create a wiget for\n",
    "R1 = IntSlider(value=10000, min=1000, max=50000, step=1000, description='R1 (Ω):',\n",
    "    orientation='horizontal', readout=True, readout_format='.2d')\n",
    "R2 = IntSlider(value=10000, min=1000, max=50000, step=1000, description='R2 (Ω):',\n",
    "    orientation='horizontal', readout=True, readout_format='.2d')\n",
    "Rf = IntSlider(value=10000, min=1000, max=50000, step=1000, description='Rf (Ω):',\n",
    "    orientation='horizontal', readout=True, readout_format='.2d')\n",
    "thresholdL = Textarea(\n",
    "    value='\"0\"',\n",
    "    placeholder='\"0\"',\n",
    "    description='String:',\n",
    ")\n",
    "interact(update, R1=R1, R2=R2, R3=Rf);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this experiment, R1 = R2 = R3 seem like a good compromise. The threshold levels for Vdd = 3V are 1V and 2V. The hysteresis is 1V, 33% of the VDD value. And this will simplify construction and the BOM, as we will need less resistor values.\n",
    "\n",
    "#### Astable Multivibrator\n",
    "\n",
    "To complete the astable vibrator circuit, we need an oscillating input. We will use the output of the opamp to charge and discharge an RC filter, and connect the capacitor to the inverting input of the opamp. Because the input is not stable in any state, the output will keep oscillating, which in turn will keep the input oscillating... you get the drill.\n",
    "\n",
    "At the start, the capacitor is discharged, so the inverting input is at 0. The non-inverting input is biased at VDD/2, so the output of the opamp is high, and the voltage at the non-inverting input is set to VthresholdH through the feedback resistor. The output of the opamp starts charging the capacitor\n",
    "\n",
    "$$V_{cap} = V_{applied} * (1 - e ^{ (-t/(R*C))}) $$\n",
    "\n",
    "Eventually, $V_{cap} \\gt V_{thresholdH}$, so the output of the opamp will go low, the voltage in $V_{+}$ will be set at $V_{thresholdL}$ and the capacitor wills start to discharge through $R$, until $V_{cap} \\le V_{thresholdL}$ and the cicle starts again.\n",
    "\n",
    "The first rise to $V_{thresholdH}$ will take longer, because the cap has to charge from 0V to $V_{thresholdH}$, but after that, the output of the opamp will be a square wave with a 50% duty cycle.\n",
    "\n",
    "The next code will generate an interactive plot allowing changing the values for all the passives in the circuit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f9a5e328d398474bb4c49656c286bed9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(IntSlider(value=10000, description='Rd1 (Ω):', max=500000, min=1000, step=1000), IntSlid…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7f777183b7b04f4abf576786b8b3f6bf",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
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       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\" Astable Multivibrator Graphs\n",
    "Putting it all together, shows an interactive plot where we can see the impact of the different\n",
    "variables of the circuit have on the output.\n",
    "\"\"\"\n",
    "Rd1:int = 10000\n",
    "Rd2:int = 10000\n",
    "Rf:int = 10000\n",
    "Rcap:int = 100000\n",
    "cap:float = 0.00001\n",
    "Vdd:float = 3\n",
    "\n",
    "start_t = 0\n",
    "stop_t = 10\n",
    "delta_t = .01\n",
    "times = linspace(start_t, stop_t, ceil((stop_t - start_t) / delta_t))\n",
    "\n",
    "# Prepare the plot\n",
    "fig = figure()\n",
    "ax = fig.add_subplot(1, 1, 1)\n",
    "\n",
    "# Generate the three signals to print\n",
    "vi_values, vo_values, vf_values = astable_vibrator_signals(times, Rd1, Rd2, Rf, Rcap, cap, Vdd)\n",
    "vf_signal, = ax.plot(times, vf_values)\n",
    "vi_signal, = ax.plot(times, vi_values)\n",
    "vo_signal, = ax.plot(times, vo_values)\n",
    "\n",
    "def update(Rd1:int, Rd2:int, Rf:int, Rcap:int, cap:float, Vdd:int):\n",
    "    # update the signal\n",
    "    vi_upd_values, vo_upd_values, vf_upd_values = astable_vibrator_signals(times, Rd1, Rd2, Rf, Rcap, cap/100000, Vdd)\n",
    "    vf_signal.set_ydata(vf_upd_values)\n",
