# What are the final steps to arrive at the transfer function for this RCL circuit?

What are the final steps to arrive at the transfer function for this RCL circuit?

I am attempting to arrive at this transfer function $$\dfrac{V_o(s)}{V_i(s)}=\dfrac{sL}{CL(R_1+R_2)s^2+(R_1R_2C+L)s+R_1}$$ for the following RCL circuit.

My initial problem was not knowing the correct steps to take to get from the circuit to the final TF, using the complex impedance method.

So, I have now used the KVL method, which has got me to a final transfer function. But, not the one that I desire.

$$\dfrac{I_2(s)}{V_1(s)}=\dfrac{s^2CL}{CL(R_1+R_2)s^2+(R_1R_2C+L)s+R_1}$$

Therefore, I would just like to know whether or not the last remaining step is to take $$\V_o = I_2(s)Z_c\$$, where $$\Z_c = \frac{1}{sC}\$$ and therefore multiply $$\I_2(s)\$$ by $$\\frac{1}{sC}\$$ and thus reduce the numerator from $$\s^2CL\$$ to $$\sL\$$

So, these are the steps taken using KVL:

Loop 1:

$$V_1(s) - I_1(s)R_1 - L(sI_1(s)-sI_2(s)) = 0$$

$$I_1(s)(R_1 + sL)- sLI_2(s) = V_1(s)\tag{1}$$

Loop 2:

$$I_2(s)R_2 + \frac{I_2(s)}{sC} + L(sI_2(s)-sI_1(s)) = 0$$

$$-sLI_1(s)+I_2(s)(sL+R_2+\frac{1}{sC}) = 0\tag{2}$$

From (2) I get that $$\I_1\$$

$$I_1=I_2(s)(sL+R_2+\frac{1}{sC})\frac{1}{sL}$$

$$I_1=I_2(s)(1+\frac{R_2}{sL}+\frac{1}{s^2CL})\tag{3}$$

which, when substituted into (1), gives

$$I_2(s)(1+\frac{R_2}{sL}+\frac{1}{s^2CL})(sL+R_1) - sLI_2(s) = V_1(s)\tag{4}$$

Multiplying through by $$\(sL+R_1)\$$

$$I_2(s)(sL+\frac{sLR_2}{sL}+\frac{sL}{s^2CL}+R_1+\frac{R_1R_2}{sL}+\frac{R_1}{s^2CL})-sLI_2(s)= V_1(s)\tag{5}$$

Multiplying through by $$\I_2(s)\$$

$$sLI_2(s)+\frac{sLR_2}{sL}I_2(s)+\frac{sL}{s^2CL}I_2(s)+R_1I_2(s)+\frac{R_1R_2}{sL}I_2(s)+\frac{R_1}{s^2CL}I_2(s)-sLI_2(s)= V_1(s)\tag{6}$$

cancelling out like terms, I get

$$\frac{sLR_2}{sL}I_2(s)+\frac{sL}{s^2CL}I_2(s)+R_1I_2(s)+\frac{R_1R_2}{sL}I_2(s)+\frac{R_1}{s^2CL}I_2(s)= V_1(s)$$

factoring out $$\I_2(s)\$$, I get

$$I_2(s)(\frac{R_1}{s^2CL}+\frac{R_1R_2}{sL}+\frac{1}{sC}+R_1+R_2)= V_1(s)\tag{7}$$

obtaining a common denominator, I get the following

$$I_2(s)(\frac{R_1}{s^2CL}+\frac{sR_1R_2C+sL}{s^2CL}+R_1+R_2)= V_1(s)\tag{8}$$

$$I_2(s)(\frac{R_1}{s^2CL}+\frac{sR_1R_2C+sL+s^2CL(R_1+R_2)}{s^2CL})= V_1(s)\tag{9}$$

factoring out the $$\1/s^2CL\$$, I get

$$\frac{I_2(s)}{s^2CL}(R_1+sR_1R_2C+sL+s^2CL(R_1+R_2)= V_1(s)\tag{10}$$

Rearranging in terms of $$\I_2(s)\$$ and $$\V_1(s)\$$, I get

$$\dfrac{I_2(s)}{V_1(s)}=\dfrac{s^2CL}{CL(R_1+R_2)s^2+(R_1R_2C+L)s+R_1}\tag{11}$$

So, is the last step to take $$\V_o = I_2(s)Z_c\$$, where $$\Z_c = \frac{1}{sC}\$$ and therefore multiply $$\I_2(s)\$$ by $$\\frac{1}{sC}\$$ whereby reducing the numerator from $$\s^2CL\$$ to $$\sL\$$?

