Examples/LoadWithExternalSource/LoadWithExternalSource.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Measurements with the EL1002 and an external power supply\n",
    "\n",
    "The [EL1002 electronic load](https://zahner.de/products-details/electronic-loads/el1002) can perform measurements over two quadrants by connecting a power supply to the EXT terminal. \n",
    "This means that measurements can be made on the OCP/OCV, batteries can be charged/discharged or electrolysers can be investigated, which would not be possible with a conventional electronic load.\n",
    "\n",
    "The exact wiring must be read in the [EL1002 manual](https://doc.zahner.de/hardware/el1002.pdf). The following figure shows the example connection.\n",
    "\n",
    "![EL1002 with Supply](EL1002_Supply.png \"EL1002 with Supply\")\n",
    "\n",
    "For this example, an EIS measurement with the EL1002 and the power supply [Delta Elektronika SM3300 SM 18-220](https://www.delta-elektronika.nl/en/products/dc-power-supplies-3300w-sm3300-series.html) is controlled with Python. The [Remote2](https://doc.zahner.de/manuals/remote2.pdf) is used to control the EL1002. The Delta supply is controlled with [SCPI over TCP/IP](https://www.delta-elektronika.nl/upload/MANUAL_ETHERNET_AND_SEQUENCER_PROGRAMMING_SM3300_P0157_V201908.pdf), [classes for simplifying the control](https://doc.zahner.de/thales_remote/delta_elektronika_supply/index.html) have been implemented for this purpose.\n",
    "\n",
    "A 200 Ah lithium cell is connected to the system as measurement object, which is measured at the OCP/OCV."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import time\n",
    "\n",
    "from delta_remote.connection import DeltaConnection\n",
    "from delta_remote.script_wrapper import DeltaSCPIWrapper, DeltaSources\n",
    "\n",
    "from thales_remote.connection import ThalesRemoteConnection\n",
    "from thales_remote.script_wrapper import PotentiostatMode, ThalesRemoteScriptWrapper\n",
    "from thales_remote.file_interface import ThalesFileInterface\n",
    "from zahner_analysis.file_import.ism_import import IsmImport\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from matplotlib.ticker import EngFormatter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Connect Python to the already launched Thales-Software\n",
    "\n",
    "A [Remote2](https://doc.zahner.de/manuals/remote2.pdf) connection is established to control the device and a connection is established to exchange the measurement data as explained in [FileExchangeEIS.ipynb](https://github.com/Zahner-elektrik/Thales-Remote-Python/blob/main/Examples/FileExchangeEIS/FileExchangeEIS.ipynb)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if __name__ == \"__main__\":\n",
    "    zenniumConnection = ThalesRemoteConnection()\n",
    "    zenniumConnection.connectToTerm(\"localhost\")\n",
    "\n",
    "    zahnerZennium = ThalesRemoteScriptWrapper(zenniumConnection)\n",
    "    zahnerZennium.forceThalesIntoRemoteScript()\n",
    "    zahnerZennium.calibrateOffsets()\n",
    "\n",
    "    fileInterface = ThalesFileInterface(\"localhost\")\n",
    "    fileInterface.enableKeepReceivedFilesInObject()\n",
    "    fileInterface.enableAutomaticFileExchange()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Connect Python to the Delta Elektronika power supply\n",
    "\n",
    "For the Delta Elektronika supply, as for the Thales, a class was developed that manages the connection ([DeltaConnection](https://doc.zahner.de/thales_remote/delta_elektronika_supply/index.html#delta_remote.connection.DeltaConnection)), and a class that contains the commands ([DeltaSCPIWrapper](https://doc.zahner.de/thales_remote/delta_elektronika_supply/index.html#delta_remote.script_wrapper.DeltaSCPIWrapper))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "IDN:\tDELTA ELEKTRONIKA BV,SM18-220,000010338779,H0_P0160,0\n"
     ]
    }
   ],
   "source": [
    "deltaConnection = DeltaConnection()\n",
    "deltaConnection.connect(ip=\"192.168.2.73\", port=8462)\n",
    "\n",
    "deltaSM18_220 = DeltaSCPIWrapper(deltaConnection)\n",
    "\n",