    "    vo_signal.set_ydata(vo_upd_values)\n",
    "    vi_signal.set_ydata(vi_upd_values)\n",
    "    # Print the freq/period of the resulting output signal\n",
    "    # get the indices of the local maxima of vi\n",
    "    vi_local_maxes=(argrelextrema(array(vi_upd_values), greater, mode='wrap'))[0]\n",
    "    # the period is the time different between the first two\n",
    "    clk_period = times[vi_local_maxes[1]] - times[vi_local_maxes[0]]\n",
    "    print(f\"Clk Freq is {1/clk_period:.2f}Hz / Period {clk_period:.2f}s\")\n",
    "    fig.canvas.draw_idle()\n",
    "\n",
    "# Create a widgets for variables that will be modifiable\n",
    "Rd1_slider = IntSlider(value=10000, min=1000, max=500000, step=1000, description='Rd1 (Ω):',\n",
    "    orientation='horizontal', readout=True, readout_format='d')\n",
    "Rd2_slider = IntSlider(value=10000, min=1000, max=500000, step=1000, description='Rd2 (Ω):',\n",
    "    orientation='horizontal', readout=True, readout_format='d')\n",
    "Rf_slider = IntSlider(value=10000, min=1000, max=500000, step=1000, description='Rf (Ω):',\n",
    "    orientation='horizontal', readout=True, readout_format='d')\n",
    "Rcap_slider = IntSlider(value=10000, min=5000, max=50000, step=5000, description='Rcap (Ω):',\n",
    "    orientation='horizontal', readout=True, readout_format='d')\n",
    "cap_slider = FloatSlider(value=10, min=.01, max=100, step=.01, description='C (μF):',\n",
    "    orientation='horizontal', readout=True, readout_format='.3f')\n",
    "Vdd_slider = FloatSlider(value=3, min=0, max=5, step=.1, description='Vdd (V):',\n",
    "    orientation='horizontal', readout=True, readout_format='.2f')\n",
    "\n",
    "interact(update, Rd1=Rd1_slider, Rd2=Rd2_slider, Rf= Rf_slider, Rcap=Rcap_slider, cap=cap_slider, Vdd=Vdd_slider);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Astable multivibrator Passive Components Values\n",
    "\n",
    "I like the idea of not having lots of different resistors on my circuit. The Schmitt trigger is balanced if $R_1 = R_2 = R_f$, so we'll select your ubiquitous 10kΩ resistor for them.\n",
    "\n",
    "For the RC filter, I think the right rate of blinking should be around 1s, but not everyone might agree so let's use a variable resistor in the RC. With a 4.7μF cap we get a period of 1s with ~15kΩ. Using a 50kΩ pot you could slow it down up to T=3.2s. Because the minimum resistance of a pot is quite low (tens of Ω), we can add a series resistor that works as a lower limit. 10kΩ would be a bit too much (as that would set the minimum period on .6s), but I don't want to add another resistor value and because smd resistors are practically free, I'll trade some space and put two 10ks in parallel to get the minimum resistance to 5kΩ that would result in minimum period of T=.35s\n",
    "\n",
    "<img src=\"img/Clock_With_Values.png\" height=\"300px\" title=\"Clock Circuit with values\" align=\"center\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Powering it up\n",
    "\n",
    "The first limitation I found is around power. I wanted to use a AAA coin cell to power them, because they store quite an amount of energy (a typical AAA stores 800-1200 mAh, 750mAh if rechargeable ([Duracell](https://www.batterystation.co.uk/content/datasheets_MSDS/duracell/Duracell%20Rechargeable%20AAA.pdf))) but we would need two to get 3V (when full) and a holder simply doesn't fit in the back and it would be quite bulky...\n",
    "\n",
    "<img src=\"img/AAA_On_PCB_Front.png\" height=\"300px\" title=\"PCB Front with AAA holder\" align=\"center\"> <img src=\"img/AAA_On_PCB.png\" height=\"300px\" title=\"PCB with triple A batts\" align=\"center\">\n",
    "\n",
    "So I guess that leaves us with coin cells. They use a different chemistry, so they provide higher voltages, so we can power the whole thing with one instead of two (that's good!), but they are smaller, so they have less net capacity (that's bad!). On a good day, a CR2032 has ~250mA and that's when you barely draw any current (see the graph below). As they get discharged, voltage quickly drops (see graph below) which might be a problem with white LEDs.\n",