• A thought just crossed my mind. Is it correct to assume that Vo = I_2(s) x Zc and therefore, can divide I_2(s) by 1/sC and thus reduce the numerator to sL? Commented Apr 1, 2021 at 22:39
• The original transfer function looks right. The one at top of your question. Are you just trying to figure out how it gets made?
– jonk
Commented Apr 1, 2021 at 23:46
• Or do you want the voltage gain, $K$?
– jonk
Commented Apr 2, 2021 at 0:32
• @jonk I am trying to figure out how to get to the the original transfer function. Tried the complex impedance method first and couldn't quite get there. So, I thought I'd try the KVL method, which has brought me closer to the original TF. So, just trying to confirm the last couple of steps to get output voltage/input voltage TF! Commented Apr 2, 2021 at 0:54
• I'll post something, then. I've not checked my work and I may have made a mistake in it. But I'm just following a "mental flowchart" that I usually apply with success. So you can see if it fits your needs. (I had copied some text I had to correct. Sorry about that.)
– jonk
Commented Apr 2, 2021 at 0:56

simulate this circuit – Schematic created using CircuitLab

Above, you can see that $$\R_2\$$ and $$\Z_2\$$ form a voltage divider that divides $$\V_Y\$$ into $$\V_\text{OUT}\$$. It follows that:

\begin{align*} \text{Each Stage} \left\{ \begin{array}{rl} V_\text{OUT} = V_Y\,\frac{1}{1+\frac{R_2}{Z_2}}&&Z_2 = \left(Z_{C_1}\mid\mid \infty\right)=Z_{C_1}\\\\ V_Y = V_\text{IN}\,\frac{1}{1+\frac{R_1}{Z_1}}&&Z_1 = Z_{L_1}\mid\mid \left(Z_2 + R_2\right) \end{array} \right. \end{align*} $$\therefore \frac{V_\text{OUT}}{V_\text{IN}}=\frac{1}{1+\frac{R_1}{Z_1}}\cdot\frac{1}{1+\frac{R_2}{Z_2}}$$

From that, I get:

$$H\left(s\right)=\frac{L_1\,s}{L_1\,C_1\left(R_1+R_2\right)s^2+\left(R_1\,R_2\,C_1+L_1\right)s+R_1}$$

That is not in standard form, though. To get started, you want to divide through so that you isolate $$\s^2\$$ in the denominator. So, something like this to start:

$$H\left(s\right)=\frac{\frac{1}{C_1\left(R_1+R_2\right)}\,s}{s^2+\frac{R_2\,C_1+\frac{L_1}{R_1}}{L_1\,C_1\left(1+\frac{R_2}{R_1}\right)}\,s+\frac{1}{L_1\,C_1\left(1+\frac{R_2}{R_1}\right)}}$$

Set $$\\alpha=\frac12\cdot \frac{R_2\,C_1+\frac{L_1}{R_1}}{L_1\,C_1\left(1+\frac{R_2}{R_1}\right)}\$$, $$\\omega_{_0}=\frac{1}{\sqrt{L_1\,C_1\left(1+\frac{R_2}{R_1}\right)}}\$$, and create the unitless damping factor of $$\\zeta=\frac{\alpha}{\omega_{_0}}\$$.

The standard form for a 2nd order bandpass is:

$$H\left(s\right)=K\cdot \frac{2\zeta\,\omega_{_0}\,s}{s^2+2\zeta\,\omega_{_0}\,s+\omega_{_0}^2}$$

Where $$\K\$$ is the voltage gain. You can now solve for $$\K\$$.

It may be convenient to set $$\\tau_{_1}=\frac{L_1}{R_1}\$$ and $$\\tau_{_2}=R_2\,C_1\$$.

Then you should find:

$$K=\frac{1}{1+\frac{\tau_{_2}}{\tau_{_1}}}$$

With all values set to 1, as you show, this means $$\K=\frac12\$$ or $$\-6\;\text{dB}\$$.

Let's re-examine $$\H\left(s\right)\$$ with some light from above.

