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How can I calculate core losses given only frequency?

  1. Jul 12, 2011 #1
    I cannot seem to figure this out. I know total core losses at 120Hz and 60Hz are 100w and 32w respectively for some unknown constant ac voltage. I cant seem to figure out how to go about finding core losses at other frequencies or separating eddy and hysteresis losses. Can anybody shed some light on this for me?
  2. jcsd
  3. Jul 12, 2011 #2

    The Electrician

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    Gold Member

    I used the search terms: "core losses" steinmetz

    and found this paper: http://people.clarkson.edu/~pillayp/c28.pdf [Broken]

    The paper and its references should help you.
    Last edited by a moderator: May 5, 2017
  4. Jul 13, 2011 #3
    Thanks for the reply. The problem I am having is that I don't know the max flux density Bm or what the core material is to be able to calculate Ke, Kh or n. There has to be a simple answer to this that I must be overlooking and its driving me crazy. Thanks for the link.
  5. Jul 13, 2011 #4


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    Is this a real world problem or an exercise (book problem)? I'd try the following approach for a somewhat simplistic (as in my not be completely accurate for a real world problem) solution.

    The eddy current loss component is usually modeled as proportional to [itex]B^2 f^2[/itex] and the hysteresis loss component as proportional to [itex]B^{1.6} f^1[/itex]. Here however the B^1.6 term is only a fairly rough approximation and different materials may use a slightly different constant (to 1.6) there. In any case, if we take the above relationships as correct then we can find a fairly simple solution.

    [tex]P_L = k_1 B^2 f^2 + k_2 B^{1.6} f^1[/tex]

    It's also approximately true that at constant voltage the flux will be inversely proportional to frequency.


    [tex] P_L(n) = k_1 \left( \frac{B_1}{n} \right)^2 (n f_1)^2 +k_2 \left( \frac{B_1}{n} \right)^{1.6} (n f_1)^2 [/tex]

    You don't know B but you do know that for a given voltage that B_1 is a constant so you can lump it (and f_1) with the constants k1 and k2 to get the above into a simple function of "n" (and of course the two lumped constants that you can determine from your two data points).
    Last edited: Jul 13, 2011
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