    "\n",
    "<img src=\"img/2032DischargeCurves.jpg\" width=\"400px\" title=\"Coin Cell Discharge Curves\" align=\"center\">\n",
    "\n",
    "Using one cell definitely looks better than using triple As, you can't see the battery.\n",
    "\n",
    "<img src=\"img/CR2032x2_On_PCB_Front.png\" height=\"300px\" title=\"Front With Coin Cell\" align=\"center\">\n",
    "\n",
    "Another option would be using two cells in series. That wouldn't \"double\" the battery life, as the current draw would be the same, but the higher VDD voltage could help to bias a white LED for longer: a single, partially-depleted cell providing 2.2V wouldn't bias a white LED, but two really-depleted cells providing 1.8V each would still give you 3.6V to comfortably bias the LED. Two cells don't look bad either, but it might be too heavy/chunky.\n",
    "\n",
    "<img src=\"img/CR2032x1_On_PCB_Side.png\" height=\"300px\" title=\"One Cell from Side\" align=\"center\"> <img src=\"img/CR2032x2_On_PCB_Side.png\" height=\"300px\" title=\"Two Cells from Side\" align=\"center\">\n",
    "\n",
    "NordicRF published a paper that proved that pulsed current demand also helped to provide more energy. The time scales mentioned in the paper are very small for our use case (we don't want to blink in the 10s of ms range) but the planned paused between cycles might give the battery a break and improve battery life.\n",
    "\n",
    "## Choosing an LED\n",
    "\n",
    "My first idea was to use white LEDs. They have a relatively high Vf (typically around 3.2V although there are some out there with 2.7V) as they are blue or UV LEDs covered with a phosphor layer. These Vfs are at relatively high currents (20-60mA or even more...), where the LED is the most efficient and designed to operate. Luckily for us, we want to work at a lower bias point because we want to run them at the lowest current possible because 1) we are running on a coin cell and 2) we don't want to light up the entire room.\n",
    "\n",
    "I'll consider using a coloured LED, as they have smaller Vfs allowing using a small bias resistor, and a white LED, which might require 2 batteries and a bigger bias resistor (so more power lost on the resistor) if their bias point is close to 3V.\n",
    "\n",
    "About the bias point, because we have two rings of 6 LEDs, the maximum draw will be ~6 * Iled. Let's aim for a current of 5mA, which would leave us with a maximum draw of 30mA.\n",
    "\n",
    "### Yellow LED\n",
    "\n",
    "This is the curve of a cheap-and-cheerful 20mA@2.2V Yellow LED ([link to datasheet](https://docs.rs-online.com/2fcb/0900766b8156b2c7.pdf)). The rated luminosity is 100mcd typ, 63mcd min at 20mA.\n",
    "\n",
    "<img src=\"img/Yellow_LED_Bias.png\" height=\"300px\" title=\"Yellow LED If/Vf curves\" align=\"center\"> <img src=\"img/Yellow_LED_LightvsCurr.png\" height=\"300px\" title=\"Yellow LED light/If curves\" align=\"center\">\n",
    "\n",
    "At 5mA, the voltage drop in the LED is ~2V.\n",
    "\n",
    "### White LED\n",
    "\n",
    "I found these Osram white LEDs, which are from a reputable brand and are surprisingly cheap for a white LED. They also operate at 20mA@3.2V, although they are on the coldish side of white, with a temperature of 4K ([link to datasheet - TOPLED E3014 KW DCLMS2.EC](https://docs.rs-online.com/4eb6/A700000007295371.pdf)). It's rated 2800mcd min / 4500 mcd max!! **That's 40x brighter.**\n",
    "\n",
    "<img src=\"img/KW_DCLMS2_Bias.png\" height=\"300px\" title=\"White LED If/Vf curves\" align=\"center\"> <img src=\"img/KW_DCLMS2_LightvsCurr.png\" height=\"300px\" title=\"White LED light/If curves\" align=\"center\">\n",
    "\n",
    "At 5mA, the voltage drop in the LED is ~2.6V. These LEDs are really efficient, and even at 5mA, they are really bright!\n",
    "\n",
    "### Limiting Resistor Calculations\n",
    "\n",
    "This code will calculate the value of the limiting resistors for the LEDs, based on the voltage supplied by the batteries, number of batteries\n",
    "\n",
    "A coin cell (CR2032) has this typical discharge rates, were voltage almost instantly drops to 2.8V and provides voltage until 1.8-2V\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OSRAM White LED - 1 Cells\n",
