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A Novel Two-Dimensional Model for Micro Thermal Expansion-based Gyroscopes towards Parametric Analysis and Efficient Optimization

机译:基于微热膨胀的陀螺仪参数分析和高效优化的新型二维模型

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We report, for the first time, a novel two-dimensional (2D) model for the micro thermal expansion-based gyroscope (μTEG) to predict the sensor's performance, which has been validated by the experimental results. Scaling analysis on the sensor's performance characteristics by this model enables the optimization of μTEG design, including the normalized distances between the heater and temperature detectors in two directions, the thin film thickness, the heater width, the cavity depth and the heater temperature, to achieve extremely high sensitivity (11.78 mV/°/s) and low power consumption (12.8mW). According to the analysis by 2D model, the sensitivity of the optimized μTEGs by using the working gases (SF6 and C4F8) with larger density, better than the best published μTEG (1.287 mV/°/s) by one order of magnitude, can reach the level of the commercial product (>6 mV/°/s). In particular, our new 2D model can significantly save the CPU time in comparison with the conventional CFD model (1.92s versus 5h) to realize the efficient systematical optimization of the key design parameters. Thus, the proposed 2D model can be a useful tool for μTEGs' system-level designs for industrial IoT applications.
机译:我们首次报告一种用于微热膨胀的陀螺仪(μTEG)的新型二维(2D)模型,以预测传感器的性能,这已经通过实验结果验证。通过该模型对传感器的性能特性进行缩放分析,可以优化μTEG设计,包括在两个方向上的加热器和温度探测器之间的归一化距离,薄膜厚度,加热器宽度,腔深度和加热器温度之间实现极高的灵敏度(11.78 mV /°/°/°/°/°)和低功耗(12.8mW)。根据2D模型的分析,优化的μTEGS通过使用更大的密度的工作气体(SF6和C4F8)的灵敏度,优于最佳发布的μTEG(1.287mV / s),可以达到一个数量级商业产品的水平(> 6 mV /°/ s)。特别是,与传统的CFD模型(1.92S与5H)相比,我们的新2D模型可以显着保存CPU时间,以实现关键设计参数的有效系统优化。因此,所提出的2D模型可以是用于工业IOT应用的μTEGS系统级设计的有用工具。

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