We know that $$\\omega_{_0}\cdot \tau_{_0}=1\$$, so it follows that: $$\\tau_{_0}=\sqrt{L_1\,C_1\left(1+\frac{R_2}{R_1}\right)}\$$

Let's follow through with some algebra and replacements:

\begin{align*} H\left(s\right)&=\frac{\frac{1}{C_1\left(R_1+R_2\right)}\,s}{s^2+\frac{R_2\,C_1+\frac{L_1}{R_1}}{L_1\,C_1\left(1+\frac{R_2}{R_1}\right)}\,s+\frac{1}{L_1\,C_1\left(1+\frac{R_2}{R_1}\right)}}\\\\ &=\frac{\frac{\frac{L_1}{R_1}}{L_1\,C_1\left(1+\frac{R_2}{R_1}\right)}\,s}{s^2+\frac{R_2\,C_1+\frac{L_1}{R_1}}{L_1\,C_1\left(1+\frac{R_2}{R_1}\right)}\,s+\frac{1}{L_1\,C_1\left(1+\frac{R_2}{R_1}\right)}}\\\\ &=\frac{\tau_{_1}\,\omega_{_0}^2\,s}{s^2+\left(\tau_{_1}+\tau_{_2}\right)\omega_{_0}^2\,s+\omega_{_0}^2} \end{align*}

From this, we can fathom that the damping factor is $$\\zeta=\frac12\,\left(\tau_{_1}+\tau_{_2}\right)\omega_{_0}\$$. (Look back at the definitions for $$\\alpha\$$, $$\\omega_{_0}\$$, and $$\\zeta\$$ earlier above.)

Looking only at the numerator now, we know that $$\K\,2\zeta\,\omega_{_0}=K\,2\left(\frac12\,\left(\tau_{_1}+\tau_{_2}\right)\omega_{_0}\right)\,\omega_{_0}=\tau_{_1}\,\omega_{_0}^2\$$ or that $$\K\left(\tau_{_1}+\tau_{_2}\right)=\tau_{_1}\therefore K=\frac{\tau_{_1}}{\tau_{_1}+\tau_{_2}}=\frac{1}{1+\frac{\tau_{_2}}{\tau_{_1}}}\$$

Q.E.D.

I hadn't realized you wanted the branch current through $$\R_2\$$ and $$\C_1\$$ divided by $$\V_\text{IN}\$$, before. But everything is present above to develop it. Take the equation for $$\V_Y\$$ from above and divide it by the branch impedance, $$\R_2+Z_{C_1}\$$:

\begin{align*} I&=\frac{V_Y}{R_2+Z_{C_1}} = V_\text{IN}\,\frac{1}{1+\frac{R_1}{Z_1}}\,\frac{1}{R_2+Z_{C_1}}\\\\&\therefore\\\\ \frac{I}{V_\text{IN}}&=\frac{L_1\,C_1\,s^2}{L_1\,C_1\left(R_1+R_2\right)s^2+\left(R_1\,R_2\,C_1+L_1\right)s+R_1} \end{align*}

But the easier way to see the above result is to just go back to your $$\\frac{V_\text{OUT}}{V_\text{IN}}\$$ transfer function. $$\V_\text{OUT}\$$ is riding on top of $$\C_1\$$. So the branch current is $$\I=\frac{V_\text{OUT}}{Z_2}\$$. All you have to do is:

$$\frac{I}{V_\text{IN}}=\frac{V_\text{OUT}}{V_\text{IN}}\cdot \frac{I}{V_\text{OUT}}=\frac{V_\text{OUT}}{V_\text{IN}}\cdot\frac1{Z_2}=\frac{V_\text{OUT}}{V_\text{IN}}\cdot \bigg[C_1\, s\bigg]$$

Nothing at all difficult to see.

## Final note to OP on using sympy for problems such as the above

Since you expressed an interest in sympy (which I most certainly recommend to you), I'll disclose below what I did to save myself time (and mindless mistakes) when creating the equations I used above.

(I also recommend including a numeric solver, SageMath. I use Sage with sympy, myself. Be sure to google around to see how others have installed both on your operating system of choice.)

I entered the following, to get started:

var('vin vout vy l1 c1 r1 r2 s')
z2=1/s/c1
z1=(s*l1)*(z2+r2)/(s*l1+z2+r2)
hs=simplify(1/(1+r1/z1)/(1+r2/z2))


Then I write the first line below, which printed out the second line:

hs
l1*s/(l1*s*(c1*r2*s + 1) + r1*(c1*s*(l1*s + r2) + 1))


Well, sympy has its own style of generating "best output" by factoring things. I didn't like it much, so I wrote something to just grab the denominator, expand it (un-factor it) out, and then factor it back over 's', instead. The first line is what I wrote; the second line is what it gave back:

factor(expand(fraction(hs)[1]),s)
r1 + s**2*(c1*l1*r1 + c1*l1*r2) + s*(c1*r1*r2 + l1)


Now, that looks a lot better.

Pretty easy, right??

