Capacitive MEMS accelerometers have a high thermal sensitivity that drifts the output when subjected to changes in temperature. To improve its performance in applications with thermal variations, it is necessary to compensate for these effects. These drifts can be compensated by a lightweight algorithm by knowing the characteristic thermal parameters of an accelerometer (Temperature Drift of Bias and Temperature Drift of Scale Factor). These parameters vary in each accelerometer and axis, making an individual calibration necessary.
In this work, a simple calibration method is proposed that allows the characteristic parameters of the three axes to be obtained simultaneously through a test of less than three hours. This method is based on the study of two specific orientations, each at two temperatures. By means of the suitable selection of the orientations and the temperature points, the data obtained can be extrapolated to the entire working range of the accelerometer. Only a mechanical anchor and a heat source are required to perform the calibration. This technique can be scaled to calibrate multiple accelerometers simultaneously. A lightweight algorithm is used to analyze the test data and obtain the characteristic parameters. This algorithm stores only the most relevant data, reducing memory and computing power requirements. This way it can be run on real-time on a low-cost microcontroller during testing to obtain compensation parameters immediately. This method is aimed at mass factory calibration, where individual calibration with traditional methods may not be an adequate option. The proposed method has been compared with a traditional calibration using a six-sided orthogonal die and a thermal camera. The average difference between the compensations according to both techniques is 0.64mg, calculated on an acceleration of 1G and a thermal variation of 20ºC; the maximum deviation being 1.1mg.
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