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Nonlinearity Analysis and Parameters Optimization for an Inductive Angle Sensor

机译:感应角传感器的非线性分析和参数优化

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摘要

Using the finite element method (FEM) and particle swarm optimization (PSO), a nonlinearity analysis based on parameter optimization is proposed to design an inductive angle sensor. Due to the structure complexity of the sensor, understanding the influences of structure parameters on the nonlinearity errors is a critical step in designing an effective sensor. Key parameters are selected for the design based on the parameters' effects on the nonlinearity errors. The finite element method and particle swarm optimization are combined for the sensor design to get the minimal nonlinearity error. In the simulation, the nonlinearity error of the optimized sensor is 0.053% in the angle range from −60° to 60°. A prototype sensor is manufactured and measured experimentally, and the experimental nonlinearity error is 0.081% in the angle range from −60° to 60°.
机译:利用有限元方法和粒子群优化算法,提出了一种基于参数优化的非线性分析设计电感式角度传感器。由于传感器的结构复杂性,了解结构参数对非线性误差的影响是设计有效传感器的关键步骤。根据参数对非线性误差的影响,选择关键参数进行设计。结合有限元方法和粒子群算法进行传感器设计,得到最小的非线性误差。在仿真中,在-60°至60°的角度范围内,优化传感器的非线性误差为0.053%。通过实验制造和测量原型传感器,并且在-60°至60°的角度范围内,实验非线性误差为0.081%。

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