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Mathematics
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Applied Mathematics and Intelligent Control in Electrical Engineering
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Applied Mathematics and Intelligent Control in Electrical Engineering

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

Deadline for manuscript submissions: 31 December 2024 | Viewed by 4726

Special Issue Editors

Prof. Dr. Helga Silaghi

E-Mail Website
Guest Editor
Department of Control Systems Engineering and Management, University of Oradea, 410087 Oradea, Romania
Interests: mathematical modelling of electrical machines; numerical simulation of electrical machines; modelling and simulation in electrical drives; control of electric drive systems; control systems engineering; mathematical modelling and control of robotic systems; intelligent control of electric vehicles
Dr. Claudiu Raul Costea

E-Mail Website
Guest Editor
Department of Control Systems Engineering and Management, University of Oradea, 410087 Oradea, Romania
Interests: modelling and simulation in electrical drives; control of electric drive systems; identification methods; control systems engineering; intelligent control of electric vehicles

Special Issue Information

Dear Colleagues,

This Special Issue, “Applied Mathematics and Intelligent Control in Electrical Engineering”, addresses researchers working in the field of mathematical methods applied in electrical engineering. The main aim of this Special Issue is to collect research articles in which the latest advances in the mathematical methods and procedures applied in electrical engineering are approached. The problem of highlighting the efficiency of the proposed solutions by applying them in the case of practical applications is also covered. This Special Issue is dedicated to a large range of scientific subjects, including mathematical modelling, numerical methods, numerical simulation of electrical machines, modelling and simulation in electrical drives, modelling and simulation in power electronics, control of electric vehicles, mathematical modelling and control of robotic systems, applied mathematics in energy systems and electrical engineering applications. Mathematical methods and procedures represent some of the most efficient solutions for improving the design of electrical machines and drives in order to obtain better performances.

Potential topics include, but are not limited to, the following areas:  

  • Mathematical modelling in electrical engineering;
  • Numerical methods in electrical engineering;
  • Numerical simulation of electrical machines;
  • Applied mathematics in electrical drive systems;
  • Artificial intelligence in electrical drive systems;
  • Modelling and simulation in electrical drives;
  • Modelling and simulation in power electronics;
  • Mathematical modelling and control of robotic systems;
  • Applied mathematics in energy systems;
  • Special electric drives;
  • Control of electric drive systems;
  • Intelligent control of electric vehicles;
  • Industrial drive applications.

Prof. Dr. Helga Silaghi
Dr. Claudiu Raul Costea
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

  • applied mathematics
  • mathematical modelling
  • numerical methods
  • numerical simulation
  • electrical engineering
  • electrical machines
  • electrical drive systems
  • artificial intelligence
  • power electronics
  • industrial applications
  • special electric drives
  • control of electric vehicles
  • energy systems
  • robotic systems

Published Papers (4 papers)

