PWM
In the circuit given below, the switches are operated using the pulse width modulation technique. The modulation voltage is $m(t)$, and the triangular carrier voltage is $v_c(t)$. The switch S1 is turned on when $m(t) > v_c(t)$, and the switch S2 is turned on otherwise. The parameter values are $R=12\,\Omega$, $L=0.1\,$H, $f_c=1\,$kHz, and $V_{dc}=200\,$V. If the modulation voltage is $m(t)=2\,\sin (100\,\pi\,t)$, what is the RMS value of the $50\,$Hz component of the load current $i_L$?In [1]:
from IPython.display import Image
Image(filename =r'pwm_6_fig_1.png', width=500)
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In [2]:
# run this cell to view the circuit file.
%pycat pwm_6_orig.in
We now replace the strings such as \$Vdc, \$L, with the values of our choice by running the python script given below. It takes an existing circuit file pwm_6_orig.in and produces a new circuit file pwm_6.in, after replacing \$Vdc, \$L, etc. with values of our choice.
In [3]:
import gseim_calc as calc
s_Vdc = "200"
s_L = "0.1"
s_R = "12"
s_f_carrier = "1e3"
s_M = "2"
s_dt_min = "1e-6"
s_dt_nrml = "10e-6"
s_f_sin = "50"
f_sin = float(s_f_sin)
T = 1/f_sin
s_2T = ("%11.4E"%(2.0*T)).strip()
l = [
('$Vdc', s_Vdc),
('$L', s_L),
('$R', s_R),
('$f_carrier', s_f_carrier),
('$f_sin', s_f_sin),
('$2T', s_2T),
('$M', s_M),
('$dt_min', s_dt_min),
('$dt_nrml', s_dt_nrml)
]
calc.replace_strings_1("pwm_6_orig.in", "pwm_6.in", l)
print('pwm_6.in is ready for execution')
pwm_6.in is ready for execution
Execute the following cell to run GSEIM on pwm_6.in.
In [4]:
import os
import dos_unix
# uncomment for windows:
#dos_unix.d2u("pwm_6.in")
os.system('run_gseim pwm_6.in')
get_lib_elements: filename gseim_aux/xbe.aux get_lib_elements: filename gseim_aux/ebe.aux Circuit: filename = pwm_6.in Circuit: n_xbeu_vr = 4 Circuit: n_ebeu_nd = 5 main: i_solve = 0 main: calling solve_trns Transient simulation starts... i=0 i=1000 i=2000 i=3000 i=4000 solve_trns_exc completed. GSEIM: Program completed.
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0
The circuit file (pwm_6.in) is created in the same directory as that used for launching Jupyter notebook. The last step (i.e., running GSEIM on pwm_6.in) creates a data file called pwm_6.datin the same directory. We can now use the python code below to compute/plot the various quantities of interest.
In [5]:
import numpy as np
import matplotlib.pyplot as plt
import gseim_calc as calc
from setsize import set_size
slv = calc.slv("pwm_6.in")
i_slv = 0
i_out = 0
filename = slv.l_filename_all[i_slv][i_out]
print('filename:', filename)
u = np.loadtxt(filename)
t = u[:, 0]
col_v_out = slv.get_index(i_slv,i_out,"v_out")
col_IR = slv.get_index(i_slv,i_out,"IR" )
col_ISrc1 = slv.get_index(i_slv,i_out,"ISrc1")
col_ISrc2 = slv.get_index(i_slv,i_out,"ISrc2")
col_P_R = slv.get_index(i_slv,i_out,"P_R" )
col_g1 = slv.get_index(i_slv,i_out,"g1" )
col_g2 = slv.get_index(i_slv,i_out,"g2" )
col_s = slv.get_index(i_slv,i_out,"s" )
col_t = slv.get_index(i_slv,i_out,"t" )
# since we have stored two cycles, we need to divide the last time point
# by 2 to get the period:
T = t[-1]/2
l_IR = calc.avg_rms_2(t, u[:,col_IR], T, 2.0*T, 1.0e-4*T)
l_v_out = calc.avg_rms_2(t, u[:,col_v_out], T, 2.0*T, 1.0e-4*T)
l_P_R = calc.avg_rms_2(t, u[:,col_P_R], T, 2.0*T, 1.0e-4*T)
l_ISrc1 = calc.avg_rms_2(t, u[:,col_ISrc1], T, 2.0*T, 1.0e-4*T)
print('rms load voltage:', "%11.4E"%l_v_out[2][0])
print('average source current:', "%11.4E"%l_ISrc1[1][0])
print('average power delivered to load:', "%11.4E"%l_P_R[1][0])
color1='green'
color2='crimson'
color3='goldenrod'
color4='blue'
color5='cornflowerblue'
fig, ax = plt.subplots(4, sharex=False)
plt.subplots_adjust(wspace=0, hspace=0.0)
set_size(7, 7, ax[0])
for i in range(4):
ax[i].set_xlim(left=0, right=T*1e3)
ax[0].grid(color='#CCCCCC', linestyle='solid', linewidth=0.5)
ax[1].grid(color='#CCCCCC', linestyle='solid', linewidth=0.5)
ax[2].grid(color='#CCCCCC', linestyle='solid', linewidth=0.5)
ax[3].grid(color='#CCCCCC', linestyle='solid', linewidth=0.5)
ax[0].plot((t-T)*1e3, u[:,col_t ], color=color5, linewidth=1.0, label="$t$")
ax[0].plot((t-T)*1e3, u[:,col_s ], color=color4, linewidth=1.0, label="$s$")
