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Diffstat (limited to 'ELECTRIC_MACHINERY/.ipynb_checkpoints/chapter10-checkpoint.ipynb')
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diff --git a/ELECTRIC_MACHINERY/.ipynb_checkpoints/chapter10-checkpoint.ipynb b/ELECTRIC_MACHINERY/.ipynb_checkpoints/chapter10-checkpoint.ipynb new file mode 100755 index 00000000..de5013c9 --- /dev/null +++ b/ELECTRIC_MACHINERY/.ipynb_checkpoints/chapter10-checkpoint.ipynb @@ -0,0 +1,364 @@ +{ + "metadata": { + "name": "" + }, + "nbformat": 3, + "nbformat_minor": 0, + "worksheets": [ + { + "cells": [ + { + "cell_type": "heading", + "level": 1, + "metadata": {}, + "source": [ + "Chapter 10: Introduction to Power Electronics" + ] + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Example 10.5, Page number: 508" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from __future__ import division\n", + "%matplotlib inline\n", + "from pylab import *\n", + "import numpy as np\n", + "from math import *\n", + "\n", + "#Variable declaration:\n", + "w=2*pi*60 #frequency of voltage(Hz)\n", + "R=10 #ohm\n", + "C=0.01 #F\n", + "Vo=120*sqrt(2) #maximum voltage(V)\n", + "Nmax=800\n", + "tau=R*C #time constant(s)\n", + "\n", + "#Calculations:\n", + "# diode = 1 when rectifier bridge is conducting\n", + "\n", + "diode=1\n", + "t=[0]*801\n", + "vs=[0]*801\n", + "vrect=[0]*801\n", + "vR=[0]*801\n", + "iB=[0]*801\n", + "\n", + "t=[0]*801\n", + "for n in range(1,Nmax+2,1):\n", + " t[n-1] = (2.5*pi/w)*(n-1)/Nmax\n", + " vs[n-1]=Vo*math.cos(w*t[n-1])\n", + " vrect[n-1]=abs(vs[n-1])\n", + "#if the rectifier bridge is ON:\n", + " if diode==1:\n", + " vR[n-1]=vrect[n-1]\n", + " if (w*t[n-1])<=(pi/2):\n", + " iB[n-1]=vR[n-1]-Vo*C*w*math.sin(w*t[n-1])\n", + " elif (w*t[n-1])<=3*pi/2:\n", + " iB[n-1]=vR[n-1]/R+Vo*C*w*math.sin(w*t[n-1])\n", + " else:\n", + " iB[n-1]=vR[n-1]/R-Vo*C*w*math.sin(w*t[n-1])\n", + " if iB[n-1]<0:\n", + " diode=0\n", + " toff=t[n-1]\n", + " Voff=vrect[n-1]\n", + " else:\n", + " vR[n-1]=Voff*exp(-(t[n-1]-toff/tau))\n", + " iB[n-1]=0\n", + " if (vrect[n-1]-vR[n-1])>0:\n", + " diode=1\n", + "\n", + "\n", + "\n", + "#Results:\n", + "iR=(1/R)*np.array(vR)\n", + "plot(1000*np.array(t),vR)\n", + "xlabel('time [msec]')\n", + "ylabel('voltage [V]')\n", + "xlim(0,22)\n", + "ylim(0,180)\n", + "plot(1000*np.array(t),vrect,'--')\n", + "grid()\n", + "print \"The required plots are shown below:\"\n", + "show()\n", + "plot(1000*np.array(t),iR)\n", + "xlabel('time [msec]')\n", + "ylabel('source current [A]')\n", + "xlim(0 ,22)\n", + "ylim(-50,250) \n", + "plot(1000*np.array(t),1.5*np.array(iB),'--')\n", + "grid()\n", + "show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Populating the interactive namespace from numpy and matplotlib\n", + "The required plots are shown below:" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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ibCiGqVKvAU4DsP/GfszznydsKIbxuYNUw2K96m0CQpzAsLS0REFBASwsLJCf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\nVVOFQzcPiRPmf3gTYFh9T5t62+9tLOi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+ "text": [ + "<matplotlib.figure.Figure at 0x2986d90>" + ] + } + ], + "prompt_number": 1 + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Example 10.6, Page number: 522" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from __future__ import division\n", + "%matplotlib inline\n", + "from math import *\n", + "\n", + "#Variable declaration:\n", + "w=2*pi*60 #Angular freq of voltage(rad/sec)\n", + "Vo=230*sqrt(2) #volt\n", + "R=5.6 #Resistance(ohm)\n", + "\n", + "#Calculations:\n", + "Ls=[0]*101\n", + "tc=[0]*101\n", + "Idc=[0]*101\n", + "for n in range(1,101,1):\n", + " Ls[n-1]=n*10**-3\n", + " Idc[n-1]=2*Vo/(pi*R+2*w*Ls[n-1])\n", + " tc[n-1]=(1/w)*acos(1-(2*Idc[n-1]*w*Ls[n-1])/Vo)\n", + "\n", + "#Results:\n", + "plot(1000*np.array(Ls),Idc,'g.')\n", + "xlabel('Commutating inductance Ls [mH]')\n", + "ylabel('Idc [A]')\n", + "title('Load current,Idc vs Commutating inductance,Ls')\n", + "show()\n", + "plot(1000*np.array(Ls),1000*np.array(tc),'g.')\n", + "xlabel('Commutating inductance L [mH]')\n", + "ylabel('tc [msec]')\n", + "title('Commutating Inductance,Ls vs time,tc')\n", + "show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Populating the interactive namespace from numpy and matplotlib\n" + ] + }, + { + "output_type": "stream", + "stream": "stderr", + "text": [ + "WARNING: pylab import has clobbered these variables: ['fmod', 'sinh', 'trunc', 'tan', 'gamma', 'cosh', 'radians', 'modf', 'expm1', 'ldexp', 'linalg', 'random', 'frexp', 'ceil', 'isnan', 'copysign', 'cos', 'degrees', 'tanh', 'fabs', 'sqrt', 'hypot', 'power', 'log', 'log10', 'info', 'log1p', 'floor', 'fft', 'pi', 'exp', 'isinf', 'e', 'sin']\n", + "`%pylab --no-import-all` prevents importing * from pylab and numpy\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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ExEQAQGJiIsLDw7UZRoum3oVkZmLGAWci0poGtRCKiopgZmaGNm3aALh9nYSS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\nIjY2VnTt2lV4eHiIqKgocfP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XyFeDl5cXmjZtiitXrqB9+/bYs2cP/Pz8yuxz/fp1rqj3/2JjYxEbG2vqZpgF9sVj7IvH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\np07QaDQAgKVLl2L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+ "text": [ + "<matplotlib.figure.Figure at 0x2981fd0>" + ] + } + ], + "prompt_number": 2 + }, + { + "cell_type": "heading", + "level": 3, + "metadata": {}, + "source": [ + "Example 10.7, Page number: 528" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from __future__ import division\n", + "%matplotlib inline\n", + "from math import *\n", + "\n", + "#Variable declaration:\n", + "R=12.5*10**-3 #ohm\n", + "L=1.2 #H\n", + "Vo=15 #volt\n", + "w=120*pi #angular freq(Hz)\n", + "Idc=35 #DC current(A)\n", + "\n", + "\n", + "#Calculations:\n", + "#for part (a):\n", + "theta=[0]*1301\n", + "t=[0]*1301\n", + "vL=[0]*1301\n", + "vs=[0]*1301\n", + "\n", + "Vdc_a=R*Idc #Dc voltage(V)\n", + "P=Vdc_a*Idc #Power\n", + "alpha_da = acos(pi*R*Idc/(2*Vo)) ; #delay angle\n", + "for n in range(1,1301,1): #loop for calculating load voltage\n", + " theta[n-1]=2*pi*(n-1)/1000\n", + " t[n-1]=theta[n-1]/w\n", + " vs[n-1]=Vo*sin(theta[n-1])\n", + " if theta[n-1]<alpha_da:\n", + " vL[n-1]=-vs[n-1]\n", + " elif (theta[n-1]<pi+alpha_da):\n", + " vL[n-1]=-vs[n-1]\n", + " elif theta[n-1]<2*pi+alpha_da:\n", + " vL[n-1]=vs[n-1]\n", + " elif theta[n-1]<3*pi+alpha_da:\n", + " vL[n-1]=vs[n-1]\n", + " elif theta[n-1]<4*pi+alpha_da:\n", + " vL[n-1]=-vs[n-1]\n", + " else:\n", + " vL[n-1]=vs[n-1]\n", + "\n", + "figure(1)\n", + "plot(1000*np.array(t),vL,'g.')