But then I wanted "standard form." So now the following (a is $$\\alpha\$$, w0 is $$\\omega_{_0}\$$, etc):

a=(r1*r2*c1+l1)/2/l1/c1/(r1+r2)
w0=sqrt(r1/l1/c1/(r1+r2))
zeta=a/w0


I knew that $$\K=\frac{H\left(s\right)}{\left[\frac{2\zeta\,\omega_{_0}\,s}{s^2+2\zeta\,\omega_{_0}\,s+\omega_{_0}^2}\right]}\$$, so I added:

K=simplify(hs/((2*zeta*w0*s)/(s**2+2*zeta*w0*s+w0*w0)))


To see what that was:

K
l1/(c1*r1*r2 + l1)


Well, this immediately told me something important. Divide top and bottom by $$\L_1\$$ and I get: $$\\frac{1}{1+\frac{R_2\,C_1}{\frac{L_1}{R_1}}}\$$. (The denominator is unitless, as it must be. And so I kept both factors in terms of time so that the unit cancellation was obvious. )

That's probably enough for now. You get the idea. It's really easy!

Sage, if you use it, has its own "shell variable" called "SAGE_STARTUP_FILE" which you can set to some file. When you start Sage from a shell command, it will load that file and execute the lines as if you typed them. Saves time. In my case, to get the bits of sympy I often use, my file starts this way:

%colors linux
from sympy import *
from sympy.solvers import solve


Because it's easy to do and because I sometimes want to look at different Butterworth filters without having to go find a manual on it, I add these lines, as well:

def Butterworth(n):
r = solve( 1+(-1)**n*x**(2*n), x )
t = []
for a in r:
if real( a ) < 0:
t.append( a )
t.sort( key = lambda tup: real( tup ) )
u = []
var( 's' )
if ( len( t ) - 2*int( len( t ) / 2 ) ) == 1:
u.append( s + 1 )
t.pop( 0 )
for i in range( len( t ) / 2 ):
scnd = collect(expand((s - t[2*i])*(s - t[2*i+1])), I, evaluate=False)[1]
n, d = fraction( scnd )
co = [collect_sqrt( simplify( r ) ) for r in Poly( n, s ).all_coeffs()]
spwr = simplify( s**(len( co )-1) )
ufactor = 0
for j in co:
ufactor = ufactor + spwr * factor( j/d )
spwr = simplify( spwr/s )
u.append( ufactor )
return u


This allows me to write:

for x in Butterworth(2): simplify(x)
s**2 + sqrt(2)*s + 1


If I want the numbers, instead, then:

for x in Butterworth(2): simplify(x.n())
s**2 + 1.4142135623731*s + 1.0


Let's try something a little higher order, done both with irrationals as well as just approximate real numbers:

for x in Butterworth(4): simplify(x)
s**2 + s*(sqrt(4 - 2*sqrt(2)) + sqrt(2*sqrt(2) + 4) + 2*sqrt(sqrt(2) + 2))/4 + 1
s**2 + s*(-sqrt(4 - 2*sqrt(2)) + 2*sqrt(2 - sqrt(2)) + sqrt(2*sqrt(2) + 4))/4 + 1
for x in Butterworth(4): simplify(x.n())
s**2 + 1.84775906502257*s + 1.0
s**2 + 0.765366864730179*s + 1.0


Ah! But I wanted a 12th order Butterworth:

for x in Butterworth(12): simplify(x.n())
s**2 + 1.98288972274762*s + 1.0
s**2 + 1.84775906502257*s + 1.0
s**2 + 1.58670668058247*s + 1.0
s**2 + 1.21752285801744*s + 1.0
s**2 + 0.765366864730179*s + 1.0
s**2 + 0.261052384440103*s + 1.0


Well, I'm insane now. I'm going to design myself a 23rd order Butterworth filter because... well because I can:

for x in Butterworth(23): simplify(x.n())
s + 1.0
s**2 + 1.98137189207266*s + 1.0
s**2 + 1.9258345746956*s + 1.0
s**2 + 1.83442260301091*s + 1.0
s**2 + 1.70883880909298*s + 1.0
s**2 + 1.55142258140884*s + 1.0
s**2 + 1.36510628643731*s + 1.0
s**2 + 1.15336064422973*s + 1.0
s**2 + 0.920130075462304*s + 1.0
s**2 + 0.669759224341972*s + 1.0
s**2 + 0.406912026105268*s + 1.0
s**2 + 0.136484826729342*s + 1.0


Now, do you know where I can find the constants for a 23rd order Butterworth? (If so, I'll just use this: "for x in Butterworth(100): simplify(x.n())" and push up the ante a bit.)

In short, you can develop your own functions and solutions for a variety of electronic needs. I have. Pretty much anything is at your fingertips.

