Cervone, Andrea (2021) Modelling and control techniques for multiphase electric drives: a phase variable approach. [Tesi di dottorato]

[img]
Preview
Text
Cervone_Andrea_33.pdf

Download (96MB) | Preview
[error in script] [error in script]
Item Type: Tesi di dottorato
Resource language: English
Title: Modelling and control techniques for multiphase electric drives: a phase variable approach
Creators:
CreatorsEmail
Cervone, Andreaandrea.cervone@unina.it
Date: 12 July 2021
Number of Pages: 319
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Elettrica e delle Tecnologie dell'Informazione
Dottorato: Information technology and electrical engineering
Ciclo di dottorato: 33
Coordinatore del Corso di dottorato:
nomeemail
Riccio, Danieledaniele.riccio@unina.it
Tutor:
nomeemail
Brando, GianlucaUNSPECIFIED
Date: 12 July 2021
Number of Pages: 319
Keywords: Multiphase Electric Drives; Phase Variable Control; Electrical Machines
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-IND/32 - Convertitori, macchine e azionamenti elettrici
Additional information: Thesis Supervisor: Prof. Gianluca Brando (gianluca.brando@unina.it) Thesis Co-Supervisor: Dr. Obrad Dordevic (o.dordevic@ljmu.ac.uk)
Date Deposited: 28 Jul 2021 14:25
Last Modified: 07 Jun 2023 10:41
URI: http://www.fedoa.unina.it/id/eprint/13673

Collection description

Multiphase electric drives are today one of the most relevant research topics for the electrical engineering scientific community, thanks to the many advantages they offer over standard three-phase solutions (e.g., power segmentation, fault-tolerance, optimized performances, torque/power sharing strategies, etc...). They are considered promising solutions in many application areas, like industry, traction and renewable energy integration, and especially in presence of high-power or high-reliability requirements. However, contrarily to the three-phase counterparts, multiphase drives can assume a wider variety of different configurations, concerning both the electrical machine (e.g., symmetrical/asymmetrical windings disposition, concentrated/distributed windings, etc...) and the overall drive topology (e.g., single-star configuration, multiple-star configuration, open-end windings, etc…). This aspect, together with the higher number of variables of the system, can make their analysis and control more challenging, especially when dealing with reconfigurable systems (e.g., in post-fault scenarios). This Ph.D. thesis is focused on the mathematical modelling and on the control of multiphase electric drives. The aim of this research is to develop a generalized model-based approach that can be used in multiple configurations and scenarios, requiring minimal reconfigurations to deal with different machine designs and/or different converter topologies, and suitable both in healthy and in faulty operating conditions. Standard field-oriented approaches for the analysis and control of multiphase drives, directly derived as extensions of the three-phase equivalents, despite being relatively easy and convenient solutions to deal with symmetrical machines, may suffer some hurdles when applied to some asymmetrical configurations, including post-fault layouts. To address these issues, a different approach, completely derived in the phase variable domain, is here developed. The method does not require any vector space decomposition or rotational transformation but instead explicitly considers the mathematical properties of the multiphase machine and the effects of the drive topology (which typically introduces some constraints on the system variables). In this thesis work, the proposed approach is particularized for multiphase permanent magnet synchronous machines and for multiphase synchronous reluctance machines. All the results are obtained through rigorous mathematical derivations, and are supported and validated by both numerical analysis and experimental tests. As proven considering many different configurations and scenarios, the main benefits of the proposed methodology are its generality and flexibility, which make it a viable alternative to standard modelling and control algorithms.

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item