      "Resistor value for 5.0mA LED bias current with fresh cells is 40Ω and will drop 0.20V\n",
      "Power use by LED is 13.00mW and Power wasted in R is 1.00mW\n",
      "==============\n",
      "OSRAM White LED - 2 Cells\n",
      "Resistor value for 5.0mA LED bias current with fresh cells is 600Ω and will drop 3.00V\n",
      "Power use by LED is 13.00mW and Power wasted in R is 15.00mW\n",
      "==============\n",
      "Generic Yellow LED - 1 Cells\n",
      "Resistor value for 5.0mA LED bias current with fresh cells is 160Ω and will drop 0.80V\n",
      "Power use by LED is 10.00mW and Power wasted in R is 4.00mW\n",
      "==============\n",
      "Generic Yellow LED - 2 Cells\n",
      "Resistor value for 5.0mA LED bias current with fresh cells is 720Ω and will drop 3.60V\n",
      "Power use by LED is 10.00mW and Power wasted in R is 18.00mW\n",
      "==============\n",
      "OSRAM White LED - 1 Cells\n",
      "Resistor value for 4.0mA LED bias current with fresh cells is 53Ω and will drop 0.21V\n",
      "Power use by LED is 10.36mW and Power wasted in R is 0.84mW\n",
      "==============\n",
      "OSRAM White LED - 2 Cells\n",
      "Resistor value for 4.0mA LED bias current with fresh cells is 753Ω and will drop 3.01V\n",
      "Power use by LED is 10.36mW and Power wasted in R is 12.04mW\n"
     ]
    }
   ],
   "source": [
    "\n",
    "from math import ceil\n",
    "\n",
    "class LED:\n",
    "    def __init__(self, name:str, Vbias:float, Ibias:float):\n",
    "        self.name = name\n",
    "        self.Vbias = Vbias\n",
    "        self.Ibias = Ibias\n",
    "\n",
    "class Battery:\n",
    "    def __init__(self, maxCellVoltage:float, minCellVoltage:float, numCells:int):\n",
    "        self.maxCellVoltage = maxCellVoltage\n",
    "        self.minCellVoltage = minCellVoltage\n",
    "        self.numCells = numCells\n",
    "    def maxBattVoltage(self)->float:\n",
    "        aux = (self.numCells * self.maxCellVoltage)\n",
    "        return aux\n",
    "    def minCellVoltage(self)->float:\n",
    "        return (self.numCells * self.minCellVoltage)\n",
    "\n",
    "def findLimiterResistorValue(LEDObj:LED, battery: Battery):\n",
    "    '''Prints the value of the limiting resistor needed in series with the LED with the\n",
    "    Bias point defined in LEDObj, and some stats\n",
    "\n",
    "    Parameters:\n",
    "    -----------\n",
    "        LEDObj: LED\n",
    "            An instance of the LED class, containing the target bias point.\n",
    "        battVoltage: float\n",
    "            The value of the battery voltage connected to the R-LED circuit\n",
    "    '''\n",
    "    resistorVoltDropMax = battery.maxBattVoltage() - LEDObj.Vbias\n",
    "    resistorValueMin = ceil(resistorVoltDropMax / LEDObj.Ibias)\n",
    "\n",
    "    print(f\"{LEDObj.name} - {battery.numCells} Cells\")\n",
    "    print(f\"Resistor value for {LEDObj.Ibias * 1000}mA LED bias current with fresh cells is {resistorValueMin}Ω and will drop {resistorVoltDropMax:.2f}V\")\n",
    "    print (f\"Power use by LED is {LEDObj.Ibias * LEDObj.Vbias * 1000:.2f}mW and Power wasted in R is {LEDObj.Ibias * resistorVoltDropMax * 1000:0.2f}mW\")\n",
    "\n",
    "\n",
    "# White OSRAM LEDs, 20mA@2.7V, 5mA@2.6V, almost the same at 4mA\n",
    "whiteLED5mA = LED(\"OSRAM White LED\", 2.6, 0.005)\n",
    "whiteLED4mA = LED(\"OSRAM White LED\", 2.59, 0.004)\n",
    "# Generic 0603 Yellow LED, bias is 20mA@2.2V, 5mA@2V\n",
    "yellowLED5mA = LED(\"Generic Yellow LED\", 2, 0.005)\n",
    "\n",
    "# Single CR2032, starts at ~2.8V and stops at ~1.8V\n",
    "singleCell = Battery(2.8, 1.8, 1)\n",
    "# Double CR2032 in series, same current, double the voltage\n",
    "doubleCell =  Battery(2.8, 1.8, 2)\n",
    "\n",
    "# Print the values of the limiting resistors needed for the white and yellow LEDs with one and two CR2032 cells\n",
    "findLimiterResistorValue(whiteLED5mA, singleCell)\n",
    "print(\"==============\")\n",
    "findLimiterResistorValue(whiteLED5mA, doubleCell)\n",
