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Energies
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Reliability and Condition Monitoring of Electric Motors and Drives
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Reliability and Condition Monitoring of Electric Motors and Drives

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: 28 January 2025 | Viewed by 4453

Special Issue Editors

Dr. Paolo Giangrande

E-Mail Website
Guest Editor
Department of Engineering and Applied Sciences, University of Bergamo, 24129 Bergamo, Italy
Interests: rotating electrical machines; fault-tolerant design and control; lifetime modelling; partial discharge; reliability-oriented design; thermal management
Dr. Marcello Minervini

E-Mail Website
Guest Editor
Department of Engineering and Applied Sciences, University of Bergamo, 24129 Bergamo, Italy
Interests: electrical machines; diagnostics of electrical machines; predictive maintenance; motor current signature analysis; stray flux analysis; vibration analysis

Special Issue Information

Dear Colleagues,

The growing demand for more energy-efficient technologies is acting as a driving force in the development of lightweight and high-power density electric drives intended for applications ranging from industry to the transport sector. Nevertheless, failures occurring in electric drive components (i.e., motor, power converter, battery) might lead to significant consequences in terms of economic losses and down-times. Therefore, condition-monitoring technology, fault-tolerant design, and enhanced reliability represent viable solutions for preventing and minimizing failure outcomes.

This Special Issue intends to collect original research, practical contributions, and review articles on the condition monitoring and fault‑tolerant design of electrical machines and drives. Research studies on insulation aging mechanisms, lifetime prediction, and partial discharge are also invited.

Topics of interest include but are not limited to:

  • Condition monitoring and signal processing;
  • Fault-tolerant electrical machines and drives;
  • Advanced control algorithms for improving reliability;
  • Modelling, detection, and measurement of partial discharge;
  • Accelerated aging tests on electrical machine insulation;
  • Insulation lifetime modelling and prediction;
  • Prediction and diagnostics of inter-turn short circuits, bearing faults, broken rotor bars, eccentricity, and manufacturing defects.

Dr. Paolo Giangrande
Dr. Marcello Minervini
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. Energies 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

  • condition monitoring
  • fault tolerance
  • dielectric breakdown
  • partial discharge
  • diagnostics
  • lifetime forecasting

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Published Papers (4 papers)

