They are reasonable to an extent. They suffer from the very big problem that they assume that you know what beta is, or at least that it is constrained to be within a pretty narrow margin. But with most small-signal transistors, the uncertainty in beta covers a range of a factor of five to ten, making the biasing selections difficult.
That paper uses one of four common large-signal models. Two are T-shaped topologies and two are pi-shaped topologies. In each topology, one is a current-driven model and the other is a voltage-driven model. They are all equivalent, but computationally they are not (meaning you do different computations but end up with the same end results). Which one is "best" depends on what you know and what you don't and how the transistor interacts with the circuitry around. One big problem with using either of the current-driven models is that you don't know beta very well, so it is usually better to use the voltage driven models when possible.
For small-signal models you have the same four options as far as models go. There is no requirement to use the same model for large signal as for small signal. In fact, that paper uses a current controlled pi model for large signal and a T-model for small signal. The hybrid-pi model is by far the more commonly used model, especially for some circuit topologies, because it can often neatly separate the input side of the circuit from the output side of the circuit with a very simple interaction between them. This is usually not the case with the T-model.
But in the cases of all of the models, the origin of all of the small-signal parameters is the application of superposition:
Define the following relations
i_C(t) = f(v_BE(t)) <<== Total response to total input
I_C(t) = f(V_BE(t)) <<== Large-signal response to large-signal input (almost always DC)
i_c(t) = f(v_be(t)) <<== Small-signal response to small-signal input
Then we HOPE to have the following:
v_BE(t) = V_BE(t) + v_be(t)
i_C(t) = f(V_BE(t) + v_be(t))
i_C(t) = f(V_BE(t)) + f(v_be(t)) <== This step uses superposition and therefore requires the circuit to behave linearly.
i_C(t) = I_C(t) + i_c(t)
The problem is that this DOES NOT WORK because f(v_be) is highly nonlinear. If you attempt to use the same model for both, you will get wrong results because the overall circuit behavior is highly non-linear and superposition is only valid for linear models.
The solution is use a DIFFERENT model of the transistor for the small-signal case than is used for the large-signal case.
I_C(t) = f(V_BE(t)) <<== Large-signal response to large-signal input (almost always DC) using a LARGE-SIGNAL model
i_c(t) = g(v_be(t)) <<== Small-signal response to small-signal input using a SMALL-SIGNAL model
Now we have
i_C(t) = f(V_BE(t)) + g(v_be(t)) <== This step uses superposition and therefore requires the circuit to behave linearly in the vicinity of f(V_BE(t)).
i_C(t) = I_C(t) + i_c(t)
Well, f(V_BE(t)) is whatever model adequately describes the relationship between i_C(t) and v_BE(t) for the entire region of interest (usually just the active region, as we generally want to avoid cutoff and saturation (but not always)). In other words, it simply the same model as would be used for f(v_BE(t)).
The Ebers-Moll model, either the basic model or one of the variants that incorporate other effects, such as the Early effect and high-frequency parasitics, are the usual choice.
But how due we get g(v_be)?
That comes down to calculus.
Given any continuous function, y(x), we can approximate y(x) in the vicinity of X_o using The first two terms of a Taylor series expansion:
\(
y \left( x \right) \; \approx \; y \left( X_0 \right) + y'(X_0) \left( x \; - \; X_0 \right)
\)
In case, y(x) is f(v_BE) which relates a current (the collector current) to a voltage (the base-emitter voltage).
X_o is the bias point, V_BE, and (x - X_o) is (v_BE - V_BE), which is simply v_be per our definition above.
Hence
\(
y \left( v_{BE} \right) \; \approx \; f \left( V_{BE} \right) + f'(V_{BE}) v_{be}
\)
Note that f'(v) is the rate of change of a current with respect to a voltage, hence it will have units of current per voltage. These happen to be the same units as conductance, and hence the reciprocal has units of resistance. However, in both cases it is NOT a conductance nor a resistance, which relates the voltage across a device to the current through that device, but rather a transconductance or a transresistance because it relates the current at one port (the collector) to the voltage across a different port (the base-emitter). Hence, just like a voltage-controlled current source in a DC circuit analysis problem, it is NOT a physical resistor.
