NTC calibration and multiple temperature sensors

Introduction

Calibration of NTC sensors and different

NTC

Note that the temperature of the sensor rises when the current supplies through the resistor. The NTC is nonlinear; see below Calibration.

Negative Temperature Coefficient, NTCLE100E3101JB0 or similar (MF52B NTC Thermistor). The NTC is connected in series with a "shunt" resistor $R_{1}$, see Measurement of resistors: voltage divider. Usually $R_{1}=10kOhms$ is used. The total resistance of the circuit is $R=R_{1}+R_{NTC}$, which gives

${\begin{aligned}R_{NTC}={\frac {U_{\text{measured}}}{U-U_{\text{measured}}}}R_{1}\end{aligned}}$

or

${\begin{aligned}R_{NTC}={\frac {U-U_{\text{measured}}}{U_{\text{measured}}}}R_{1}\end{aligned}}$

depending on the circuit. So check the circuit.

Calibrating: Steinhart-Hart Equation

A nonlinear Steinhart-Hart equation is widely used

${\frac {1}{T}}=A+B\ln(Rt)+C(\ln(Rt))^{3}$

The parameters $A$, $B$ and $C$ can be obtained, if the resistance of three (3) temperatures is known.

Calibrating using known datapoints

Though the NTC sensor is nonlinear, locally it will be linear. Thus by using some known datapoints the temperature can be estimated.

Some known datapoints:

• boiling water 100 deg
• room temperature
• freezing point of water

Semiconductor Physics

Resistivity: $E=\rho J$ where $\rho$ is the density or number of charge carriers, $\rho =n/V$. Electrons are spin-1/2 particles and thus they obey Fermi-Dirac statistics.

The Fermi energy is the highest energy of the collection of electrons at T=0 Kelvin is the "primitive" approximation. Fermi-Dirac distribution $f_{f-d}(\epsilon )={\frac {1}{e^{\beta (\epsilon -\mu )}+1}}$ can be approximated (exercise: when) as Maxwell-Boltzmann exponential $e^{-\beta (\epsilon -\mu )}$