    "print(\"==============\")\n",
    "findLimiterResistorValue(yellowLED5mA, singleCell)\n",
    "print(\"==============\")\n",
    "findLimiterResistorValue(yellowLED5mA, doubleCell)\n",
    "# The White LED was quite bright at 5mA, what would be needed to get it driven at 4mA?\n",
    "print(\"==============\")\n",
    "findLimiterResistorValue(whiteLED4mA, singleCell)\n",
    "print(\"==============\")\n",
    "findLimiterResistorValue(whiteLED4mA, doubleCell)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LTSPICE Simulation\n",
    "\n",
    "### One Coin Cell\n",
    "\n",
    "To see the bias point as the battery drops voltage, we will need to run simulations on LTSpice.\n",
    "\n",
    "I found this link about how to model LEDs on LTSpice in electronics stackexchange: [Modelling an LED](https://electronics.stackexchange.com/questions/9510/how-do-i-model-an-led-with-spice)\n",
    "\n",
    "The circuit is as follows\n",
    "\n",
    "<img src=\"img/LTSPice.png\" width=\"300px\" title=\"LTSpice Sim Schematic\" align=\"center\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joel.santos\\AppData\\Local\\Temp\\ipykernel_7084\\4211692061.py:13: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.\n",
      "  fig_spice = figure()\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1be4bf277d0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "50a05a8d973c4099be19fca74f255d79",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ltspice\n",
    "from matplotlib.collections import LineCollection\n",
    "\n",
    "# Get spice simulation data\n",
    "filepath = 'LTSpice/LED And Battery Sims 1 Cell.raw'\n",
    "l = ltspice.Ltspice(filepath)\n",
    "l.parse() # Data loading sequence. It may take few minutes for huge file.\n",
    "# Get data from simulation\n",
    "voltages = l.get_time() # the x axis in the simulation is Voltages, not time\n",
    "Vwhite = l.get_data('I(D1)')\n",
    "Vyellow = l.get_data('I(D2)')\n",
    "\n",
    "fig_spice = figure()\n",
    "ax_spice = fig_spice.add_subplot(1, 1, 1)\n",
    "\n",
    "# Plot the two diode curves\n",
    "whiteLED = ax_spice.plot(voltages, Vwhite * 1000, label=\"White LED RS=40Ω\")\n",
    "yellowLED = ax_spice.plot(voltages, Vyellow * 1000, label=\"Yellow LED RS=160Ω\")\n",
    "\n",
    "# plot a dashed lines at the points the light should go off, more or less\n",
    "ax_spice.axhline(y=1.4, c=\"blue\",linewidth=1,zorder=0, linestyle=\"dashed\")\n",
    "ax_spice.axhline(y=1, c=\"orange\",linewidth=1,zorder=0, linestyle=\"dashed\")\n",
    "ax_spice.axvline(x=2.55, c=\"blue\",linewidth=1,zorder=0, linestyle=\"dashed\")\n",
    "ax_spice.axvline(x=2.05, c=\"orange\",linewidth=1,zorder=0, linestyle=\"dashed\")\n",
    "#Invert the axis, as it's easier to read \"as the battery gets depleted\"\n",
    "ax_spice.invert_xaxis()\n",
    "ax_spice.set_ylabel(\"If (mA)\")\n",
    "ax_spice.set_xlabel(\"Vbatt (V)\")\n",
    "ax_spice.set_title(\"If/Vbat with 1 Coin Cell\")\n",
    "ax_spice.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the case of one coin cell, the current would drop below 1mA at @2V in the case of the yellow diode and current is around 2mA@2.55V in the case of the white (the model is not spot on). That means that the white LED is not going to stay lit for long with one cell... (but check the results for an interesting plot twist!).\n",
    "\n",
    "### Two Coin Cells\n",
    "\n",
    "For the two coin cells, I will use the same circuit, but I will sweep the voltage from 1.8 * 2 to 2.8 * 2.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1be4d9ef3d0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "427ad66183094be8a787afc928ac0135",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get spice simulation data\n",
    "filepath = 'LTSpice/LED And Battery Sims - Two Cells.raw'\n",
    "l = ltspice.Ltspice(filepath)\n",
    "l.parse() # Data loading sequence. It may take few minutes for huge file.\n",
    "# Get data from simulation\n",
    "voltages = l.get_time() # the x axis in the simulation is Voltages, not time\n",
    "Vwhite = l.get_data('I(D1)')\n",
