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TECHNICAL MOTOBRICK WRENCHING In Remembrance of Inge K. => The Motobrick Workshop => Topic started by: rbm on June 09, 2018, 10:48:32 PM
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There has been a popular graph floating around that shows the negative temperature coefficient response of the temperature sensor used in the 2 valve K100 bikes. It has been difficult to read a given resistance given a particular temperature on this graph. I thought I'd improve that graph.
Today, I recorded a set of data from a new temperature sensor that was obtained from Euro Motoelectric. I've included the Excel sheet with the raw data and the resulting graph as a PNG graphic file. The raw sensor data is attached as a ZIP file.
The vertical axis is resistance in Ohms between one of the terminals and the body of the NTC temperature sensor, the horizontal axis is temperature in °C.
Click link to download. ⬇︎
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:2thumbup: Much appreciated thanks Robert.
Regards Martin.
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Always loved your work, your posts & your effort in explainig to us ignorants! Already took great knowledge from your dissertation about rpm feed and filter in aftermarket speedo. Now you add great knowledge with this scheme.. as you said, i am one of those that tried hardly on getting a useful value from that old graph!
I’m working towards making a new “troubleshooting guide” like the Vogel’s one including some of the information I gathered through my searches and trial-n-error, particularly on 4v models that are often so neglected.. would be great to add this precius info to it, if i have your blessing [emoji6]
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Thank you for you kind words LeMoeur. Yes, you can use the information in your guide. I believe in sharing information widely.
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H/T to RBM for the excel file!
And for any precision geeks like me, here's an equation (6th degree curve fit):
R = 9.057E-7T^6 - 0.0002T^5 + 0.0161T^4 - 0.6733T^3 + 15.23T^2 - 198.59T+1844.3
(T in Celsius)
or
T (C) = -4.278E-14R^5 + 2.503E-10R^4 - 5.627E-7R^3 + 0.0006R^2 - 0.3907R + 152.13
Blue is the curve fit for visual reference:

Screen Shot 2019-01-12 at 6.28.41 AM .jpg (52.09 kB . 768x419 - viewed 477 times)
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Brilliatn DavidATL!! I love the comparison of mathematical predictive versus measured empirical results.