Model predictive control for synchronous reluctance motor drive

Aros, Nelson; Mora, Vanessa; Alarcon, Claudio

doi:10.1109/chilecon.2017.8229704

Cited by 7 publications

(5 citation statements)

References 12 publications

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“…Furthermore, the solution of ( 22) requires a combination of two active constraints and since there are six different combinations of two constraints, the maximum value of the counter in this step is N = 6. Finally, in the last step three active constraints have to be considered simultaneously and therefore there are four Start Solve (20) Constraints (19) satisfied?…”

Section: Solving Vsti-mpc Qp Problemmentioning

confidence: 99%

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Fixed Switching Frequency Direct Model Predictive Control of Synchronous Reluctance Machines Based on Stator Flux Gradients

Zagorščak,

Pravica,

Erceg

et al. 2024

IEEE Access

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This paper proposes a direct model predictive control method with a fixed switching frequency for stator flux control of a synchronous reluctance machine. Besides ensuring a fixed switching frequency, the main objective is to minimize the ripple of the stator flux. The objective function, which calculates the switching time instants within the switching period based on the stator flux gradients, is formulated as a standard constrained quadratic programming (QP) problem. Instead of using general-purpose QP solvers, an iterative algorithm based on the active-set method with Lagrange multipliers is proposed to solve this particular QP problem while reducing the computational complexity of the proposed algorithm and enabling successful implementation in real-time embedded systems. The proposed method has been successfully implemented on a laboratory model and the results are compared with a conventional indirect model predictive control. The experimental results show better performance in stator flux ripple and lower total stator current distortion factor for the proposed method compared to the conventional method. A 7.5 kW synchronous reluctance motor drive was used for the experimental validation of the proposed control method.INDEX TERMS Constrained quadratic programming problem, direct model predictive control, fixed switching frequency, harmonics, inverter, model predictive control with variable switching time instants, stator flux gradient, synchronous reluctance machine.

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Section: Solving Vsti-mpc Qp Problemmentioning

confidence: 99%

“…In addition, the lack of a modulator leads to a variable switching frequency, which results in a poor harmonic spectrum [19]. Nevertheless, FCS-MPC has been successfully applied to various power converter and drive applications, including the control of SynRM [20]- [24].…”

Section: Introductionmentioning

confidence: 99%

Fixed Switching Frequency Direct Model Predictive Control of Synchronous Reluctance Machines Based on Stator Flux Gradients

Zagorščak,

Pravica,

Erceg

et al. 2024

IEEE Access

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“…For several reasons, SynRMs are suitable in industrial and commercial applications, [1,[11][12][13][14] including (I) SynRMs are extremely efcient because of their simple rotor structure and lack of rotor windings, which reduces power losses in the motor. (II) Low Cost: Because SynRMs have a simple rotor structure and do not require rotor windings, the motor is less expensive.…”

Section: Need For Synchronous Reluctance Motormentioning

confidence: 99%

Comprehensive Overview of Modern Controllers for Synchronous Reluctance Motor

AngayarKanni,

Ramash Kumar,

Senthilnathan

2023

Journal of Electrical and Computer Engineering

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Synchronous reluctance motor drives (SynRMs) are the best promising machines utilized in modern industries and electric vehicles, according to the current study. Research on new SynRMs drive systems has increased as a result. This review article disseminates the most recent developments in these technologies’ design, modeling, and controlling. First, a simple comparison between the main motor technologies and SynRMs is made. To aid researchers in selecting the appropriate motor controller for their motor drive systems, the most common motor control approaches are examined and classed.

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“…Apart from model-free predictive motor control methods, model-based control (MPC) methods are gaining more attention in SynRM drive systems [152][153][154][155]. MPC considers the model of all of the system, including the inverter and the motor.…”

Section: Pc Of Synrmmentioning

confidence: 99%

A Review of Synchronous Reluctance Motor-Drive Advancements

et al. 2021

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Recent studies show that synchronous reluctance motors (SynRMs) present promising technologies. As a result, research on trending SynRMs drive systems has expanded. This work disseminates the recent developments of design, modeling, and more specifically, control of these motors. Firstly, a brief study of the dominant motor technologies compared to SynRMs is carried out. Secondly, the most prominent motor control methods are studied and classified, which can come in handy for researchers and industries to opt for a proper control method for motor drive systems. Finally, the control strategies for different speed regions of SynRM are studied and the transitions between trajectories are analyzed.

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Model predictive control for synchronous reluctance motor drive

Cited by 7 publications

References 12 publications

Fixed Switching Frequency Direct Model Predictive Control of Synchronous Reluctance Machines Based on Stator Flux Gradients

Fixed Switching Frequency Direct Model Predictive Control of Synchronous Reluctance Machines Based on Stator Flux Gradients

Comprehensive Overview of Modern Controllers for Synchronous Reluctance Motor

A Review of Synchronous Reluctance Motor-Drive Advancements

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