Nonlinear Modelling, Flatness-Based Current Control, and Torque Ripple Compensation for Interior Permanent Magnet Synchronous Machines

Veeser, Felix; Braun, Tristan; Kiltz, Lothar; Reuter, Johannes

doi:10.3390/en14061590

Cited by 7 publications

(5 citation statements)

References 28 publications

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“…The property of flatness can be used to design control algorithms. A dynamic system is flat if and only if the state and control variables of the system can be written as functions of the flat output and its derivatives [38,39]. Mathematically, a system defined by: .…”

Section: Flatness-based Controlmentioning

confidence: 99%

“…Mathematically, a system defined by: . x = f (x, u) (x R n and u R m are state and the input vector, respectively) is considered to be differentially flat if an output y R m can be found in the form of (18) such that the state and the input vectors be written like Equation (19) [38,39]. Generally, the control structure consists of a feedforward and a feedback part.…”

Section: Flatness-based Controlmentioning

confidence: 99%

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Comparative Study between Flatness-Based and Field-Oriented Control Methods of a Grid-Connected Wind Energy Conversion System

2022

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Wind energy is an alternative to meet the growing energy demand. Control of wind turbines should help the reliability and stable operation of the power grid. Furthermore, they should respect the technical requirements according to the grid codes to inject the wind energy into the grid. In this paper, a well-known field-oriented control (FOC) method and a new control method based on the flatness properties (FBC) are presented and compared. These control methods are applied to a wind energy conversion system (WECS), which connects a variable-speed wind turbine (WT) based on a permanent magnet synchronous generator (PMSG) to the grid via a back-to-back converter. The main aim of both control methods is to extract the maximum power from the wind. For this purpose, the mathematical model of each subsystem, i.e., WT, PMSG, and electrical grid, is presented. To evaluate and to compare the dynamic behavior of the high-power wind energy conversion system, it is modeled and the control strategies are developed using SimPowerSystems Toolbox in MATLAB. The simulation results obtained in the time domain show that the FBC performs better at managing the energy in the studied system. Indeed, the proposed FBC is a high bandwidth control method with only one closed-loop control, which leads to a high dynamic performance. Therefore, that strategy can be used to provide ancillary services such as frequency control and spinning reserves according to the grid codes.

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Section: Flatness-based Controlmentioning

confidence: 99%

Section: Flatness-based Controlmentioning

confidence: 99%

Comparative Study between Flatness-Based and Field-Oriented Control Methods of a Grid-Connected Wind Energy Conversion System

2022

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“…Note that the stability and response of the differential flatness-based control are easy to set compared to the traditional PI controller. By defining and selecting the governing damping and natural frequency [21,22], as shown in Figure 6, the controller parameters of current and speed loop control may be calculated by Equations (29), (30), ( 35) and (36).…”

Section: Differential Flatness Control Of Speed Control Loop Developmentmentioning

confidence: 99%

Design, Modeling, and Differential Flatness Based Control of Permanent Magnet-Assisted Synchronous Reluctance Motor for e-Vehicle Applications

et al. 2021

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This paper presents the utilization of differential flatness techniques from nonlinear control theory to permanent magnet assisted (PMa) synchronous reluctance motor (SynRM). The significant advantage of the proposed control approach is the potentiality to establish the behavior of the state variable system during the steady-state and transients operations as well. The mathematical models of PMa-SynRM are initially proved by the nonlinear case to show the flatness property. Then, the intelligent proportional-integral (iPI) is utilized as a control law to deal with some inevitable modeling errors and uncertainties for the torque and speed of the motor. Finally, a MicroLab Box dSPACE has been employed to implement the proposed control scheme. A small-scale test bench 1-KW relying on the PMa-SynRM has been designed and developed in the laboratory to approve the proposed control algorithm. The experimental results reflect that the proposed control effectively performs high performance during dynamic operating conditions for the inner torque loop control and outer speed loop control of the motor drive compared to the traditional PI control.

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“…Several methods may be used to create numerical data representing the surfaces Ψ d (i d , θ e ), Ψ q (i q , θ e ): starting from detailed 3D modeling of the motor magnetic field, ending with observers of a different type, for example, as described in [27,28,32,33]. All these methods produce data degraded (to a certain degree) by noise or outliers.…”

Section: Motor Flux Distribution Modelingmentioning

confidence: 99%

Approximation of Permanent Magnet Motor Flux Distribution by Partially Informed Neural Networks

Jastrzębski

Kabziński

2021

Energies

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New results in the area of neural network modeling applied in electric drive automation are presented. Reliable models of permanent magnet motor flux as a function of current and rotor position are particularly useful in control synthesis — allowing one to minimize the losses, analyze motor performance (torque ripples etc.) and to identify motor parameters—and may be used in the control loop to compensate flux and torque variations. The effectiveness of extreme learning machine (ELM) neural networks used for approximation of permanent magnet motor flux distribution is evaluated. Two original network modifications, using preliminary information about the modeled relationship, are introduced. It is demonstrated that the proposed networks preserve all appealing features of a standard ELM (such as the universal approximation property and extremely short learning time), but also decrease the number of parameters and deal with numerical problems typical for ELMs. It is demonstrated that the proposed modified ELMs are suitable for modeling motor flux versus position and current, especially for interior permanent magnet motors. The modeling methodology is presented. It is shown that the proposed approach produces more accurate models and provides greater robustness against learning data noise. The execution times obtained experimentally from well-known DSP boards are short enough to enable application of derived models in modern algorithms of electric drive control.

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Nonlinear Modelling, Flatness-Based Current Control, and Torque Ripple Compensation for Interior Permanent Magnet Synchronous Machines

Cited by 7 publications

References 28 publications

Comparative Study between Flatness-Based and Field-Oriented Control Methods of a Grid-Connected Wind Energy Conversion System

Comparative Study between Flatness-Based and Field-Oriented Control Methods of a Grid-Connected Wind Energy Conversion System

Design, Modeling, and Differential Flatness Based Control of Permanent Magnet-Assisted Synchronous Reluctance Motor for e-Vehicle Applications

Approximation of Permanent Magnet Motor Flux Distribution by Partially Informed Neural Networks

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