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| Simon:
I am looking at this datasheet: https://www.te.com/commerce/DocumentDelivery/DDEController?Action=showdoc&DocId=Data+Sheet%7FGA10K3MCD1%7FA%7Fpdf%7FEnglish%7FENG_DS_GA10K3MCD1_A.pdf%7FGA10K3MCD1 the time constant is 200ms but what exactly ho they mean by time constant? is this the time to fully match the new temperature or is it our old friend tau from RC circuits of 66% ? |
| floobydust:
I've always seen it defined as the thermal time constant, to reach 63.2% of the temperature difference. You can cheat this spec, depending on the fluid used (water vs oil) and if there is a stirrer. Tiny bead thermistors are around 10 seconds at best, so this 0.2 sec response time is very fast, almost too fast... "Thermal Time Constant simply put, under zero conditions, is the time it takes a thermistor temperature sensor to change 63.2% of the total difference between the initial and the final body temperature; when subjected to a step function change in temperature. In simple terms, it represents in time, how long it takes a thermistor to recover up to 50% of its initial resistance." It might be a guillotine tester they use? https://www.ametherm.com/blog/thermistors/thermal-time-constant-ntc-thermistors |
| Simon:
So theoretically I don't have to wait 5t, knowing what the last reading was allows me to make sense of the next reading. If I take a reading 0.2s later I know that this is 63% of what the temperature actually is but that assumes that the last reading had stabilized after 5t so I would still need to wait that time or this gets really complicated as I would need a history of readings and use an algorithm to model the response of the thermistor say over the last 10t period. |
| floobydust:
Ideally, the sensor response time is faster than the system (time constant) for stability in PID control etc. if that is what you are doing. If the system changes temperature faster than that (sensor), feedback control gets sloppy as you are always lagging, always behind, and need 1 second at least to get accuracy. You can model the sensor's thermal characteristics (time constant) and attempt to predict (add lag compensation) but it never works well for me. The problem is the system gain (that a model is built upon) might change and make closed-loop control go unstable, if you are modeling it. A classic example is a change in airflow past the sensor, that controls a heater. Higher airflow decreases thermistor response time (due to better heat transfer to it) and usually system gain goes down due to the heater being less effective with higher mass flow. I might be wrong here but I have made a few oscillators by accident. |
| Ice-Tea:
I image that if you would measure every 0.2s and use the 63% value that would be absolute worst case/largest possible change (for when you just applied a fresh step). Not a bad thing to work with, not sure if keeping a ledger and releasing further algorithms would bring much to the table? |
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