Temperature Hysteresis Calibration Method of MEMS Accelerometer.

Area of Science:

• Sensor Technology
• Instrumentation
• Materials Science

Background:

• Micro-electromechanical system (MEMS) sensors are crucial for navigation due to their size and cost.
• Temperature hysteresis, caused by internal gradients, degrades MEMS sensor performance.
• Existing solutions often require hardware modifications or are insufficient.

Purpose of the Study:

• To develop a hardware-independent calibration method for correcting temperature hysteresis in MEMS sensors.
• To enhance the accuracy and reliability of MEMS sensors in dynamic thermal conditions.
• To provide a practical solution for improving navigation system performance.

Main Methods:

• A mathematical calibration model was derived by analyzing the relationship between external temperature change rate and hysteresis errors.
• The method was experimentally validated on MEMS accelerometers.
• Performance was assessed by evaluating hysteresis reduction, bias repeatability, scale factor repeatability, nonlinearity, and Allan variance.

Main Results:

• The proposed calibration method achieved up to a 63% reduction in MEMS accelerometer hysteresis errors.
• Bias and scale factor repeatability showed good performance post-calibration.
• Minor trade-offs in noise characteristics were observed, but overall hysteresis was significantly improved.

Conclusions:

• The developed calibration method effectively corrects temperature hysteresis in MEMS sensors without additional hardware.
• This approach offers a practical and efficient way to enhance MEMS sensor accuracy in variable temperatures.
• The findings contribute to more reliable navigation systems utilizing MEMS technology.