ax[1].plot((t-T)*1e3, u[:,col_v_out], color=color1, linewidth=1.0, label="$V_{out}$")
ax[2].plot((t-T)*1e3, u[:,col_ISrc1], color=color3, linewidth=1.0, label="$i_1$")
ax[3].plot((t-T)*1e3, u[:,col_IR ], color=color2, linewidth=1.0, label="$i_L$")
ax[1].set_ylabel(r'$V_{out}$', fontsize=14)
ax[2].set_ylabel(r'$i_1$', fontsize=14)
ax[3].set_ylabel(r'$i_L$', fontsize=14)
ax[3].set_xlabel('time (msec)', fontsize=14)
ax[0].legend(loc = 'lower right',frameon = True, fontsize = 10, title = None,
markerfirst = True, markerscale = 1.0, labelspacing = 0.5, columnspacing = 2.0,
prop = {'size' : 12},)
ax[0].tick_params(labelbottom=False)
ax[1].tick_params(labelbottom=False)
ax[2].tick_params(labelbottom=False)
#plt.tight_layout()
plt.show()
filename: pwm_6.dat rms load voltage: 2.0000E+02 average source current: 1.9189E-01 average power delivered to load: 5.3964E+01
In [6]:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import (MultipleLocator, AutoMinorLocator)
import gseim_calc as calc
from setsize import set_size
slv = calc.slv("pwm_6.in")
i_slv = 0
i_out = 0
filename = slv.l_filename_all[i_slv][i_out]
print('filename:', filename)
u = np.loadtxt(filename)
t = u[:, 0]
col_v_out = slv.get_index(i_slv,i_out,"v_out")
col_IR = slv.get_index(i_slv,i_out,"IR" )
col_ISrc1 = slv.get_index(i_slv,i_out,"ISrc1")
col_ISrc2 = slv.get_index(i_slv,i_out,"ISrc2")
col_P_R = slv.get_index(i_slv,i_out,"P_R" )
col_g1 = slv.get_index(i_slv,i_out,"g1" )
col_g2 = slv.get_index(i_slv,i_out,"g2" )
col_s = slv.get_index(i_slv,i_out,"s" )
col_t = slv.get_index(i_slv,i_out,"t" )
# since we have stored two cycles, we need to divide the last time point
# by 2 to get the period:
T = t[-1]/2
# compute Fourier coeffs:
t_start = T
t_end = 2.0*T
n_fourier = 45
coeff_IR, thd_IR = calc.fourier_coeff_1C(t, u[:,col_IR],
t_start, t_end, 1.0e-8, n_fourier)
coeff_v_out, thd_v_out = calc.fourier_coeff_1C(t, u[:,col_v_out],
t_start, t_end, 1.0e-8, n_fourier)
coeff_ISrc1, thd_ISrc1 = calc.fourier_coeff_1C(t, u[:,col_ISrc1],
t_start, t_end, 1.0e-8, n_fourier)
print("THD (load current): ", "%5.2f"%(thd_IR*100.0), "%")
print("load current fundamental: RMS value: ", "%11.4E"%(coeff_IR[1]/np.sqrt(2.0)))
print("THD (load voltage): ", "%5.2f"%(thd_v_out*100.0), "%")
print("load voltage fundamental: RMS value: ", "%11.4E"%(coeff_v_out[1]/np.sqrt(2.0)))
print("DC source current fundamental: RMS value: ", "%11.4E"%(coeff_ISrc1[1]/np.sqrt(2.0)))
print("DC source current 1st harmonic: RMS value: ", "%11.4E"%(coeff_ISrc1[2]/np.sqrt(2.0)))
x = np.linspace(0, n_fourier, n_fourier+1)
y_IR = np.array(coeff_IR)
y_v_out = np.array(coeff_v_out)
y_ISrc1 = np.array(coeff_ISrc1)
fig, ax = plt.subplots(3, sharex=False)
plt.subplots_adjust(wspace=0, hspace=0.0)
grid_color='#CCCCCC'
set_size(7, 6, ax[0])
delta = 5.0
x_major_ticks = np.arange(0.0, (float(n_fourier+1)), delta)
x_minor_ticks = np.arange(0.0, (float(n_fourier+1)), delta/5)
for i in range(3):
ax[i].set_xlim(left=-1.0, right=float(n_fourier))
ax[i].set_xticks(x_major_ticks)
ax[i].set_xticks(x_minor_ticks, minor=True)
ax[i].grid(visible=True, which='major', axis='x', color=grid_color, linestyle='-', zorder=0)
# ax[i].grid(visible=True, which='minor', axis='x', color=grid_color, linestyle='-', zorder=0)
ax[0].set_ylabel('$i_{load}$',fontsize=14)
ax[1].set_ylabel('$v_{out}$', fontsize=14)
ax[2].set_ylabel('$i_1$', fontsize=14)
ax[2].set_xlabel('N', fontsize=14)
bars1 = ax[0].bar(x, y_IR, width=0.3, color='red', label="$i_{load}$", zorder=3)
bars2 = ax[1].bar(x, y_v_out, width=0.3, color='blue', label="$V_{out}$", zorder=3)
bars3 = ax[2].bar(x, y_ISrc1, width=0.3, color='green', label="$i_1$", zorder=3)
plt.tight_layout()
plt.show()
filename: pwm_6.dat THD (load current): 12.37 % load current fundamental: RMS value: 2.1024E+00 THD (load voltage): 264.56 % load voltage fundamental: RMS value: 7.0715E+01 DC source current fundamental: RMS value: 1.0546E+00 DC source current 1st harmonic: RMS value: 2.5060E-01
This notebook was contributed by Prof. Nakul Narayanan K, Govt. Engineering College, Thrissur. He may be contacted at nakul@gectcr.ac.in.
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