Velocity Estimation Method with Kalman Filtering for High-Speed Linear Induction Motor based on Voltage Characteristic Waves

The disturbance of velocity sensor data may cause serious problems when the motor is running at high velocity. To tackle this issue, a velocity estimation method for high-speed linear induction motors (HS-LIM) is proposed in this paper. Firstly, the state equations of voltage, current, and velocity are established in a synchronous coordinate system to obtain the relationship between the voltage and the velocity. Secondly, the voltages of each stator section are used to synthesize the voltage characteristic waves, which are used to calculate the velocity. Finally, two velocity estimation values are fused into one more precise velocity data based on the Kalman filtering recursion algorithm. The simulation experiment verifies that the voltage characteristic waves can accurately estimate the mover velocity of HS-LIM, and the Kalman fusion velocity gets better precise.

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Publication Details

Published
2024-11-03
DOI
https://doi.org/10.1109/iecon55916.2024.10905257
Primary Topic
Sensorless Control of Electric Motors
Type
article
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Velocity Estimation Method with Kalman Filtering for High-Speed Linear Induction Motor based on Voltage Characteristic Waves

Zixin Li, Xinyu Jiang, Fei Xu, Zhen Li et al.
Sensorless Control of Electric Motors
article

Velocity Estimation Method with Kalman Filtering for High-Speed Linear Induction Motor based on Voltage Characteristic Waves

Zixin Li, Xinyu Jiang, Fei Xu, Zhen Li, Yaohua Li, Liming Shi
article en

Abstract

The disturbance of velocity sensor data may cause serious problems when the motor is running at high velocity. To tackle this issue, a velocity estimation method for high-speed linear induction motors (HS-LIM) is proposed in this paper. Firstly, the state equations of voltage, current, and velocity are established in a synchronous coordinate system to obtain the relationship between the voltage and the velocity. Secondly, the voltages of each stator section are used to synthesize the voltage characteristic waves, which are used to calculate the velocity. Finally, two velocity estimation values are fused into one more precise velocity data based on the Kalman filtering recursion algorithm. The simulation experiment verifies that the voltage characteristic waves can accurately estimate the mover velocity of HS-LIM, and the Kalman fusion velocity gets better precise.

Chinese Academy of Sciences (CN)
Affordable and clean energy
Openalex Percentile: Top 74%
Sensorless Control of Electric Motors
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