monte carlo/ worst case analysis in pspice

Hi, I am trying to study the effect of parameter variations of various components in a circuit. I read i can most likely use monte carlo or the worst case analysis in pspice. My aim is to find the worst ouput condition for the various combination of the circuit parmaeter variations. Please suggest how i can do it. I was thinking to use worst case analysis. But, i read in the OrCad spice's manunal that says the worst case analysis does not search for the set of parameter values that result in worst result. I am confused here. My aim is to find the set of parameter values that result in the worst result. Kindly suggest how i can do it. Thanks a lot. Regards, kristo

Reply to
kristo
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Imho you feed the Monte Carlo program with a range of possible variation for every circuit component. Monte Carlo then "throws dice", determines an accidental value for every component within its given range of variability and calculates the outcome for that set. And again and again, as often as you command it to repeat.

Thus you simulate the outcome of a production line, where in 100 produced sets may be 3, which fail to work (worst case). One of the three, however, may be the only one you build (at home :-)).

Eg if you choose resistors with +-5%, caps with +-10%, then there may be a combination of parts that cause your circuit to not to work as designed (worst case). Thus you may have to buy some of the caps with +-5% to avoid that.

Regards, H.

Reply to
Heinz Schmitz

Monte Carlo analysis simulates operational variation that resulting from specified component tolerances.

Worst case analysis aims to determine the single "worst" operating point for your *particular* definition of worst. For example, in an adjustable linear regulator (LM317) circuit is there a combination of setting resistors, Iadj, etc. that results in an out of band value for Vout?

  1. Determine the specified guaranteed min/max values or 1-sigma variance for applicable components.
  2. Determine which extreme value will result in your particular "worst case." In the case of components with a range of variation, determine how much risk you're willing to accept.
  3. Run the numbers.
--
Rich Webb     Norfolk, VA
Reply to
Rich Webb

Kristo, The reason that worst case analysis does not necessarily give you the actual worst case is the way it is done. During your design, you need to be sure and specify the tolerances on all your critical parts, such as resistors, capacitors, inductors, and even on your transistors. This means that each parts actual value will be in a range of values around the nominial value that you usually use in simulation.

When you do a Monte Carlo analysis, the software literaly goes to each of these parts, and throws the dice, and gives you a random value somewhere inside this range. You normally do many runs in this type of simulation, anywhere from 30 to 100, so that you get many possible combinations of your component values. Everytime you run a simulation, you get a trace of your critical output variable. After all the runs, you look at that output, and you measure the range of those responses, and see if they are within your acceptable performance. It can take quite a bit of time to run the necessary simulations, especially if you have a large and complex circuit where each individual simulation takes a lot of time, but the results can be very informative.

Now, on a worst case analysis, PSpice simplifies things a bit. It starts with a quick simulation at the nominal value. It then goes to the first toleranced part, tweaks the value a bit, and then runs another simulation, and sees if your output value goes up, or down. It repeats this process on each part, getting a direction of change for each part. Once it has done this for all the toleranced parts in your design, it does one final simulation where it takes each part and pegs its value at the extreme of its tolerance values either up, or down, in the direction indicated by those earlier simulatons. You get a choice as to whether you get the max, or the min of the output variable.

Now, the obvious question is "Why isn't this the guaranteed worst case?" for your circuit? Well, in real circuits, there are interactions between all these parts, especially in filters and other resonances, where the actuall worst possible performance is somewhere in the midst of all the possible values. The worst case analysis will miss this combination, but a Monte Carlo analysis, with enough runs, will probably get some simlulations with values near this worst case.

So, if you have the time and budget, you do MC analysis, especially on a final circuit design. However, worst case is very informative, especially in the early design stages.

Oh, and one final note. When you are setting up tolerances, you have two major choices for specifying the variation of your tolerances - uniform and guassian. If you chose uniform, then your specified tolerance is the top and bottom of the expected range. If you choose guassian, though, then be aware that your tolerance value specifies the one sigma point. When you do a worst case, it sets the part to the three sigma point, which is then three times the variation that many engineers expect! So, be warned... ;-)

Charlie

Reply to
Charlie E.

Thanks to Heinz, Webb and Charlie a lot. My special thanks to Charlie for long and detailed explanation. kristo.

Reply to
kristo

hi, Any other simulation tool that provides the features of advance analysis of Pspice .(e.g sensitivity, smoke) etc. kristo

Reply to
kristo

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