Active and Reactive Power Sharing Between Three-Phase Winding Sets of a Multiphase Induction Machine

Subotić, Ivan; Dordevic, Obrad; Gomm, J.B.; Levi, E.

doi:10.1109/tec.2019.2898545

Cited by 21 publications

(11 citation statements)

References 21 publications

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“…The currents of the stator phases are always out of phase by 120°. The modulation of the envelope of the stator current after the breaks of the bars is also noted, the increase of the amplitude of proportional to the number of broken bars which appears in the figures (1)(2). With regard to the simulation of short-circuit faults between coils in an induction machine, in a first case, we presented the shapes of the stator currents in the case operation and with short-circuit-type faults between 40 turns (25%), and the second case we apply short circuit faults between 20 turns (12.5%).…”

Section: Withmentioning

confidence: 74%

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Induction Machine Faults Detection and Localization by Neural Networks Methods

Chouidira¹,

Khodja²,

Chakroune³

2019

RIA

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The objective of this study is to present artificial intelligence (AI) technique for detection and localization of fault in induction machine fault, through a multi-winding model for the simulation of four adjacent broken bars and three-phase model for the simulation of shortcircuit between turns. In this work, it was found that the application of artificial neural networks (ANN) based on Root mean square values (RMS) plays a big role for fault detection and localization. The simulation and obtained results indicate that ANN is able to detect the faulty with high accuracy. Keywords:Induction machine, faults detection and localization, broken bars, artificial neural network (ANN), root mean square (RMS), multi winding, three-phase model = [V] − [R][I](1)

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Section: Withmentioning

confidence: 74%

“…Thus, no control system is safe from failure. Therefore, it is very important to pre-detect the various defects that may occur in these systems through the use of traditional or modern methods that allow us to monitor and control by taking preventive action to detect these incidents sudden accidents on the machine [1].…”

Section: Introductionmentioning

confidence: 99%

Induction Machine Faults Detection and Localization by Neural Networks Methods

Chouidira¹,

Khodja²,

Chakroune³

2019

RIA

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“…VD1 (34,43) VD2 (42,38) VD3 (46,10) VD4 (14,44) VD5 (12,30) VD6 (28,13) VD7 (29,20) VD8 (21,25) VD9 (17,53) VD10 (49,19) VD11 (51,33) VD12 ( The bi-subspace PCC strategy based on virtual vectors (BSVV-PCC) presented in Reference [120] aims to provide an accurate current control in both d-q and x -y subspaces. This strategy uses two FCS-MPC stages, where one regulates the d-q current components and the other regulates the x -y current components.…”

Section: Bi-subspace Predictive Current Control Based On Virtual Vectorsmentioning

confidence: 99%

“…Multimotor drives proposed in the 2000s is another application that takes advantage of the additional degrees of freedom, where a single n-phase VSI is able to drive independently up to (n − 1) /2 machines if n is odd or up to (n − 2) /2 machines if n is even, either connected in series or in parallel [10,11]. More recently, the additional degrees of freedom of multiphase machines are being used to provide: balancing of the dc-link capacitors of series-connected VSIs on the machine side [12]; unequal power sharing [13,14]; full-load test methods [15,16]; integrated battery charging for electric vehicles [17][18][19]; dynamic braking for non-regenerative electric drives [20,21];…”

Section: Introductionmentioning

confidence: 99%

Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview

2019

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Recently, the control of multiphase electric drives has been a hot research topic due to the advantages of multiphase machines, namely the reduced phase ratings, improved fault tolerance and lesser torque harmonics. Finite control set model predictive control (FCS-MPC) is one of the most promising high performance control strategies due to its good dynamic behaviour and flexibility in the definition of control objectives. Although several FCS-MPC strategies have already been proposed for multiphase drives, a comparative study that assembles all these strategies in a single reference is still missing. Hence, this paper aims to provide an overview and a critical comparison of all available FCS-MPC techniques for electric drives based on six-phase machines, focusing mainly on predictive current control (PCC) and predictive torque control (PTC) strategies. The performance of an asymmetrical six-phase permanent magnet synchronous machine is compared side-by-side for a total of thirteen PCC and five PTC strategies, with the aid of simulation and experimental results. Finally, in order to determine the best and the worst performing control strategies, each strategy is evaluated according to distinct features, such as ease of implementation, minimization of current harmonics, tuning requirements, computational burden, among others.

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“…1 for a triple three-phase drive [13]. This control possibility, also known under the name of power-sharing capability of multiphase drives, has been analyzed in-depth in recent research studies [14]- [16].…”

Section: Introductionmentioning

confidence: 99%

Power-Sharing Control in Bearingless Multi-Sector and Multi-Three-Phase Permanent Magnet Machines

Sala

Valente

Nardo

et al. 2021

IEEE Trans. Ind. Electron.

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This paper deals with the power-sharing control of bearingless multi-sector and multi-three-phase permanent magnet machines. The proposed control strategy allows to distribute the power flows among the three-phase inverters supplying the machine during bearingless operation of the drive. The control technique is based on the extension of the vector space decomposition modeling approach. The components producing the electromagnetic torque, i.e. the q-axis currents, are controlled independently from the d-axis ones, also with the aim of managing the power flows among the three-phase systems. Conversely, the d-axis currents are exploited for the generation of the radial forces needed to levitate the rotor, while considering the compensation of the forces caused by the q-axis currents in case of unbalanced power sharing strategy. The validity of the proposed method is confirmed by simulations and experimental tests on a prototyped bearingless multisector permanent magnet synchronous machine. The proposed approach is a contribution to the development of advanced control systems employing multiphase drives in the field of bearingless and multiport applications. Index Terms-Bearingless machines, force control, machine vector control, magnetic levitation, multiphase drives, permanent magnet machines, power-sharing, variable speed drives. NOMENCLATURE Pole pair number. Subscript used to identify the sub-windings under the same P th sector (= 1,2, … ,). Number of three-phase star connected windings located under each pole pair (sector). T Subscript used to distinguish the sub-windings under the same P th sector (= 1,2, … ,). ̅ , Current space vector of each T th three-phase sub-winding under the P th sector.

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Active and Reactive Power Sharing Between Three-Phase Winding Sets of a Multiphase Induction Machine

Cited by 21 publications

References 21 publications

Induction Machine Faults Detection and Localization by Neural Networks Methods

Induction Machine Faults Detection and Localization by Neural Networks Methods

Finite Control Set Model Predictive Control of Six-Phase Asymmetrical Machines—An Overview

Power-Sharing Control in Bearingless Multi-Sector and Multi-Three-Phase Permanent Magnet Machines

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