    "print(f\"IDN:\\t{deltaSM18_220.IDN()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After the connection is established and the device identification is displayed, the current and voltage source of the Delta supply is switched to Ethernet."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "deltaSM18_220.setProgSourceVoltage(DeltaSources.eth)\n",
    "deltaSM18_220.setProgSourceCurrent(DeltaSources.eth)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parameterization of the EIS measurement\n",
    "\n",
    "The EIS measurement is configured the same way as for spectra with the internal potentiostat. Only potentiostat one is selected, this corresponds to EPC channel one to which the EL1002 is connected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "zahnerZennium.setEISOutputPath(r\"C:\\THALES\\temp\")\n",
    "zahnerZennium.setEISNaming(\"individual\")\n",
    "zahnerZennium.setEISOutputFileName(\"spectra_5aac\")\n",
    "\n",
    "zahnerZennium.selectPotentiostat(1)\n",
    "zahnerZennium.setPotentiostatMode(PotentiostatMode.POTMODE_GALVANOSTATIC)\n",
    "zahnerZennium.setAmplitude(0)\n",
    "zahnerZennium.setLowerFrequencyLimit(0.01)\n",
    "zahnerZennium.setStartFrequency(1000)\n",
    "zahnerZennium.setUpperFrequencyLimit(100000)\n",
    "zahnerZennium.setLowerNumberOfPeriods(5)\n",
    "zahnerZennium.setLowerStepsPerDecade(5)\n",
    "zahnerZennium.setUpperNumberOfPeriods(10)\n",
    "zahnerZennium.setUpperStepsPerDecade(10)\n",
    "zahnerZennium.setScanDirection(\"startToMax\")\n",
    "zahnerZennium.setScanStrategy(\"single\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Switching ON the outputs\n",
    "\n",
    "After the EIS measurement has been configured, the outputs of the EL1002 and the Delta supply are switched on in the **correct order**.\n",
    "\n",
    "The EIS measurement should be performed at the OCP. Therefore the EL1002 is switched on at 0 A, afterwards the supply is switched on at 20 A constant current. Then the complete current flows through the EL1002, that no current flows through the object. The supply voltage is set to 6 V, but this voltage will not be reached.\n",
    "\n",
    "For safety, that everything is settled and stable, a pause of one second is always kept after switching on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "zahnerZennium.setCurrent(0)\n",
    "zahnerZennium.enablePotentiostat()\n",
    "\n",
    "time.sleep(1.0)\n",
    "\n",
    "deltaSM18_220.setTargetVoltage(6)\n",
    "deltaSM18_220.setTargetCurrent(20)\n",
    "deltaSM18_220.enableOutput()\n",
    "\n",
    "time.sleep(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a next step, the currents in the system are output to show where which currents flow when the EXT connection is used.\n",
    "\n",
    "It can be seen that the EL1002 measures 0 A of current through the object even though 20 A of current is output from the supply. These 20 A flow into the output stage of the EL1002, but not through the measuring object and the current measuring unit.\n",
    "\n",
    "**The 65 watts of power are converted into heat in the EL1002. This is the special aspect of the connection of the EL1002 with the EXT terminal, although the EL1002 displays 0 A current, there is a power loss at the EL1002.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Measured current\tEL1002:\t\t    -0.009 A\n",
      "Measured current\tDelta SM18-220:\t    19.988 A\n",
      "Measured voltage\tDelta SM18-220:\t     3.280 V\n",
      "Measured power\t\tDelta SM18-220:\t    65.230 W\n"
     ]
    }
   ],
   "source": [
    "print(f\"Measured current\\tEL1002:\\t\\t{zahnerZennium.getCurrent():>10.3f} A\")\n",
    "\n",
    "print(\n",
    "    f\"Measured current\\tDelta SM18-220:\\t{deltaSM18_220.getMeasuredCurrent():>10.3f} A\"\n",
    ")\n",
    "print(\n",
    "    f\"Measured voltage\\tDelta SM18-220:\\t{deltaSM18_220.getMeasuredVoltage():>10.3f} V\"\n",
    ")\n",
    "print(f\"Measured power\\t\\tDelta SM18-220:\\t{deltaSM18_220.getMeasuredPower():>10.3f} W\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Performing the measurement\n",
    "\n",
    "After the outputs are turned on, the amplitude is also turned on and the impedance measurement is started. The amplitude must be switched off again after the impedance measurement.\n",
