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Mathematics
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Control, Modeling and Optimization for Multiphase Machines and Drives
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Control, Modeling and Optimization for Multiphase Machines and Drives

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 8135

Special Issue Editors

Dr. Kotb Basem Tawfiq

E-Mail Website
Guest Editor
Department of Electromechanical, Systems, and Metal Engineering, Ghent University, 9000 Ghent, Belgium
Interests: matrix converter; inverter; space vector modulation; symmetrical sequence algorithm; wind energy conversion system; synchronous reluctance machine; multiphase machine; vector control; winding function; harmonic analysis; star-pentagon and optimization techniques
Special Issues, Collections and Topics in MDPI journals
Dr. Mohamed N. Ibrahim

E-Mail Website
Guest Editor
Department of Electromechanical, Systems and Metal Engineering, Ghent University, 9052 Ghent, Belgium
Interests: synchronous reluctance machine; permanent magnet assisted synchronous reluctance motors; field-oriented control; winding function; harmonic analysis; star-delta; magnetic steel grade and optimization techniques
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The study of multiphase machines has emerged as a promising research area in recent years as interest in electrical machines has increased. They are an extremely fascinating alternative to traditional three-phase machines due to their inherent qualities, such as improved fault tolerance, or decreased torque ripple. Recently, multiphase electric drives have been employed in situations where the drive's fault tolerance and continuous operation are essential. Their widespread use in industrial solutions is still constrained by the challenges of extending the three-phase conventional current regulation and control structure to multiphase systems. The essential component of a multiphase drive system, such as an electrical vehicle, a hospital, or a military application, is the power electronic converter. The power converter's switching frequency greatly affects the machine performance that is ultimately attained. The power converter switching has a significant impact on the drive system's efficiency and torque density. This influence could be reduced given the fast-paced development of power electronics. You are pleasantly invited to submit your original research or review papers to this Special Issue on “Control, Modeling and Optimization for Multiphase Machines and Drives” in Mathematics.

The main objective of this Special Issue is to promote new advancements, developments, and applications of control, modeling and optimization in the field of multiphase machines and drives. Additionally, carefully choose the switching or create a power converter that has a minimal effect on the machine's performance. Moreover, this impact is important to be considered especially under the fault condition. This is not limited to the type of machine or the type of power converter. The topics of interest include, but are not limited to, mathematical and numerical methods applied to:

  1. Power converter topologies;
  2. Associated control and modulation techniques;
  3. Modeling and switching enhancement techniques for power converters;
  4. New technologies in multiphase drives;
  5. Fault detection and diagnosis;
  6. Innovative winding.

Dr. Kotb Basem Tawfiq
Dr. Mohamed N. Ibrahim
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multiphase machines
  • power converter
  • multiphase drives
  • electric machines
  • switching losses
  • fault tolerance control
  • parameter estimation
  • model predictive control
  • modulation techniques
  • innovative winding
  • mathematical modeling
  • control methods
  • numerical analysis
  • optimization algorithms

Published Papers (5 papers)

