Error in Correction Formula Creates Confusion
By John Copeland
Did you ever notice that when you do something right, nobody notices, but when you do something wrong, everybody spots it? When I put together the article about correcting dyno data for temperature, humidity, and barometric pressure, I tried to simplify the calculations as much as possible. Unfortunately, in so doing I went a bit too far and accidentally omitted part of the equation. The actual equation should have read:
F (the correction factor)= 1.18 (29.38/(BP-Vp)x the square root of (T+460)/537)-0.18. Also, to find Vp, find the temperature on the steam tables and multiply the corresponding factor by the relative humidity when expressed as a decimal. (i.e. 70% relative humidity should be expressed as .7) Given the environmental conditions shown on the dyno sheet, that should yield a correction factor of 1.0280698.
Just to further confuse things, the dyno sheet shown in the example for corrected data was an older one that was calculated from the SAE tables, not from this formula. The Society of Automotive Engineers (SAE) has since discontinued use of those tables for data correction and now has adopted the newer, formula-based means of correcting data. The correction factor that you arrive at from the tables is somewhat different from the one derived from the formula. Some of that is due to the fact that all the most current stuff is calculated using metric measurements; temperature in Centigrade, barometric pressure in Pascals, and so on. The differences are tiny, but all together they yield a slightly different correction factor.
I should point out, however, that it doesn't really matter how you correct your data only that you do it. Even if the data correction formula or table you use isn't the most current one, as long as you're consistent with how you adjust for temperature, humidity, and barometric pressure, you'll be able to get maximum benefit from your dyno data. Remember, if you don't normalize your data for different environmental conditions, it will be a lot less useful, comparison-wise.
In retrospect, I should have re-made the corrected data printout using the formula (including the missing factors) that was outlined in the article. Sorry for any confusion this created. It is gratifying, however, and a measure of how many readers are seriously interested in this subject, to note how many of you took the trouble to drag out your calculators and grind through the formula to discover that I was wrong. Thanks for keeping me on my toes. I'll try not to lead you astray again.