    "\n",
    "Here 20 A quiescent current was selected by the EL1002 and 5 A amplitude. This ratio must be determined empirically. At least the amplitude must be used as quiescent current, but it is recommended to use more current, a good guideline is factor 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "zahnerZennium.setAmplitude(5)\n",
    "zahnerZennium.measureEIS()\n",
    "zahnerZennium.setAmplitude(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Switching OFF the outputs\n",
    "\n",
    "After the measurement, it is necessary to switch off in the reverse order. Since 0 A should flow through the object, the Delta power supply is switched off first, then the EL1002 regulates to 0 A. At last the EL1002 is switched off."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "deltaSM18_220.disableOutput()\n",
    "\n",
    "time.sleep(1)\n",
    "\n",
    "zahnerZennium.disablePotentiostat()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting the measurement data\n",
    "\n",
    "The measurement data is plotted after the measurement with matplotlib."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ismFile = IsmImport(fileInterface.getLatestReceivedFile().binaryData)\n",
    "\n",
    "impedanceFrequencies = ismFile.getFrequencyArray()\n",
    "impedanceAbsolute = ismFile.getImpedanceArray()\n",
    "impedancePhase = ismFile.getPhaseArray()\n",
    "impedanceComplex = ismFile.getComplexImpedanceArray()\n",
    "\n",
    "figBode, (impedanceAxis) = plt.subplots(1, 1)\n",
    "\n",
    "phaseAxis = impedanceAxis.twinx()\n",
    "\n",
    "impedanceAxis.loglog(\n",
    "    impedanceFrequencies,\n",
    "    impedanceAbsolute,\n",
    "    linestyle=\"dashed\",\n",
    "    linewidth=1,\n",
    "    marker=\"o\",\n",
    "    markersize=5,\n",
    "    fillstyle=\"none\",\n",
    "    color=\"blue\",\n",
    ")\n",
    "impedanceAxis.xaxis.set_major_formatter(EngFormatter(unit=\"Hz\"))\n",
    "impedanceAxis.yaxis.set_major_formatter(EngFormatter(unit=\"$\\Omega$\"))\n",
    "impedanceAxis.set_xlabel(r\"f\")\n",
    "impedanceAxis.set_ylabel(r\"|Z|\")\n",
    "impedanceAxis.yaxis.label.set_color(\"blue\")\n",
    "impedanceAxis.grid(which=\"both\", linestyle=\"dashed\", linewidth=0.5)\n",
    "impedanceAxis.set_xlim(\n",
    "    [min(impedanceFrequencies) * 0.8, max(impedanceFrequencies) * 1.2]\n",
    ")\n",
    "\n",
    "phaseAxis.semilogx(\n",
    "    impedanceFrequencies,\n",
    "    np.abs(impedancePhase * (360 / (2 * np.pi))),\n",
    "    linestyle=\"dashed\",\n",
    "    linewidth=1,\n",
    "    marker=\"o\",\n",
    "    markersize=5,\n",
    "    fillstyle=\"none\",\n",
    "    color=\"red\",\n",
    ")\n",
    "phaseAxis.yaxis.set_major_formatter(EngFormatter(unit=\"$°$\", sep=\"\"))\n",
    "phaseAxis.xaxis.set_major_formatter(EngFormatter(unit=\"Hz\"))\n",
    "phaseAxis.set_xlabel(r\"f\")\n",
    "phaseAxis.set_ylabel(r\"|Phase|\")\n",
    "phaseAxis.yaxis.label.set_color(\"red\")\n",
    "phaseAxis.set_ylim([0, 90])\n",
    "figBode.set_size_inches(15, 6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Close the connections\n",
    "\n",
    "Finally, the two connections are disconnected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "zahnerZennium.selectPotentiostat(0)\n",
    "zenniumConnection.disconnectFromTerm()\n",
    "fileInterface.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On the Delta source, the signal source for current and voltage is reset to the rotary switch on the front panel before disconnect."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "finish\n"
     ]
    }
   ],
   "source": [
    "deltaSM18_220.setProgSourceVoltage(DeltaSources.front)\n",
    "deltaSM18_220.setProgSourceCurrent(DeltaSources.front)\n",
    "deltaConnection.disconnect()\n",
    "\n",
    "print(\"finish\")"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "b89b5cfaba6639976dc87ff2fec6d58faec662063367e2c229c520fe71072417"
  },
  "kernelspec": {
   "display_name": "Python 3.10.4 64-bit",
   "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": "3.10.4"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}