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Research

19 pages, 6672 KiB  
Article
Neural Network-Driven Sensorless Speed Control of EV Drive Using PMSM
by Harshit Mohan, Gopal Agrawal, Vibhu Jately, Abhishek Sharma and Brian Azzopardi
Mathematics 2023, 11(19), 4029; https://doi.org/10.3390/math11194029 - 22 Sep 2023
Viewed by 746
Abstract
To reduce pollution and energy consumption, particularly in the automotive industry, energy saving is the main concern, and hence, Electric vehicles (EVs) are getting significantly more attention than vehicles with internal combustion engines (IC engines). Electric motors used in Electric Vehicles (EVs) must [...] Read more.
To reduce pollution and energy consumption, particularly in the automotive industry, energy saving is the main concern, and hence, Electric vehicles (EVs) are getting significantly more attention than vehicles with internal combustion engines (IC engines). Electric motors used in Electric Vehicles (EVs) must have high efficiency for maximum utilization of the energy from the batteries or fuel cells. Also, these motors must be compact, lightweight, less expensive and very easily recycled. Further, to obtain better dynamic performance, various motor control strategies are used to control the speed of the motor. And to have increased reliability, sensorless speed control techniques that offer sufficiently high performance are used. The sensorless speed control techniques are largely divided into three groups: state observer methods, indirect measurement methods and saliency-based methods. Generally, the state observer uses back emf or flux linkage to estimate the speed of the motor. Since the back emf is directly proportional to the rotor speed, at low-speed back emf based method will give poor performance. The current-based Model Reference Adaptive System (MRAS) model is also popular for estimating low speed; however, assessments deteriorate during high performance applications such as EV. This paper presents an artificial neural network (ANN)-deployed sensorless speed control of permanent magnet synchronous motor (PMSM) drive used in EVs. In this paper, the estimation of speed using the current-based MRAS model is discussed and compared with the proposed ANN-based controller, which shows significant improvement in the performance of EV motor drives. The MATLAB simulation and experimental results are presented to validate the proposed algorithm. Full article
(This article belongs to the Special Issue Control, Modeling and Optimization for Multiphase Machines and Drives)
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18 pages, 5118 KiB  
Article
Performance of a Vector-Controlled PMSM Drive without Using Current Sensors
by Sai Shiva Badini, Vimlesh Verma, Mohd Tariq, Shabana Urooj and Lucian Mihet-Popa
Mathematics 2022, 10(23), 4623; https://doi.org/10.3390/math10234623 - 06 Dec 2022
Viewed by 1747
Abstract
The current sensorless vector-controlled permanent-magnet synchronous motor (PMSM) drive using a single sensor (i.e., speed sensor) is presented in this work. The current sensors are removed, and the estimated currents are used to close the current loop to minimize the drive cost and [...] Read more.
The current sensorless vector-controlled permanent-magnet synchronous motor (PMSM) drive using a single sensor (i.e., speed sensor) is presented in this work. The current sensors are removed, and the estimated currents are used to close the current loop to minimize the drive cost and make it fault-tolerant against current sensor failure. A classical vector-control PMSM drive requires at least three sensors, i.e., two current sensors and one speed/position sensor. This paper presents a new current estimation technique that is free from inverter switching states, an integrator, and differentiator terms. The drive is suitable for retrofit applications, as it does not require any additional hardware. The reference voltages (vds and vqs) are used to estimate the rotor reference frame currents (i.e., iqs and ids). The presented algorithm depends on the stator resistance (Ɍs). The online Ɍs estimation algorithm is used for compensation to overcome the effect of the Ɍs on the estimated currents. The sensitivity analysis for the currents against the speed is verified and presented. The speed loop is closed with actual speed information, which will try to maintain the reference speed under any circumstances. The proposed current sensorless PMSM drive was validated using MATLAB/Simulink and also verified on a hardware prototype. The presented technique was verified for various operation conditions, and some of the extensive results are presented. Full article
(This article belongs to the Special Issue Control, Modeling and Optimization for Multiphase Machines and Drives)
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12 pages, 3313 KiB  
Article
A Practical Approach to Identify the Phases Sequence in Five Phase Machines with Combined Star–Pentagon Configuration
by Kotb B. Tawfiq, Mohamed N. Ibrahim, Ayman M. EL-Refaie and Peter Sergeant
Mathematics 2022, 10(21), 4086; https://doi.org/10.3390/math10214086 - 02 Nov 2022
Viewed by 1190
Abstract
Due to the significant advantages of a high torque density, better fault tolerance and high efficiency, the combined star–pentagon winding has recently gained researchers’ interest. In this paper, a simple method to identify the sequence of phases of a five-phase machine with combined [...] Read more.
