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Fault Diagnosis and Fault-Tolerant Control for Power Systems and Machine Drives in Electrical Transport Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: closed (14 March 2022) | Viewed by 15770

Special Issue Editor

Dr. Cristina Morel

E-Mail Website
Guest Editor
Energy and Control of Transportation Systems Laboratory, Graduate School of Aeronautical, Aerospace, Automobile, Railway Engineering (ESTACA), 53061 Laval, France
Interests: power electronics; renewable energies; nonlinear dynamics; fault diagnosis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Guest Editor is inviting submissions for a Special Issue of Energies on the subject area of “Fault Diagnosis and Fault-Tolerant Control for Power Systems and Machine Drives in Electrical Transport Systems”.

Innovation in the transportation domain (automobile, aeronautics, railway, and ship) has made considerable progress in recent years, improving the performance of vehicle drivetrain architectures. The drivetrain can be exposed during its operation to various types of faults that may occur within the electronic power stage or the electrical machine. Reliability in the electrical drives is an important issue in many applications. The detection and isolation of faults is necessary but not sufficient to guarantee operational reliability. Indeed, to maintain a certain level of performance in degraded mode, the system must possess some degrees of redundancies or modify the control law by integrating a fault-tolerant control to ensure operating safety.

This Special Issue will focus on Fault Diagnosis and Fault-Tolerant Control for Power Systems and Machine Drives in Electrical Transport Systems.

Topics of interest for publication include but are not limited to:

  • Electrical polyphase machines;
  • Topologies for high voltage inverter/converter;
  • Stability analysis of power electronic circuits;
  • Fault diagnosis, detection, localization, and fault-tolerant control scheme;
  • Artificial intelligence techniques.

Dr. Cristina MOREL
Guest Editor

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

  • Fault diagnosis and fault-tolerant control scheme 
  • Power systems in electrical transport applications 
  • Motor drives
  • Power converters/inverters

Published Papers (6 papers)

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Editorial

Jump to: Research

7 pages, 3334 KiB  
Editorial
Fault Diagnosis Methods and Fault Tolerant Control Strategies for the Electric Vehicle Powertrains
by Chenyun Wu, Rabia Sehab, Ahmad Akrad and Cristina Morel
Energies 2022, 15(13), 4840; https://doi.org/10.3390/en15134840 - 1 Jul 2022
Cited by 8 | Viewed by 4770
Abstract
With the challenges of global climate anomalies and energy crises, vehicle electrification has an increasing trend as an exciting solution for reducing greenhouse gas emissions and fossil fuel-based energy consumption [...] Full article
(This article belongs to the Special Issue Fault Diagnosis and Fault-Tolerant Control for Power Systems and Machine Drives in Electrical Transport Systems)
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Research