I sometimes want to develop my own diode equations for various LED devices. I grab a bunch of random devices from the bag and make three measurements on each one. (I do have to use a 5-digit multimeter, or better, to get necessary precision and reasonable accuracy. I have a 6.5 digit one from HP.) In this way, I can collect up the LED parameters and examine their distributions. This tells me a lot about their manufacturer and their strategies in selling them through the supplier I bought from.

So I wrote this:

def diode():
print( "This program uses 3 diode measurements to extract parameters." )
print( "You will need to have taken these measurements beforehand." )
print( "Enter each point as [ <diode current>, <diode voltage> ]." )
print( "" )
TA= int( input( "Enter the ambient temperature in Celsius (default is 27 C): " ) or "27" )
print( "" )
VT= 8.61733034e-5 * ( 273.15 + TA )
POINTS= []
vd, id, N, ISAT, RS= symbols( "vd id N ISAT RS" )
for i in range(3):
pid, pvd= input( "Enter point " + str(i) + ": " ).split()
POINTS.append( { vd: pvd, id: pid } )
EQS= []
for i in range(3):
EQS.append( Eq( POINTS[i][vd], RS*POINTS[i][id] + N*VT*ln(POINTS[i][id]) - N*VT*ISAT ) )
print( POINTS )
print( EQS )
ANS= solve( EQS, [ RS, N, ISAT ] )[0]
print( "RS   = " + str(ANS[0]) )
print( "N    = " + str(ANS[1]) )
print( "ISAT = " + str(exp(ANS[2])) )


This program generates the model parameters I want for any LED I have in my hand from just three distinct measurement points, $$\\left(V_i, I_i\right)\$$.

By the way, if you think I'm joking about 100th order Butterworth? Here it is:

for x in Butterworth(100): simplify(x.n())
s**2 + 1.99975326496332*s + 1.0
s**2 + 1.99777974992394*s + 1.0
s**2 + 1.99383466746626*s + 1.0
s**2 + 1.98792191091036*s + 1.0
s**2 + 1.98004731543312*s + 1.0
s**2 + 1.97021865230955*s + 1.0
s**2 + 1.95844562124353*s + 1.0
s**2 + 1.94473984079535*s + 1.0
s**2 + 1.9291148369156*s + 1.0
s**2 + 1.91158602959666*s + 1.0
s**2 + 1.89217071765509*s + 1.0
s**2 + 1.87088806165973*s + 1.0
s**2 + 1.84775906502257*s + 1.0
s**2 + 1.82280655327089*s + 1.0
s**2 + 1.79605515152123*s + 1.0
s**2 + 1.76753126017739*s + 1.0
s**2 + 1.73726302887638*s + 1.0
s**2 + 1.70528032870818*s + 1.0
s**2 + 1.67161472273654*s + 1.0
s**2 + 1.63629943485005*s + 1.0
s**2 + 1.59936931697418*s + 1.0
s**2 + 1.56086081467666*s + 1.0
s**2 + 1.52081193120006*s + 1.0
s**2 + 1.47926218995722*s + 1.0
s**2 + 1.43625259552638*s + 1.0
s**2 + 1.39182559318463*s + 1.0
s**2 + 1.34602502701955*s + 1.0
s**2 + 1.29889609666037*s + 1.0
s**2 + 1.25048531267141*s + 1.0
s**2 + 1.20084045065177*s + 1.0
s**2 + 1.15001050408656*s + 1.0
s**2 + 1.09804563599626*s + 1.0
s**2 + 1.0449971294319*s + 1.0
s**2 + 0.990917336864815*s + 1.0
s**2 + 0.935859628521147*s + 1.0
s**2 + 0.87987833971183*s + 1.0
s**2 + 0.823028717210218*s + 1.0
s**2 + 0.765366864730179*s + 1.0
s**2 + 0.706949687558514*s + 1.0
s**2 + 0.647834836396299*s + 1.0
s**2 + 0.588080650464608*s + 1.0
s**2 + 0.527746099930746*s + 1.0
s**2 + 0.466890727711811*s + 1.0
s**2 + 0.405574590713025*s + 1.0
s**2 + 0.343858200558819*s + 1.0
s**2 + 0.281802463875165*s + 1.0
s**2 + 0.219468622182091*s + 1.0
s**2 + 0.15691819145569*s + 1.0
s**2 + 0.0942129014192853*s + 1.0
s**2 + 0.0314146346236414*s + 1.0


Of course, that's all theoretical! Assuming a sufficiently precise VNA even existed, you might be sitting around for a long time tweaking it using its time domain function.

• Comments are not for extended discussion; this conversation has been moved to chat. Commented Apr 3, 2021 at 6:38