    "Vyellow = l.get_data('I(D2)')\n",
    "\n",
    "fig_spice = figure()\n",
    "ax_spice = fig_spice.add_subplot(1, 1, 1)\n",
    "\n",
    "# Plot the two diode curves\n",
    "whiteLED = ax_spice.plot(voltages, Vwhite * 1000, label=\"White LED RS=40Ω\")\n",
    "yellowLED = ax_spice.plot(voltages, Vyellow * 1000, label=\"Yellow LED RS=160Ω\")\n",
    "#Invert the axis, as it's easier to read \"as the battery gets depleted\"\n",
    "ax_spice.invert_xaxis()\n",
    "ax_spice.set_ylabel(\"If (mA)\")\n",
    "ax_spice.set_xlabel(\"Vbat (V)\")\n",
    "ax_spice.set_title(\"If/Vbat with 1 Coin Cell\")\n",
    "ax_spice.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With two cells, even when the batteries are depleted, we are still drawing a good 2-2.5mA, so the LEDs will still emit some light. Because of the way voltage drops in a coin cell (non-linearly with a big voltage dip at the end of the cell's life) this might not translate in a significant increase in battery life for the increased price of the extra battery in the case of the Yellow LED, but the white LED can squeeze quite a lot more energy from the batteries."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing it\n",
    "\n",
    "Let's put it all together and do some tests. The things I want to check are:\n",
    "\n",
    "* Which pin has to be connected to the reset in the binary counter\n",
    "* How long do we want to pause between cycles\n",
    "* What's a good blinking rate that doesn't get annoying\n",
    "* How bright are the LEDs at different bias currents\n",
    "* How long does one and two cells last with the different LEDs\n",
    "\n",
    "### Findings\n",
    "\n",
    "#### Decade counter output connections\n",
    "\n",
    "The decade counter is active high: outputs are low while they are not selected, and the reset pin needs a HIGH level to reset. I left `O0` unconnected, that will be my \"pause\" with no lights in the cycle. Then `O1` is the centre LED, `O2` triggers the NPN of the \"inner ring\" and `O3` the \"outter ring\". Reset is connected to `O4`. As soon as `O4` output is enabled, the reset is triggered, which stops resets `O4` to LOW and restarts the counter. `O0` is then HIGH and in the next clock transition, `O1` will turn the centre LED on.\n",
    "\n",
    "#### Blinking pattern\n",
    "\n",
    "One cycle of pause at the end of the cycle felt good. Blinking fast was annoying, 1Hz looked good to me.\n",
    "\n",
    "#### LED Brightness, Battery duration\n",
    "\n",
    "5mA is a lot for the white LEDs, they get bright! They were better than the yellow LEDs on every metric. They last longer, they are brighter and while the yellow LED languished with a very pale light (not noticeable during the day) when the battery was dying, the white LEDs were still strong after days of leaving them on.\n",
    "\n",
    "Surprisingly, the white LEDs, on one battery, lasted for almost a week of continuous blinking. And it's not only surprising because of how long it lasted, it is surprising because they outlasted the yellow LEDs by 48+ hours (to be fair, I lost track of how long the white LEDs lasted because it took so long to deplete the battery that I stopped counting). A battery will be more than enough to get you through the festive season.\n",
    "\n",
    "I wasn't expecting this at all. I guess the fact that they are so stupidly efficient compared to the crappy yellow ones makes them very bright even at very low currents, so you can drive them with lower currents, get more light out of them (compared to the yellow ones) and they tax the battery less. White LEDs it is, then.\n",
    "\n",
    "They will get particularly bright on a new battery, but \n",
    "\n",
    "\n",
    "### Conclusion\n",
    "\n",
    "* White Osram LEDs on a single battery are stupidly bright and last enough to use them for a whole \"Christmas\", so it's settled.\n",
    "* I ended up using 56Ω current limiting resitstors and the white LEDs were still very bright with a fully charged battery, and quite bright during the whole battery charge.\n"
   ]
  }
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