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Diagnosis and Fault Tolerant Control of Electrical Vehicle

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

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 15522

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Special Issue Editors

Dr. Moussa Boukhnifer

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Guest Editor

Laboratoire de Conception, Optimisation et Modélisation des Systèmes (LCOMS), University of Lorraine, 57000 Metz, France
Interests: diagnosis; fault-tolerant control; electrical system, energy management; power electronics
Special Issues, Collections and Topics in MDPI journals

Dr. Ahmed Chaibet

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Guest Editor

ESTACA, 12 avenue Paul Delouvrier, 78180 Montigny-le-Bretonneux, France
Interests: robust control; electrical drives; autonomous systems

Prof. Dr. Kondo Adjallah

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Guest Editor

Ecole Nationale d’Ingénieurs, Université de Lorraine, 57000 Metz, France
Interests: intelligent data acquisition; risk; anticipation; resilience; RUL; machine health monitoring; maintenance decision support
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Guest Editors are inviting submissions for a Special Issue of Energies on the subject area of "Diagnosis and Fault-Tolerant Control of Electric Vehicles". The development and progress of electric vehicles is directly related to their electric powertrains. A typical electric powertrain includes an energy source, a power inverter, and an electrical machine. The energy source is basically a high-voltage battery, but it can be a hybrid source (e.g., fuel cell and battery). However, the electric powertrain can be affected by failures in the battery (short-circuited cell, stack or cells performance degradation, etc.), failures in the power converters (short-circuit or open-circuit of the power switches), failures of the sensors (mechanical or electrical), or failures in the electrical machine or some mechanical parts (e.g., bearings systems).

In this context, the appearance of a fault can lead to substantial damage that can even be dangerous for humans and the environment. Consequently, a high degree of fault tolerance is required for electric vehicle systems. This can later be realized using certain redundant material components, or by detecting and isolating the faults at an early stage of their development so as to perform required system operation against faults. In fact, it is necessary to develop suitable strategies for fault-tolerant control (FTC) in order to maintain drive system stability even in failure situations.

This Special Issue invites original articles that address state-of-the-art research and developments as well as future trends in (but not limited to) the following topics of interest in electric vehicles:

Robust control strategies of electric vehicles;
Failure detection and diagnosis in EVs;
Fault-tolerant control of electric vehicles;
Energy management systems in EVs.

Dr. Moussa Boukhnifer
Dr. Ahmed Chaibet
Prof. Kondo Adjallah
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

diagnosis
fault-tolerant control
robust control
machine drives
electric vehicle

Published Papers (5 papers)

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Research

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20 pages, 18903 KiB

Open AccessArticle

Fault-Tolerant Control for Reducing Harmonic Distortion of Dual Three-Phase Permanent Magnet Synchronous Motor

by Liping Zhao, Baojun Ge, Hanying Gao and Dajun Tao

Energies 2022, 15(11), 3887; https://0-doi-org.brum.beds.ac.uk/10.3390/en15113887 - 25 May 2022

Cited by 2 | Viewed by 1351

Abstract

Aiming at the open circuit fault of a dual three-phase permanent magnet synchronous motor, a normalized current method is used for open circuit fault diagnosis. Then, a fault-tolerant control strategy for reducing the harmonic distortion of a dual three-phase permanent magnet synchronous motor is proposed, which is based on current model prediction control and keeps the decoupling transformation matrix unchanged. The fault-tolerant control method based on current model prediction considers the influence of the control quantity on the future state of the system, and effectively reduces the total harmonic distortion. Two fault-tolerant control strategies for the motor are analyzed, with minimizing stator copper consumption and maximizing torque output as control objectives. Through simulation and experiment of fault-tolerant control strategies for a dual three-phase permanent magnet synchronous motor, the results verify the effectiveness and feasibility of the strategy. Full article

(This article belongs to the Special Issue Diagnosis and Fault Tolerant Control of Electrical Vehicle)

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17 pages, 7868 KiB

Open AccessArticle

Data-Driven Fault Diagnosis for Automotive PEMFC Systems Based on the Steady-State Identification

by Ying Tian, Qiang Zou and Jin Han

Energies 2021, 14(7), 1918; https://0-doi-org.brum.beds.ac.uk/10.3390/en14071918 - 30 Mar 2021

Cited by 14 | Viewed by 2106

Abstract

Data-driven diagnosis methods for faults of proton exchange membrane fuel cell (PEMFC) systems can diagnose faults through the state variable data collected during the operation of the PEMFC system. However, the state variable data collected from the PEMFC system during the stack switching between different operating points can easily cause false alarms, such that the practical value of the diagnosis system is reduced. To overcome this problem, a fault diagnosis method for PEMFC systems based on steady-state identification is proposed in this paper. The support vector data description (SVDD) and relevance vector machine (RVM) optimized by the artificial bee colony (ABC) are used for the steady-state identification and fault diagnosis. The density-based spatial clustering of applications with noise (DBSCAN) and linear least squares fitting (LLSF) are used to identify the abnormal data in datasets and estimate change rates of the system state variables respectively. The proposed method can automatically identify the state variable data collected from the PEMFC system during the stack switching between different operating points, so that the diagnosis accuracy can be improved and false alarms can be reduced. The proposed method has a certain practical value and can provide a reference for further study. Full article

