Space Vectors and Pseudoinverse Matrix Methods for the Radial Force Control in Bearingless Multisector Permanent Magnet Machines

Sala, Giacomo; Valente, Giorgio; Formentini, Andrea; Papini, Luca; Gerada, David; Zanchetta, Pericle; Tani, A.; Gerada, Christopher

doi:10.1109/tie.2018.2795590

Cited by 25 publications

(21 citation statements)

References 24 publications

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“…Consequently, the simultaneous control of both torque and radial force can be implemented as a function of the three current space vectors of order p, p-1 and p+1 as follows [48]:…”

Section: Torque and Radial Force Equationsmentioning

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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“…Consequently, the simultaneous control of both torque and radial force can be implemented as a function of the three current space vectors of order p, p-1 and p+1 as follows [48]:…”

Section: Torque and Radial Force Equationsmentioning

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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“…Furthermore, the phases can be all identically placed under each machine stator pole pair or can be located in the same electrical positions but under different stator areas (sectors). This last category of multiphase windings is named as multi-sectored [30]. Finally, an interesting design of multiphase winding is the one based on a multi-winding layout.…”

Section: B Dc/ac Segmented Inverters For Multiphase Starter/generatorsmentioning

confidence: 99%

A Multiport Power Conversion System for the More Electric Aircraft

Yan

Yang

et al. 2020

IEEE Trans. Transp. Electrific.

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In more electric aircraft (MEA) weight reduction and energy efficiency constitute the key figures. Additionally, the safety and continuity of operation of its electrical power distribution system (EPDS) is of critical importance. These sets of desired features are in disagreement with each other, because higher redundancy, needed to guarantee the safety of operation, implies additional weight. In fact, EPDS is usually divided into isolated sections, which need to be sized for the worst-case scenario. Several concepts of EPDS have been investigated, aiming at enabling the power exchange among separate sections, which allows better optimization for power and weight of the whole system. In this paper, an approach based on the widespread use of multi-port power converters for both DC/DC and DC/AC stages is proposed. System integration of these two is proposed as a multiport power conversion system (MPCS), which allows a ring power distribution while galvanic isolation is still maintained, even in fault conditions. Thus, redundancy of MEA is established by no significant weight increase. A machine design analysis shows how the segmented machine could offer superior performance to the traditional one with same weight. Simulation and experimental verifications show the system feasibility in both normal and fault operations.

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“…In terms of structure, the bearingless motor has a certain similarity with the related structure of the magnetic bearing and the AC motor [7]. The windings generating the suspension force are superimposed on the stator of the motor, so that the suspension force winding and the armature winding of the motor are combined into a whole [8]. The basic principle of a bearingless motor can be realized in various conventional motors, such as induction motors, reluctance motors, permanent magnet motors, etc [9]- [12].…”

Section: Introductionmentioning

confidence: 99%

A Nonlinear Flux Linkage Model for Bearingless Induction Motor Based on GWO-LSSVM

Cheng

Sun

et al. 2019

IEEE Access

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The flux-linkage characteristics of bearingless induction motors (BIMs) are nonlinear, and the models established by the general analytical method cannot accurately reflect the actual characteristics of BIMs. Thus, a novel method for nonlinear modeling of BIM flux linkage is proposed in this paper. The main objective of this method is to improve the accuracy of the flux linkage model based on the least square support vector machine (LSSVM) technique by applying the gray wolf optimization (GWO) algorithm to determine the optimal kernel parameter and regularization parameter of the LSSVM automatically. In this method, all BIMs flux linkage data are obtained from the finite-element method. In this paper, the relationship between input and output of the nonlinear flux linkage model is studied, and the precision model of GWO-LSSVM flux linkage is obtained. The simulation results demonstrate that the GWO-LSSVM model has high prediction accuracy and strong prediction ability. In addition, the GWO-LSSVM model is compared with other models. From this simulation comparison, it can be concluded that GWO-LSSVM modeling has the characteristics of higher accuracy. INDEX TERMS Bearingless induction motor, gray wolf optimization, least squares support vector machine, nonlinear model, finite element analysis.

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Space Vectors and Pseudoinverse Matrix Methods for the Radial Force Control in Bearingless Multisector Permanent Magnet Machines

Cited by 25 publications

References 24 publications

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

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

A Multiport Power Conversion System for the More Electric Aircraft

A Nonlinear Flux Linkage Model for Bearingless Induction Motor Based on GWO-LSSVM

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