\n", + "xlabel('time [msec]')\n", + "ylabel('Load voltage [V]')\n", + "grid()\n", + "show()\n", + "\n", + "\n", + "#part(b):\n", + "alpha_db=0.9*pi #delay angle\n", + "Vdc_b=(2*Vo/pi)*cos(alpha_db) #new dc voltage(V)\n", + "tau=L/R #time constant(s)\n", + "imo=Idc #Initial curent(A)\n", + "tzero=-tau*log((-Vdc_b/R)/(imo-Vdc_b/R))\n", + "for n in range(1,1301,1):\n", + " theta[n-1]=2*pi*(n-1)/1000\n", + " t[n-1]=theta[n-1]/w\n", + " vs[n-1]=Vo*sin(theta[n-1])\n", + " if theta< alpha_db:\n", + " vL[n-1]=-vs[n-1]\n", + " elif (theta[n-1]<pi+alpha_db):\n", + " vL[n-1]=vs[n-1]\n", + " elif theta[n-1]<2*pi+alpha_db:\n", + " vL[n-1]=-vs[n-1]\n", + " elif theta[n-1]<3*pi+alpha_db:\n", + " vL[n-1]=vs[n-1]\n", + " elif theta[n-1]<4*pi+alpha_db:\n", + " vL[n-1]=-vs[n-1]\n", + " else:\n", + " vL[n-1]=vs[n-1]\n", + "\n", + "#Results:\n", + "figure(2)\n", + "plot (1000*np.array(t), vL,'g.')\n", + "xlabel('time [msec] ')\n", + "ylabel('Load voltage [V]')\n", + "print \"part (a):\"\n", + "print \"\\n Vdc_a=\",round(1000*Vdc_a,2),\"mV\"\n", + "print \"\\n Power=\",round(P),\"W\" \n", + "print \"\\n alpha_d=\",round((180/pi)*alpha_da,1),\"degrees\"\n", + "print \"\\n part (b):\"\n", + "print \"\\n alpha_d=\",round((180/pi)*alpha_db,1),\"degrees\" \n", + "print \"\\n Vdc_b=\",round(Vdc_b,1),\"V\"\n", + "print \"\\n Current will reach zero at\",round(tzero,1),\"sec\"\n", + "grid()\n", + "show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "Populating the interactive namespace from numpy and matplotlib\n" + ] + }, + { + "output_type": "stream", + "stream": "stderr", + "text": [ + "WARNING: pylab import has clobbered these variables: ['fmod', 'cosh', 'sinh', 'trunc', 'tan', 'gamma', 'degrees', 'radians', 'sin', 'expm1', 'ldexp', 'isnan', 'frexp', 'ceil', 'copysign', 'cos', 'tanh', 'fabs', 'sqrt', 'hypot', 'log', 'log10', 'pi', 'log1p', 'floor', 'modf', 'exp', 'isinf', 'e']\n", + "`%pylab --no-import-all` prevents importing * from pylab and numpy\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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0J06fPo0NGzaYfZ0gCHjppZcQGxsLANDr9UhNTTXOh279l0NGRgb07+hx9Z9X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\nhNj0/wELMsFZawmOEgAAAABJRU5ErkJggg==\n", + "text": [ + "<matplotlib.figure.Figure at 0x1e16bd0>" + ] + }, + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "part (a):\n", + "\n", + " Vdc_a= 437.5 mV\n", + "\n", + " Power= 15.0 W\n", + "\n", + " alpha_d= 87.4 degrees\n", + "\n", + " part (b):\n", + "\n", + " alpha_d= 162.0 degrees\n", + "\n", + " Vdc_b= -9.1 V\n", + "\n", + " Current will reach zero at 4.5 sec\n" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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