(This article belongs to the Special Issue Diagnosis and Fault Tolerant Control of Electrical Vehicle)

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18 pages, 4974 KiB

Open AccessArticle

Sizing of Lithium-Ion Battery/Supercapacitor Hybrid Energy Storage System for Forklift Vehicle

by Théophile Paul, Tedjani Mesbahi, Sylvain Durand, Damien Flieller and Wilfried Uhring

Energies 2020, 13(17), 4518; https://0-doi-org.brum.beds.ac.uk/10.3390/en13174518 - 01 Sep 2020

Cited by 17 | Viewed by 4853

Abstract

Nowadays, electric vehicles are one of the main topics in the new industrial revolution, called Industry 4.0. The transport and logistic solutions based on E-mobility, such as handling machines, are increasing in factories. Thus, electric forklifts are mostly used because no greenhouse gas is emitted when operating. However, they are usually equipped with lead-acid batteries which present bad performances and long charging time. Therefore, combining high-energy density lithium-ion batteries and high-power density supercapacitors as a hybrid energy storage system results in almost optimal performances and improves battery lifespan. The suggested solution is well suited for forklifts which continuously start, stop, lift up and lower down heavy loads. This paper presents the sizing of a lithium-ion battery/supercapacitor hybrid energy storage system for a forklift vehicle, using the normalized Verein Deutscher Ingenieure (VDI) drive cycle. To evaluate the performance of the lithium-ion battery/supercapacitor hybrid energy storage system, different sizing simulations are carried out. The suggested solution allows us to successfully optimize the system in terms of efficiency, volume and mass, in regard to the battery, supercapacitors technology and the energy management strategy chosen. Full article

(This article belongs to the Special Issue Diagnosis and Fault Tolerant Control of Electrical Vehicle)

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15 pages, 2730 KiB

Open AccessArticle

Experimental Sensorless Control of Switched Reluctance Motor for Electrical Powertrain System

by Ahmed Chaibet, Moussa Boukhnifer, Nadir Ouddah and Eric Monmasson

Energies 2020, 13(12), 3081; https://0-doi-org.brum.beds.ac.uk/10.3390/en13123081 - 15 Jun 2020

Cited by 6 | Viewed by 2216

Abstract

In this paper a mechanical sensorless control of Switched Reluctance Motors (SRMs) scheme of an electric vehicle (EV) powertrain is presented. The aim is to develop a soft sensors implementation for position and speed measurements of SRM. This contribution is focused on an extended Kalman filter and a sliding mode observer. The proposed observers are designed to generate speed and position estimations with the purpose of achieving highly robust speed control. The performances of these two observers are assessed and their robustness are analyzed. The design also includes a robustness analysis of the proposed mechanical sensorless control scheme under conditions which take the parameter variations and the load torque into account. To carry out this work, experiments are highlighted on an experimental test bench of 8/6 Switched Reluctance Motor prototype. Full article

(This article belongs to the Special Issue Diagnosis and Fault Tolerant Control of Electrical Vehicle)

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Review

Jump to: Research

19 pages, 4007 KiB

Open AccessReview

Thorough Review Analysis of Safe Control of Autonomous Vehicles: Path Planning and Navigation Techniques

by Sara Abdallaoui, El-Hassane Aglzim, Ahmed Chaibet and Ali Kribèche

Energies 2022, 15(4), 1358; https://0-doi-org.brum.beds.ac.uk/10.3390/en15041358 - 14 Feb 2022

Cited by 22 | Viewed by 3848

Abstract

Mobile robot path planning has passed through multiple phases of development and took up several challenges. Up to now and with the new technology in hands, it becomes less complicated to conduct path planning for mobile robots and avoid both static and dynamic obstacles, so that collision-free navigation is ensured. Thorough state of the art review analysis with critical scrutiny of both safe and optimal paths for autonomous vehicles is addressed in this study. Emphasis is given to several developed techniques based using sampling algorithms, node-based optimal algorithms, mathematic model-based algorithms, bio-inspired algorithms, which includes neural network algorithms, and then multi-fusion-based algorithms, which combine different methods to overcome the drawbacks of each. All of these approaches consider different conditions and they are used for multiple domains. Full article

(This article belongs to the Special Issue Diagnosis and Fault Tolerant Control of Electrical Vehicle)

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