Design and parameter optimization of contactless vertical inductive angle sensor. (November 2019)

• Record Type: Journal Article
• Authors: Li, Zhipeng; Zhang, Chao; Shi, Songzhuo; Meng, Xu; Wang, Bonan
• Is Part Of: Vacuum. Volume 169(2019)
• Publication Date: 2019-11
• Subjects: Contactless vertical inductive angle sensor -- Particle swarm optimization -- Measurement accuracy error; Vacuum -- Periodicals; 621.55
• DOI: 10.1016/j.vacuum.2019.108865
• Languages: English
• ISSNs: 0042-207X

Abstract

Abstract: Contactless inductive angle sensors are widely used in the industrial field. To date, the contactless inductive angle sensor is a planar structure, and its physical structure limits the number of turns of the excitation coil, resulting in a small eddy current on the rotor, which increases the measurement accuracy error of the sensor. Therefore, in view of reducing the sensor volume and reducing the sensor measurement accuracy error, a contactless vertical inductive angle sensor is designed. Through modeling and simulation, when the position of the rotor and stator changes, the induced voltage in the receiving coil changes sinusoidally. The structural parameters that have the greatest influence on the measurement accuracy error of the sensor are obtained by simulation. Because of the complex electromagnetic structure of the sensor, the linearly-decrease inertia weight particle swarm optimization (LIWPSO) and finite element method (FEM) are used to optimize the sensor measurement accuracy error. In the simulation, the measurement accuracy error of the optimized sensor is 0.778% in the angle range of 0°–40°. The sensor is manufactured and tested for the optimized parameters, and the observed experimental measurement accuracy error is 0.981% in the angle range of 0°–40°. Highlights: The sensor is a novel vertical structure design with smaller volume, larger eddy current and higher measurement accuracy. The three-dimensional model of the sensor is established, and the induction voltage of three receiving coils is simulated. Several key parameters of the sensor were selected. The optimized measurement accuracy error was 0.981%. LIWPSO and FEM are used to optimize the sensor measurement accuracy error.