Thermal Compensation System for Silicon Piezoresistive Pressure Sensors Based on Surface Fitting and Wild Horse Algorithm

Silicon piezoresistive pressure sensors suffer from temperature effects significantly. The thermal compensation system based on surface fitting and wild horse algorithm is proposed to overcome the nonlinearity. The polynomial coefficients in surface fitting are optimized using the wild horse algorithm. A platinum resistance thermometer (PRT) integrated in the silicon layer of the pressure sensor is employed to capture the local temperature variations. The extracted pressure and temperature changes are fed to the compensation algorithm via digital circuits. The results of calibration experiments show that the PRT has a maximum absolute error of
$1.24 \Omega $
, and the standard deviation of the output signal and sensitivity among several pressure sensors in the same batch is 4.5 mV and 0.07 mV/MPa, respectively, ensuring the accuracy for PRT and mass production repeatability for pressure sensors. The comprehensive performance of the compensation system was validated under 0–40 MPa and 0 °C–80 °C. The linearity of the sensor decreases from 8.1218%FS to 0.0629%FS on the calibration data. When the pressure and temperature change simultaneously, the linearity remains at 0.1112%FS. Hence, the system considerably reduces the temperature impact on silicon piezoresistive pressure sensors and exhibits strong integration and generalization.