Algorithm of Linear Induction Motor Control for Low Normal Force of Magnetic Levitation Train Propulsion System

Seo, Hyunuk; Lim, Jaewon; Choe, Gyu-Ha; Choi, Jang-Young; Jeong, Jong Seob

doi:10.1109/tmag.2018.2842222

Cited by 22 publications

(10 citation statements)

References 5 publications

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“…22 shows eddy current distributio n fo r short shell. The calculated differential induced voltage is 110 µV in long shell aluminum model and it becomes 66 µV in short shell aluminum model due to the modified path for induced eddy currents [23]- [24]. Fig.…”

Section: Methodsmentioning

confidence: 91%

Rotational Eddy Current Speed Sensor

et al. 2019

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A novel eddy current speed sensor is develope d to measure rotational speed of conductive o bj e ct s. Th e s e nso r co ns ist s o f o n e e xcitation coil and two pick up coils around rotating cylinder or rod. The sensor does not use magnetic y o ke. Fo r t h e a n aly si s a n d e xperimental verification we used 30 mm diameter non-magnetic aluminum and also magnetic solid iron cylinders. The calculated and me asured speed range is until 1200 rpm. 2D analytical method is developed to calculate sensor performance. 2D finite element i s a l so use d for simulations to compare results with 2D analytical method. 3D finite elemen t a n a lys is i s requ ired t o t a k e i nt o a cco u nt significant 3D effects due to the air coils configuration. The experimental results are presented at different steady s t a te s pe eds. Th e calculations results are compared with measurements to validate theoretical models and sensor performance. The eddy current s pe ed se nsor shows high linearity even at low speeds. For ferromagnetic rods we suggest novel double-layer configura t io n: n on-m ag net ic conductive ring or shell on top of the iron rod minimizes the influence of the permeability changes. The main advantage o f t h e n o vel se nsor is that it has neither mechanical nor electrical contact to the rotating rod.

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Section: Methodsmentioning

confidence: 91%

Rotational Eddy Current Speed Sensor

et al. 2019

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“…Up to now, the main suspension control methods include PID control, fuzzy logic control, sliding mode control (SMC), neural network and Genetic Algorithm (NNGA), etc. These methods are mainly applied in the suspension control of maglev bearing [15][16][17], maglev train [18][19][20], maglev plane motor [21][22][23] and maglev ball [24].…”

Section: Introductionmentioning

confidence: 99%

Research on suspension control strategy based on finite control set model predictive control with state feedback control‐PID for maglev yaw system of wind turbine

Wang

Cai

Chu

et al. 2021

IET Electric Power Applications

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The maglev yaw system (MYS) of wind turbine adopts the maglev-driving technique instead of the traditional gear-driving technique, so it has the advantages of short downtime and low cost of operation and maintenance. However, it is vulnerable to the nonlinear time-varying disturbance caused by the random change of wind speed and direction. This paper proposes a dual-loop suspension control strategy based on the finite control set model predictive control (FCS-MPC) with state feedback control (SFC) to improve the dynamic response and anti-disturbance ability of the MYS. First, the mathematical models of the MYS are built. Second, in order to realise the stable suspension control, the outer loop controller for suspension air gap tracking is designed by combining SFC with proportional integral differential, and the inner loop controller for maglev current tracking is designed by adopting FCS-MPC with delay compensation. Finally, the simulation and experimental results show that the proposed control strategy has better robustness and dynamic response property comparing with the existing control strategies, and the maglev system of MYS can realise smooth and reliable operation. The proposed suspension control strategy is substantiated to be effective and feasible. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Apart from the permanent magnet machines (PMM), induction motor (IM) is one of the most commonly used propulsion machines in the electrical propulsion applications [1][2][3]. Comparatively speaking, although IM has the advantages of low cost, robust structure, high reliability and demagnetization-free risks, the energy conversion efficiency of an IM-based drive system is lower than a PMM-based system [4].…”

Section: Introductionmentioning

confidence: 99%

Low-Switching-Loss Finite Control Set Model Predictive Current Control for IMs Considering Rotor-Related Inductance Mismatch

Tan

et al. 2020

IEEE Access

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This paper develops a high-performance finite control set model predictive current control (FCS-MPCC) method for induction motors (IM) to ensure the system control performance over the lowswitching-frequency (LSF) range, where the switching loss is low. The new controller is based on tripartite calculations in each control period and sliding mode (SM) rotor-related inductance observer. In detail, firstly, to solve the problem that the control performance of the traditional FCS-MPCC methods is low when they are used at low frequencies, tripartite calculations are employed in each control period to improve the prediction accuracy. By dividing one control period into three equal parts and executing the prediction algorithm in each subsection, the current estimation errors become lower compared to the conventional single-step Euler-discretization controller. Then, considering that the performance of an FCS-MPCC controller highly relies on the machine parameter values, but it is hard to directly obtain the accurate rotor-related inductances (mutual inductance and rotor inductance), this paper uses an online parameter observer based on the sliding mode (SM) principle to diagnose them in real time. It needs to be mentioned that when discussing the stability of the sigmoid-function-based SM observer, a new technique called estimation-error-limitation is initially adopted in this paper to simplify the analysis process. Finally, the proposed algorithms are verified by simulation, which is conducted on a three-phase IM at LSF situations. INDEX TERMS Induction motor, finite control set model predictive control, sliding mode observer, parameter mismatch, low switching frequency.

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Algorithm of Linear Induction Motor Control for Low Normal Force of Magnetic Levitation Train Propulsion System

Cited by 22 publications

References 5 publications

Rotational Eddy Current Speed Sensor

Rotational Eddy Current Speed Sensor

Research on suspension control strategy based on finite control set model predictive control with state feedback control‐PID for maglev yaw system of wind turbine

Low-Switching-Loss Finite Control Set Model Predictive Current Control for IMs Considering Rotor-Related Inductance Mismatch

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