Abstract
A high-precision Complementary Metal-Oxide-Semiconductor (CMOS) temperature sensor for (−5 °C, 120 °C) temperature range is designed and analyzed in this investigation. The proposed design is featured with a temperature range selection circuit so that the thermistor linear circuit automatically switches to a corresponding calibration loop in light of the temperature range besides the analysis of the calibration method. It resolves the problem that the temperature range of a single thermistor temperature sensor is too small. Notably, the output of the proposed design also attains a high linearity. The measurement results in a thermal chamber justifying that the output voltage is 1.96 V to 4.15 V, the maximum linearity error ≤1.4%, and the worst temperature error ≤1.1 °C in the temperature range of −5 °C to 120 °C.
Highlights
In recent years, consumer electronic products are often equipped with many sensors to detect the surrounding environmental conditions, e.g., voltage, current, temperature, etc., to facilitate a rapid and appropriate response
A thermistor linearity calibration circuit with switches is in charge of carrying out predictable linearization because the characteristic function of the thermistor is nonlinear
The linear correcting output, only attains high linearity when the sensed temperature is close to the selected center temperature
Summary
Consumer electronic products are often equipped with many sensors to detect the surrounding environmental conditions, e.g., voltage, current, temperature, etc., to facilitate a rapid and appropriate response. Industrial sensors utilized in those temperature sensing scenarios are classified into four categories: infrared, thermocouple, resistance thermometer, and thermistor. Proposed a linearization for thermistor-based correction resistor to correct the thermistor [10]. It has seriousscheme temperature error at the sensing in biomedical applications [11]. Bandyopadhyay et al proposed a linearization scheme thermistor-based sensing in biomedical. This circuit, has large output resistors with resistance variations. Kumar applications et al showed a block diagram of a neural network based error due to many resistors with resistance variations.
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