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Research

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21 pages, 8877 KiB  
Article
The Effect of the Number of Parallel Winding Paths on the Fault Tolerance of a Switched Reluctance Motor
by Mariusz Korkosz, Jan Prokop and Piotr Bogusz
Energies 2024, 17(22), 5701; https://doi.org/10.3390/en17225701 - 14 Nov 2024
Viewed by 326
Abstract
Achieving increased fault tolerance in an electric motor requires decisions to be made about the type and specifications of the motor machine and its appropriate design. Depending on the type of motor, there are generally three ways to achieve an increased resistance of [...] Read more.
Achieving increased fault tolerance in an electric motor requires decisions to be made about the type and specifications of the motor machine and its appropriate design. Depending on the type of motor, there are generally three ways to achieve an increased resistance of the drive system to tolerate resulting faults. The simplest way is to select the right motor and design it appropriately. Switched reluctance motors (SRMs) have a high tolerance for internal faults (in the motor windings). Failure tolerance can be improved by using parallel paths. The SRM 24/16 solution has been proposed, which allows for operation with four parallel paths. In this paper, a mathematical model designed to analyse the problem under consideration is provided. Based on numerical calculations, the influence of typical faults (open and partial short circuit in one of the paths) on the electromagnetic torque generated as well as its ripple and (source and phase) currents were determined. The higher harmonics of the source current (diagnostic signal) were determined. Laboratory tests were performed to verify the various configurations for the symmetric and emergency operating states. The feasibility of SRM correct operation monitoring was determined from an FFT analysis of the source current. Full article
(This article belongs to the Special Issue Reliability and Condition Monitoring of Electric Motors and Drives)
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19 pages, 7534 KiB  
Article
Improved Fault Detection Using Shifting Window Data Augmentation of Induction Motor Current Signals
by Robert Wright, Poria Fajri, Xingang Fu and Arash Asrari
Energies 2024, 17(16), 3956; https://doi.org/10.3390/en17163956 - 9 Aug 2024
Viewed by 886
Abstract
Deep learning models have demonstrated potential in Condition-Based Monitoring (CBM) for rotating machinery, such as induction motors (IMs). However, their performance is significantly influenced by the size of the training dataset and the way signals are presented to the model. When trained on [...] Read more.
Deep learning models have demonstrated potential in Condition-Based Monitoring (CBM) for rotating machinery, such as induction motors (IMs). However, their performance is significantly influenced by the size of the training dataset and the way signals are presented to the model. When trained on segmented signals over a fixed period, the model’s accuracy can decline when tested on signals that differ from the training interval or are randomly sampled. Conversely, models utilizing data augmentation techniques exhibit better generalization to unseen conditions. This paper highlights the bias introduced by traditional training methods towards specific periodic waveform sampling and proposes a new method to augment phase current signals during training using a shifting window technique. This approach is considered as a practical approach for motor current augmentation and is shown to enhance classification accuracy and improved generalization when compared to existing techniques. Full article
(This article belongs to the Special Issue Reliability and Condition Monitoring of Electric Motors and Drives)
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14 pages, 8541 KiB  
Article
Optimized Fabrication Process and PD Characteristics of MVDC Multilayer Insulation Cable Systems for Next Generation Wide-Body All-Electric Aircraft
by Md Asifur Rahman, Anoy Saha and Mona Ghassemi
Energies 2024, 17(12), 3040; https://doi.org/10.3390/en17123040 - 20 Jun 2024
Cited by 1 | Viewed by 1037
Abstract
For wide-body all-electric aircraft (AEA), a high-power-delivery, low-system-mass electric power system (EPS) necessitates advanced cable technologies. Increasing voltage levels enhances power density yet poses challenges in aircraft cable design, including managing arc-related risks, partial discharges (PDs), and thermal management. Developing multilayer multifunctional electrical [...] Read more.
For wide-body all-electric aircraft (AEA), a high-power-delivery, low-system-mass electric power system (EPS) necessitates advanced cable technologies. Increasing voltage levels enhances power density yet poses challenges in aircraft cable design, including managing arc-related risks, partial discharges (PDs), and thermal management. Developing multilayer multifunctional electrical insulation (MMEI) systems for aircraft applications is a feasible option to tackle these challenges and reduce the size and mass of cable systems. This approach involves selecting layers of different materials to address specific challenges. Our prior research concentrated on the modeling and simulation-based design of MMEI systems for MVDC power cables. Experimental tests are essential for determining the behavior of PDs under varying pressure conditions. Also, the dielectric strength and time to failure of the designs need to be assessed. In this work, the fabrication process of a down-selected MMEI flat configuration is discussed and analyzed. This paper analyzes the fabrication process of power cables employing MMEI configurations and evaluates the PD characteristics of down-selected ARC-SC-T-MMEI cable samples. This study presents a detailed analysis of the characteristics of PD under atmospheric and low-pressure conditions, which will provide essential insights into the design of MVDC cables for future AEA applications. Full article
(This article belongs to the Special Issue Reliability and Condition Monitoring of Electric Motors and Drives)
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Review

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30 pages, 9870 KiB  
Review
Insulation for Rotating Low-Voltage Electrical Machines: Degradation, Lifetime Modeling, and Accelerated Aging Tests
by Xuanming Zhou, Paolo Giangrande, Yatai Ji, Weiduo Zhao, Salman Ijaz and Michael Galea
Energies 2024, 17(9), 1987; https://doi.org/10.3390/en17091987 - 23 Apr 2024
Cited by 3 | Viewed by 1585
Abstract
The low-voltage electric machine (EM) is a core technology for transportation electrification, and features like high power density and compact volume are essential prerequisites. However, these requirements are usually in conflict with the reliability property of EM, especially in the safety-critical industry such [...] Read more.
The low-voltage electric machine (EM) is a core technology for transportation electrification, and features like high power density and compact volume are essential prerequisites. However, these requirements are usually in conflict with the reliability property of EM, especially in the safety-critical industry such as aviation. Therefore, an appropriate balance between high-performance and reliability needs to be found. Often, the over-engineering method is applied to ensure safety, although it might have a detrimental effect on the EM volume. To address this issue, the EM reliability assessment is included at the EM design stage through the physics of failure (PoF) theory. In EMs, the windings play a key role in electromechanical energy conversion, but their insulation system is subject to frequent failure and represents a reliability bottleneck. Therefore, in-depth research on the root causes of insulation breakdown is beneficial for EM reliability improvement purposes. Indeed, increasing awareness and knowledge on the mechanism of the insulation degradation process and the related lifetime modeling enables the growth of appropriate tools for achieving reliability targets since the first EM design steps. In this work, the main aspects of the insulation system, in terms of materials and manufacturing, are first reviewed. Then, the principal stresses experienced by the winding insulation system are deeply discussed with the purpose of building a profound understanding of the PoF. Finally, an overview of the most common insulation lifetime prediction models is presented, and their use for accomplishing the reliability-oriented design (RoD) and the remaining useful life (RUL) estimation are examined. Full article
(This article belongs to the Special Issue Reliability and Condition Monitoring of Electric Motors and Drives)
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