Jump to: Editorial

18 pages, 7430 KiB  
Article
Velocity Sensor Fault-Tolerant Controller for Induction Machine Using Intelligent Voting Algorithm
by Fadi Alyoussef, Ahmad Akrad, Rabia Sehab, Cristina Morel and Ibrahim Kaya
Energies 2022, 15(9), 3084; https://doi.org/10.3390/en15093084 - 22 Apr 2022
Cited by 9 | Viewed by 2297
Abstract
Nowadays, induction machines (IMs) are widely used in industrial and transportation applications (electric or hybrid ground vehicle or aerospace actuators) thanks to their significant advantages in comparison to other technologies. Indeed, there is a large demand for IMs because of their reliability, robustness, [...] Read more.
Nowadays, induction machines (IMs) are widely used in industrial and transportation applications (electric or hybrid ground vehicle or aerospace actuators) thanks to their significant advantages in comparison to other technologies. Indeed, there is a large demand for IMs because of their reliability, robustness, and cost-effectiveness. The objective of this paper is to improve the reliability and performance of the three-phase induction machine in case of mechanical sensor failure. Moreover, this paper will discuss the development and proposal of a fault-tolerant controller (FTC), based on the combination of a vector controller, two virtual sensors (an extended Kalman filter, or EKF, and a sliding mode observer, or SMO) and a neural voting algorithm. In this approach, the vector controller is based on a new structure of a back-stepping sliding mode controller, which incorporates a double integral sliding surface to improve the performance of the induction machine in faulty operation mode. More specifically, this controller improves the machine performance in terms of having a fast response, fewer steady-state errors, and a robust performance in the existence of uncertainty. In addition, two voting algorithms are suggested in this approach. The first is based on neural networks, which are insensitive to parameter variations and do not need to set a threshold. The second one is based on fuzzy logic. Finally, validation is carried out by simulations in healthy and faulty operation modes to prove the feasibility of the proposed FTC. Full article
(This article belongs to the Special Issue Fault Diagnosis and Fault-Tolerant Control for Power Systems and Machine Drives in Electrical Transport Systems)
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18 pages, 4902 KiB  
Article
Charging Electric Vehicles from Photovoltaic Systems—Statistical Analyses of the Small Photovoltaic Farm Operation
by Arkadiusz Małek, Agnieszka Dudziak, Ondrej Stopka, Jacek Caban, Andrzej Marciniak and Iwona Rybicka
Energies 2022, 15(6), 2137; https://doi.org/10.3390/en15062137 - 15 Mar 2022
Cited by 7 | Viewed by 2250
Abstract
Zero-emission transport is a very important topic that is increasingly taken up by many institutions and research centers around the world. However, the zero-emissivity of the vehicle is quite a complex issue, which should be understood as not only the lack of emissions [...] Read more.
Zero-emission transport is a very important topic that is increasingly taken up by many institutions and research centers around the world. However, the zero-emissivity of the vehicle is quite a complex issue, which should be understood as not only the lack of emissions during the operation of the vehicle, but also the provision of clean energy to the vehicle. In this approach, charging the battery of an electric vehicle from renewable sources—a photovoltaic (PV) farm—and its operation can be considered as a totally zero-emission form of transport. The article presents a PV system containing two micro-installations with a capacity of up to 40 kWp each to supply electricity to two parts of the Lublin Science and Technology Park (LSTP) building. Thanks to the innovative monitoring system, it was possible to analyze the consumption and production as well as the effective use of electricity. Statistical analyses of consumption (charging the electric vehicle battery) and electricity production by the PV installation were carried out. It was found that charging an electric vehicle could be a good way to use the surplus energy production from the farm and thus a faster repayment on investment in the PV farm installation. Full article
(This article belongs to the Special Issue Fault Diagnosis and Fault-Tolerant Control for Power Systems and Machine Drives in Electrical Transport Systems)
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14 pages, 1813 KiB  
Article
Fast Real-Time RDFT- and GDFT-Based Direct Fault Diagnosis of Induction Motor Drive
by Piotr Kołodziejek and Daniel Wachowiak
Energies 2022, 15(3), 1244; https://doi.org/10.3390/en15031244 - 8 Feb 2022
Cited by 3 | Viewed by 1704
Abstract
This paper presents the theoretical analysis and experimental verification of a direct fault harmonic identification approach in a converter-fed electric drive for automated diagnosis purposes. On the basis of the analytical model of the proposed real-time direct fault diagnosis, the fault-related harmonic component [...] Read more.
