In this study, a novel signal processing algorithm and hardware processing circuit for the self-calibration of angular position sensors is proposed. To calibrate error components commonly found in angular position sensors, a parameter identification algorithm based on the least mean square error demodulation is developed. A processor to run programs and a coprocessor based on the above algorithm are used and designed to form a System-on-Chip, which can calibrate signals as well as implement parameter configuration and control algorithm applications. In order to verify the theoretical validity of the design, analysis and simulation verification of the scheme are carried out, and the maximum absolute error value in the algorithm simulation is reduced to 0.003 %. The circuit’s Register-Transfer Level simulation shows that the maximum absolute value of the angular error is reduced to 0.03%. Simulation results verify the calibration performance with and without quantization and rounding error, respectively. The entire system is prototyped on a Field Programmable Gate Array and tested on a Capacitive Angular Position Sensor. The proposed scheme can reduce the absolute value of angular error to 4.36%, compared to 7.68% from the experimental results of a different calibration scheme.
Design and Implementation of a System-on-Chip for Self-Calibration of an Angular Position Sensor