So we define the small-signal transconductance, g_m, as
\(
g_m \; \equiv \; \left. \frac{ di_C \left( v_{BE} \right) ) }{ dv_{BE} } \right|_{V_{BE}}
\)
This means our g() function is
\(
g \left( v_{be} \right) \; = \; g_m \cdot v_{be}
\)
So what is gm for the basic Ebers-Moll model for a BJT transistor?
\(
i_C \; = \; I_S \left( e^{\frac{v_{BE}}{V_T}} \; - \; 1 \right) \; \approx \; I_S e^{\frac{v_{BE}}{V_T}} \\
g_m \; = \; \left. \frac{ di_C \left( v_{BE} \right) ) }{ dv_{BE} } \right|_{V_{BE}} \\
g_m \; = \; \left. \frac{d}{dv_{BE}} I_S e^{\frac{v_{BE}}{V_T}} \right|_{V_{BE}} \\
g_m \; = \; \left. \frac{ I_S e^{\frac{v_{BE}}{V_T}}}{V_T} \right|_{V_{BE}} \\
g_m \; = \; \frac{ I_S e^{\frac{V_{BE}}{V_T}}}{V_T} \\
g_m \; = \; \frac{ I_C }{V_T}
\)
Do you NOW see that THIS is how gm came to be associated with Ic/VT? That is was NOT defined as I_C/VT and then somehow, miraculously, we discovered that it was useful for small-signal analysis? It evolved directly from the very concept of crafting a linear small-signal model of the transistor's response in the vicinity of a large-signal bias point.
Furthermore, it ONLY has meaning within the small-signal portion of the response. It has NO meaning in the DC response. The DC current does NOT flow through re (which comes directly from backing out the T-model circuit equivalent using the small signal model relation above).
The DC response is ENTIRELY determined by the Ebers-Moll model (or whatever model is used) with NO NEED for ANY use of ANY of the parameters or results from g(v_be).
Also, do you see that re is NOT 1/gm?
It's close. Close enough that we often use it as an approximation. But can you see what it needs to be in order to make the T-model consistent with the mathematics of the small-signal model?
Now, if you want to expand the response so that it remains sufficiently valid for larger values of v_be, then the place to start is to add a quadratic term to the Taylor series expansion. But doing so would almost always (notice I am not saying always) be counterproductive, because the entire reason for using gm is because we either want a response that is very close to being linear or because we want to leverage the powerful tools we have at our disposal for designing and analyzing linear systems (and often both). If we don't want either of those, then there would seldom be a reason not to simply use the full model.
Hello again,
Well again you seem to be talking about other models and other techniques. That's not the point of this all the point is to start with the model they are calling "T" and go from there. It just doesnt matter what other techniques there are they will be a side note that's about it, and that is even if they are better than that one model shown.
I feel that you are right about some of this stuff but it just doesnt matter at least right now. The main point was if you understood the model they were showing on that and many other web sites and in books around the world.
I think you do though, at least in part, be cause you mentioned something about it being ok if we know what Beta is. But, that's another detail not needed at this time as that will come later just like any other design check would have. Later we can check on the effect of Beta.
I would think by now we all know there are better techniques to start with but I will still go over your notes though it looks interesting also.
So to recap:
There are better techniques to START with. This idea start with a PARTICULAR technique and goes from there. The idea is to improve on that particular technique and show an interesting problem that comes up.
It should be noted that the technique that is shown in that image before is an accepted technique and it isnt extremely bad but there are interesting ways to improve it that are not that hard to do or to implement.
This will all come out later.
I guess i have to say though if you are not interested in this then this idea will not do you any good. It's not the end of the world you can use whatever method you like im not suggesting that everyone suddenly switch to this method either. It's just another new look at an old method.