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Research

32 pages, 13207 KiB  
Article
Mathematical Modelling of Traction Equipment Parameters of Electric Cargo Trucks
by Boris V. Malozyomov, Nikita V. Martyushev, Svetlana N. Sorokova, Egor A. Efremenkov, Denis V. Valuev and Mengxu Qi
Mathematics 2024, 12(4), 577; https://doi.org/10.3390/math12040577 - 14 Feb 2024
Viewed by 585
Abstract
Electric vehicles are one of the most innovative and promising areas of the automotive industry. The efficiency of traction equipment is an important factor in the operation of an electric vehicle. In electric vehicles, the energy stored in the battery is converted into [...] Read more.
Electric vehicles are one of the most innovative and promising areas of the automotive industry. The efficiency of traction equipment is an important factor in the operation of an electric vehicle. In electric vehicles, the energy stored in the battery is converted into mechanical energy to drive the vehicle. The higher the efficiency of the battery, the less energy is lost in the conversion process, which improves the overall energy efficiency of the electric vehicle. Determining the performance characteristics of the traction battery of an electric vehicle plays an important role in the selection of the vehicle and its future operation. Using mathematical modelling, it is shown that battery capacity, charging rate, durability and efficiency are essential to ensure the comfortable and efficient operation of an electric vehicle throughout its lifetime. A mathematical model of an electric truck including a traction battery has been developed. It is shown that, with the help of the developed mathematical model, it is possible to calculate the load parameters of the battery in standardised driving cycles. The data verification is carried out by comparing the data obtained during standardised driving with the results of mathematical modelling. Full article
(This article belongs to the Special Issue Applied Mathematics and Intelligent Control in Electrical Engineering)
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23 pages, 5801 KiB  
Article
Moving Discretized Control Set Model Predictive Control with Dominant Parameter Identification Strategy for Dual Active Bridge Converters
by Tan-Quoc Duong and Sung-Jin Choi
Mathematics 2024, 12(4), 563; https://doi.org/10.3390/math12040563 - 13 Feb 2024
Viewed by 613
Abstract
The dual active bridge (DAB) converter has grown significantly as one of the most important units for energy distribution, connecting various types of renewable energy sources with the DC microgrid. For controlling the DAB converter, moving discretized control set model predictive control (MDCS-MPC) [...] Read more.
The dual active bridge (DAB) converter has grown significantly as one of the most important units for energy distribution, connecting various types of renewable energy sources with the DC microgrid. For controlling the DAB converter, moving discretized control set model predictive control (MDCS-MPC) is considered one of the most effective methods because of its advantages, such as high dynamic performance and multiobjective control. However, MDCS-MPC strongly depends on the accuracy of system parameters. Meanwhile, the system parameters can be changed due to temperature drift, manufacturing tolerance, age, and operating circumstances. As a result, the steady-state performance of the output voltage of MDCS-MPC is affected. Motivated by this, this paper proposes MDCS-MPC combined with the parameter identification technique to improve the steady-state performance of the output voltage of the DAB converter. Then, analysis of the percentage of the steady-state error of the output voltage is defined on six model parameters, and sensitivity analysis of two dominant parameters is chosen. After that, a straightforward least-squares analysis (LSA) technique is used to identify the two parameters online. The proposed method is verified through simulation in several different operating scenarios to verify its effectiveness. Full article
(This article belongs to the Special Issue Applied Mathematics and Intelligent Control in Electrical Engineering)
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28 pages, 5648 KiB  
Article
Applied Mathematics in the Numerical Modelling of the Electromagnetic Field in Reference to Drying Dielectrics in the RF Field
by Viorica Spoiala, Helga Silaghi and Dragos Spoiala
Mathematics 2024, 12(4), 526; https://doi.org/10.3390/math12040526 - 08 Feb 2024
Viewed by 470
Abstract
The processing of dielectric materials in the radio frequency field continues to be a concern in engineering. This procedure involves a rigorous analysis of the electromagnetic field based on specific numerical methods. This paper presents an original method for analysing the process of [...] Read more.
The processing of dielectric materials in the radio frequency field continues to be a concern in engineering. This procedure involves a rigorous analysis of the electromagnetic field based on specific numerical methods. This paper presents an original method for analysing the process of drying wooden boards in a radio frequency (RF) installation. The electromagnetic field and thermal field are calculated using the finite element method (FEM). The load capacity of the installation is also calculated, since the material being heated in the radio frequency heating installations is placed in a capacitor-type applicator. A specific method is created in order to solve the problem related to mass, a quantity which tends to change during the drying of the dielectric. In addition, special consideration is given to issues regarding the coupling of the electromagnetic field and the thermal field, along with aspects pertaining to mass. These are implemented numerically using a program written in the Fortran language, which takes the distribution of finite elements from the Flux2D program, the dielectric thermal module, intended only for the study of RF heating. The results obtained after running the program are satisfactory and they represent a support for future studies, especially if the movement of the dielectric is taken into account. Full article
(This article belongs to the Special Issue Applied Mathematics and Intelligent Control in Electrical Engineering)
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35 pages, 2444 KiB  
Article
Privacy Preservation Using Machine Learning in the Internet of Things
by Sherif El-Gendy, Mahmoud Said Elsayed, Anca Jurcut and Marianne A. Azer
Mathematics 2023, 11(16), 3477; https://doi.org/10.3390/math11163477 - 11 Aug 2023
Cited by 1 | Viewed by 2592
Abstract
The internet of things (IoT) has prepared the way for a highly linked world, in which everything is interconnected, and information exchange has become more easily accessible via the internet, making it feasible for various applications that enrich the quality of human life. [...] Read more.
The internet of things (IoT) has prepared the way for a highly linked world, in which everything is interconnected, and information exchange has become more easily accessible via the internet, making it feasible for various applications that enrich the quality of human life. Despite such a potential vision, users’ privacy on these IoT devices is a significant concern. IoT devices are subject to threats from hackers and malware due to the explosive expansion of IoT and its use in commerce and critical infrastructures. Malware poses a severe danger to the availability and reliability of IoT devices. If left uncontrolled, it can have profound implications, as IoT devices and smart services can collect personally identifiable information (PII) without the user’s knowledge or consent. These devices often transfer their data into the cloud, where they are stored and processed to provide the end users with specific services. However, many IoT devices do not meet the same security criteria as non-IoT devices; most used schemes do not provide privacy and anonymity to legitimate users. Because there are so many IoT devices, so much malware is produced every day, and IoT nodes have so little CPU power, so antivirus cannot shield these networks from infection. Because of this, establishing a secure and private environment can greatly benefit from having a system for detecting malware in IoT devices. In this paper, we will analyze studies that have used ML as an approach to solve IoT privacy challenges, and also investigate the advantages and drawbacks of leveraging data in ML-based IoT privacy approaches. Our focus is on using ML models for detecting malware in IoT devices, specifically spyware, ransomware, and Trojan horse malware. We propose using ML techniques as a solution for privacy attack detection and test pattern generation in the IoT. The ML model can be trained to predict behavioral architecture. We discuss our experiments and evaluation using the “MalMemAnalysis” datasets, which focus on simulating real-world privacy-related obfuscated malware. We simulate several ML algorithms to prove their capabilities in detecting malicious attacks against privacy. The experimental analysis showcases the high accuracy and effectiveness of the proposed approach in detecting obfuscated and concealed malware, outperforming state-of-the-art methods by 99.50%, and would be helpful in safeguarding an IoT network from malware. Experimental analysis and results are provided in detail. Full article
(This article belongs to the Special Issue Applied Mathematics and Intelligent Control in Electrical Engineering)
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