Iterative-learning-based torque-ripple compensation in a transverse flux motor

Rupar, U.; Lahajnar, Franci; Zajec, Peter

doi:10.1049/iet-cta.2011.0051

Cited by 8 publications

(6 citation statements)

References 15 publications

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“…The output variable is ω(t), the control variable is T(t), and the initial conditions are θ(0) = 0 and ω(0) = 0. A previous study [27] noted that the influence of the torque ripple above the 6th order on the rotation speed can be neglected; thus, we focus our analysis on the 1st, 2nd, and 6th harmonic torque of the torque ripple. The load torque can be expressed as…”

Section: Simulation Results and Analysismentioning

confidence: 99%

Accelerated Iterative Learning Control of Speed Ripple Suppression for a Seeker Servo Motor

Lin

2018

Algorithms

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To suppress the speed ripple of a permanent magnet synchronous motor in a seeker servo system, we propose an accelerated iterative learning control with an adjustable learning interval. First, according to the error of current iterative learning for the system, we determine the next iterative learning interval and conduct real-time correction on the learning gain. For the learning interval, as the number of iterations increases, the actual interval that needs correction constantly shortens, accelerating the convergence speed. Second, we analyze the specific structure of the controller while applying reasonable assumptions pertaining to its condition. Using the λ-norm, we analyze and apply our mathematical knowledge to obtain a strict mathematical proof on the P-type iterative learning control and obtain the condition of convergence for the controller. Finally, we apply the proposed method for periodic ripple inhibition of the torque rotation speed of the permanent magnet synchronous motor and establish the system model; we use the periodic load torque to simulate the ripple torque of the synchronous motor. The simulation and experimental results indicate the effectiveness of the method.

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Section: Simulation Results and Analysismentioning

confidence: 99%

Accelerated Iterative Learning Control of Speed Ripple Suppression for a Seeker Servo Motor

Lin

2018

Algorithms

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“…The magnetic flux in the windings is obtained by integrating the difference between the input voltage and the voltage drops across winding resistor. The electric currents in the stator windings are determined by the interpolation function I = f 3 (φ, θ) using Equation (6). The electromagnetic torques produced by each stator winding are obtained by the nonlinear interpolation function Γ = f 2 (I, θ) according to Equation (6) and subsequently summed to give the total torque produced by the machine.…”

Section: Dspm Modelingmentioning

confidence: 99%

“…These types of speed adaptation system have several disadvantages; for example, they are bulky, costly, and require regular maintenance. To overcome these problems, new structures of variable reluctance machines, operating at low speeds, called slow machines or direct attack machines are proposed [1][2][3][4][5][6][7][8][9][10]. One of these structures, named Doubly Salient Permanent Magnet Machine (DSPM), a variable reluctance machine, with a large number of rotor and stator teeth excited by non-rotating permanent magnets housed in the stator yoke, attracts more and more attention [2,9,13].…”

Section: Introductionmentioning

confidence: 99%

Electromagnetic Torque Ripple Minimization of Slotted Doubly-Salient-Permanent-Magnet Generator for Wind Turbine Applications

Bekhouche¹,

Saou²,

Guerroudj³

et al. 2019

PIER M

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The aim of this work is to reduce the torque ripple of a low-speed/high-torque Doubly Salient Permanent Magnet (DSPM) generator for wind turbine applications. To do this, a combined design and control-based approaches are set up to improve the overall machine performance. The design-based approach helps to develop a form of small stator/rotor teeth combination, focusing on the shapes and dimensions of the teeth that will minimize torque ripple. On the other hand, in the second approach, a control technique is designed. It employs indirect torque control (Torque Sharing Function: TSF), including a PI-controller with gains adjusted continuously for regulating the reference current. The obtained results show that by combining these two approaches, the ripple rate of the electromagnetic torque for the studied DSPM is reduced to a minimum when the teeth shapes are trapezoidal in both the stator and rotor, and the command approach also allows an improvement in the total torque shape, such that the ripple rate decreases by about 96%.

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“…However, because of the offline-based calculation, this approach is very sensitive to parameters and variations during the practical operation. In [24], an iterative learning scheme for reducing the torque ripple of direct-drive transverse flux motor was presented by Rupar et al Nevertheless, this method is mainly applicable to reduce the periodic torque ripple and its effectiveness depends heavily on the accuracy of parameters that obtained by experiments. In [25], a cascade of two superordinate state controllers was adopted to control the force of transverse flux linear motor and in [26], an approach based on the active disturbance rejection control and harmonic spectrum analysis was proposed for suppressing force ripples.…”

Section: Introductionmentioning

confidence: 99%

Torque Ripple Suppression of Building-Block Transverse Flux Permanent Magnet Motor by Current Compensation and Variable Parameter Control Based on Real-Time Inductance

2020

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Building-block transverse flux permanent magnet motor (B-TFPMM) has the advantage of electromagnetic decoupling and high torque density, but it has the strong nonlinearity and the large torque ripple. To solve the problem, the nonlinear characteristics of B-TFPMM stator back electromotive force (EMF) e pm , winding inductance L and single-phase torque T sp are analyzed firstly, and the nonlinear dynamic models involving e pm , L, T sp , stator current and rotor position are established by three-dimensional finite element method (3DFEM). Secondly, apply the square wave current and sinusoidal current to stator windings respectively, and the result shows that using sinusoidal current would acquire smaller torque ripple rate when the load torque is more than 30 N • m. Furthermore, the variation rule of five-phase current utilization is obtained and the maximum current utilization model is established. Based on these, the current compensation method is developed and then the torque ripple rate could be reduced by 10% approximately. After that, combining with 7 nonlinear dynamic models of B-TFPMM, a closed-loop control system based on the compensation method and variable parameter PID algorithm is built. The ratio of the real-time winding inductance to sampling period is chosen as the proportional coefficient of controller. The results indicate that compared with the control mode which combining uncompensated current and traditional constant parameter PID algorithm, the control mode of using compensated current and variable parameter PID algorithm would reduce the torque ripple rate by 57% to 65% and increase the average torque by 13% to 33% in the meantime. INDEX TERMS Building-block transverse flux permanent magnet motor, torque ripple suppression, current compensation, nonlinear dynamic model, variable parameter control.

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Iterative-learning-based torque-ripple compensation in a transverse flux motor

Cited by 8 publications

References 15 publications

Accelerated Iterative Learning Control of Speed Ripple Suppression for a Seeker Servo Motor

Accelerated Iterative Learning Control of Speed Ripple Suppression for a Seeker Servo Motor

Electromagnetic Torque Ripple Minimization of Slotted Doubly-Salient-Permanent-Magnet Generator for Wind Turbine Applications

Torque Ripple Suppression of Building-Block Transverse Flux Permanent Magnet Motor by Current Compensation and Variable Parameter Control Based on Real-Time Inductance

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