This paper presents the theoretical analysis and experimental verification of a direct fault harmonic identification approach in a converter-fed electric drive for automated diagnosis purposes. On the basis of the analytical model of the proposed real-time direct fault diagnosis, the fault-related harmonic component is calculated using recursive DFT (RDFT) and Goertzel DFT (GDFT), applied instead of the full spectrum calculations required in the most popular FFT algorithm. The simulation model of an inverter sensorlessly controlled induction motor drive is linked with the induction machine rotor fault model for testing the sensitivity of the GDFT- and RDFT-based fault diagnosis to state variable estimation errors. According to the presented simulation results, the accuracy of the direct identification of a fault-related harmonic is sensitive to the quality of fault harmonic frequency estimation. The sensitivity analysis with respect to RDFT and GDFT algorithms is included. Based on the experimental setup with a sensorlessly controlled induction motor drive with the investigated rotor fault, fault diagnosis algorithms were implemented in the microprocessor by integration with the control system in one microcontroller and experimentally verified. The RDFT and GDFT approach has shown accurate and fast direct automated fault identification at a significantly decreased number of arithmetical operations in the microcontroller, which is convenient for the frequency-domain fault diagnosis in electric drives and supports fault-tolerant control system implementation. Full article
(This article belongs to the Special Issue Fault Diagnosis and Fault-Tolerant Control for Power Systems and Machine Drives in Electrical Transport Systems)
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23 pages, 1594 KiB  
Article
Open-Circuit Fault-Tolerant Strategy for Interleaved Boost Converters via Filippov Method
by Cristina Morel, Ahmad Akrad, Rabia Sehab, Toufik Azib and Cherif Larouci
Energies 2022, 15(1), 352; https://doi.org/10.3390/en15010352 - 4 Jan 2022
Cited by 7 | Viewed by 1486
Abstract
Interleaved converters use an increased number of power electronics switches; this may subsequently affect their reliability. However, this is an opportunity to develop fault-tolerant strategies to improve their reliability and to ensure continuity of service. This is why we herein propose, for the [...] Read more.
Interleaved converters use an increased number of power electronics switches; this may subsequently affect their reliability. However, this is an opportunity to develop fault-tolerant strategies to improve their reliability and to ensure continuity of service. This is why we herein propose, for the first time, a mathematical function to simultaneously model the healthy and faulty conditions of each switch, thus enabling a unique model of the system. This model is then used in an original fault-tolerant strategy based upon the peak current control with slope compensation. This method not only extends the stable range of the load variation but also ensures the stability in faulty conditions. Finally, the simulation results validate its effectiveness and confirm the theoretical analysis. Full article
(This article belongs to the Special Issue Fault Diagnosis and Fault-Tolerant Control for Power Systems and Machine Drives in Electrical Transport Systems)
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22 pages, 7243 KiB  
Article
A Hybrid Framework for Detecting and Eliminating Cyber-Attacks in Power Grids
by Arshia Aflaki, Mohsen Gitizadeh, Roozbeh Razavi-Far, Vasile Palade and Ali Akbar Ghasemi
Energies 2021, 14(18), 5823; https://doi.org/10.3390/en14185823 - 15 Sep 2021
Cited by 13 | Viewed by 2274
Abstract
The work described in this paper aims to detect and eliminate cyber-attacks in smart grids that disrupt the process of dynamic state estimation. This work makes use of an unsupervised learning method, called hierarchical clustering, in an attempt to create an artificial sensor [...] Read more.
The work described in this paper aims to detect and eliminate cyber-attacks in smart grids that disrupt the process of dynamic state estimation. This work makes use of an unsupervised learning method, called hierarchical clustering, in an attempt to create an artificial sensor to detect two different cyber-sabotage cases, known as false data injection and denial-of-service, during the dynamic behavior of the power system. The detection process is conducted by using an unsupervised learning-enhanced approach, and a decision tree regressor is then employed for removing the threat. The dynamic state estimation of the power system is done by Kalman filters, which provide benefits in terms of the speed and accuracy of the process. Measurement devices in utilities and buses are vulnerable to communication interruptions between phasor measurement units and operators, who can be easily manipulated by false data. While Kalman filters are incapable of detecting the majority of such cyber-attacks, this article proves that the proposed unsupervised machine learning method is able to detect more than 90 percent of the mentioned attacks. The simulation results on the IEEE 9-bus with 3-machines and IEEE 14-bus with 5-machines systems verify the efficiency of the proposed approach. Full article
(This article belongs to the Special Issue Fault Diagnosis and Fault-Tolerant Control for Power Systems and Machine Drives in Electrical Transport Systems)
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