Why is a thermistor very sensitive to temperature changes at low ranges and how does this affect linearization?

Why is a thermistor very sensitive to temperature changes at low ranges and how does this affect linearization?

• A. The resistance change is small and linear; linearization is typically not required.
• B. The resistance change is large and nonlinear; linearization often required around operating range with polynomial or look-up.
• C. The thermistor is not affected by temperature.
• D. It is solely affected by humidity.

Answer: (B)

Thermistors have a highly nonlinear resistance versus temperature curve, and at low temperatures the slope is steep, so small temperature changes produce large changes in resistance. That makes the sensor extremely sensitive there, but the output is not proportional to temperature, so using it directly gives a nonlinear response. To use the signal in a system that assumes a linear relationship, linearization is often applied around the operating range. This can be done with a polynomial approximation or a look-up table (often using the Steinhart-Hart model) to map the measured resistance to temperature and then present a linearized output. By choosing the linearization range carefully, you minimize error across the intended span. In short, the strong, nonlinear change in resistance at low temperatures necessitates linearization to achieve a usable linear temperature response. The other statements are not correct because thermistors do exhibit large, nonlinear resistance changes, and humidity does not govern their resistance in typical temperature sensing.

Thermistors have a highly nonlinear resistance versus temperature curve, and at low temperatures the slope is steep, so small temperature changes produce large changes in resistance. That makes the sensor extremely sensitive there, but the output is not proportional to temperature, so using it directly gives a nonlinear response. To use the signal in a system that assumes a linear relationship, linearization is often applied around the operating range. This can be done with a polynomial approximation or a look-up table (often using the Steinhart-Hart model) to map the measured resistance to temperature and then present a linearized output. By choosing the linearization range carefully, you minimize error across the intended span. In short, the strong, nonlinear change in resistance at low temperatures necessitates linearization to achieve a usable linear temperature response. The other statements are not correct because thermistors do exhibit large, nonlinear resistance changes, and humidity does not govern their resistance in typical temperature sensing.