Due to the significant advantages of a high torque density, better fault tolerance and high efficiency, the combined star–pentagon winding has recently gained researchers’ interest. In this paper, a simple method to identify the sequence of phases of a five-phase machine with combined star–pentagon winding was proposed. This was accomplished using resistance measurements between adjacent and non-adjacent phases. The analysis was conducted to clarify the phase sequence identification method. A case study of a 5.5 kW five-phase synchronous reluctance motor with combined star–pentagon winding was considered to simply apply the proposed method using an LCR meter for resistance measurements. The parasitic and wire resistances are dominant in the studied case, and this did not influence the accuracy of this method. Full article
(This article belongs to the Special Issue Control, Modeling and Optimization for Multiphase Machines and Drives)
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16 pages, 3626 KiB  
Article
Comparative Study of Electrically Excited Conventional and Homopolar Synchronous Motors for the Traction Drive of a Mining Dump Truck Operating in a Wide Speed Range in Field-Weakening Region
by Vladimir Prakht, Vladimir Dmitrievskii, Vadim Kazakbaev and Alecksey Anuchin
Mathematics 2022, 10(18), 3364; https://doi.org/10.3390/math10183364 - 16 Sep 2022
Cited by 6 | Viewed by 2207
Abstract
A synchronous homopolar motor (SHM) has a salient pole passive rotor, an excitation winding located on the stator, and no permanent magnets, which ensures high reliability and makes this type of motor a good alternative to motors traditionally used in traction drives. However, [...] Read more.
A synchronous homopolar motor (SHM) has a salient pole passive rotor, an excitation winding located on the stator, and no permanent magnets, which ensures high reliability and makes this type of motor a good alternative to motors traditionally used in traction drives. However, there is no comparison between SHMs and conventional brushed synchronous machines for traction applications in the literature. In this paper, the performances of a wound rotor synchronous machine (WRSM) and SHM are theoretically compared at the operating points of a 370 kW dump mining truck drive traction curve that has a 10:1 constant power range in the field weakening region. The nine-phase motors under comparison have the same outer diameter of the stator lamination. Before comparison, both motor designs are optimized using the Nelder–Mead method to minimize the semiconductor inverter rated current and the operating cycle power loss. The main advantages of the WRSM, which was designed, are reduction in stator length, smaller losses, and smaller inverter. The reduction in the total stator length was by 1.23 times taking into account the winding end parts as well. Losses were reduced by 1.21 times for the same radius of the stator lamination. Finally, the cost of power modules of the inverter was decreased by 1.4 times. SHM is more reliable since its rotor does not have an excitation winding and a diode rectifier, as in a WRSM with a brushless exciter. In addition, SHM provides lower consumption of copper, which reduces the total mass and cost of active materials. This article also introduces a new term, “inverter utilization factor”, which can be useful, more informative than motor power factor, when comparing traction drives with different types of motors. Full article
(This article belongs to the Special Issue Control, Modeling and Optimization for Multiphase Machines and Drives)
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18 pages, 4958 KiB  
Article
Multiphase Electric Motor Drive with Improved and Reliable Performance: Combined Star-Pentagon Synchronous Reluctance Motor Fed from Matrix Converter
by Kotb B. Tawfiq, Mohamed N. Ibrahim and Peter Sergeant
Mathematics 2022, 10(18), 3351; https://doi.org/10.3390/math10183351 - 15 Sep 2022
Cited by 3 | Viewed by 1338
Abstract
This paper investigated and demonstrated an electric drive topology with inherently high reliability and improved performance. The topology combines a five-phase combined star-pentagon synchronous reluctance machine (SynRM) and a power electronic “matrix” converter without vulnerable electrolytic capacitors, which are often a point of [...] Read more.
This paper investigated and demonstrated an electric drive topology with inherently high reliability and improved performance. The topology combines a five-phase combined star-pentagon synchronous reluctance machine (SynRM) and a power electronic “matrix” converter without vulnerable electrolytic capacitors, which are often a point of failure of conventional drives. This drive is suitable for harsh environments, with possibly high ambient temperatures and limited maintenance. In this paper, an accurate model of the five-phase combined star-pentagon SynRM was introduced considering the effect of magnetic saturation and cross saturation on dq-flux-linkages. The five-phase combined star-pentagon SynRM will be connected to a three-to-five-phase indirect matrix converter (IMC) and the indirect field-oriented control based on a space vector pulse width modulation was applied. The introduced SVM commutates the bidirectional switches of the IMC at zero current which enhance and minimize the switching losses. The performance of the proposed drive system was studied and experimentally validated at different loading conditions. Finally, the reliability, cost, and performance of the proposed drive system were compared with the conventional drive system (three-phase star-connected SynRM fed from rectifier-inverter). Full article
(This article belongs to the Special Issue Control, Modeling and Optimization for Multiphase Machines and Drives)
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