Applied sciences

Bulletin of the Polish Academy of Sciences Technical Sciences

Description

The Bulletin of the Polish Academy of Sciences Technical Sciences is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred:

Artificial and Computational Intelligence,
Biomedical Engineering and Biotechnology,
Civil Engineering,
Control, Informatics and Robotics,

Electronics, Telecommunication and Optoelectronics,
Mechanical and Aeronautical Engineering, Thermodynamics,
Material Science and Nanotechnology,
Power Systems and Power Electronics.

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Journal Metrics:

JCR Impact Factor 2023:	1.2
5 Year Impact Factor 2022:	1.1
CiteScore 2023:	2.8
SCImago Journal Rank (SJR) 2023:	0.282
Source Normalized Impact per Paper (SNIP) 2023:	0.573
Ministry of Education and Science:	100 points

Abbreviated title: Bull. Pol. Acad. Sci. Tech. Sci.

ISSN

ISSN 2300-1917

Editorial Board 2023-2025

Editor-in-Chief:

A. Rogalski, Military University of Technology

Honorary (Past) Editor-in Chief:

T. Kaczorek, Warsaw University of Technology

M.P. Kaźmierkowski, Warsaw University of Technology

Deputy Editor-in-Chief:

B. Błachowski, Institute of Fundamental Technological Research PAN

M. Mrozowski, Gdansk University of Technology

Board of Topical Co-editors:

Artificial and Computational Intelligence

S. Osowski, B. Sawicki and T. Leś, Warsaw University of Technology

Biomedical Engineering and Biotechnology

D. Pijanowska, Institute of Biocybernetics and Biomedical Engineering PAN

Civil Engineering

L. Czarnecki, Building Research Institute, ITB, Warsaw

Ł. Sadowski, Wroclaw University of Science and Technology

Control, Robotics and Informatics

J. Klamka and A. Babiarz, Silesian Technical University

J. Stefanowski, Poznan University of Technology

Electronics, Telecommunication and Optoelectronics

M. Mrozowski and A. Lamęcki, Gdansk University of Technology

Mechanical and Aeronautical Engineering, Thermodynamics

B. Błachowski, Institute of Fundamental Technological Research PAN

G. Zboiński, Institute of Fluid-Flow Machinery PAN and University of Warmia and Mazury in Olsztyn

Materials Science and Nanotechnology

B. Major and P. Czaja, Institute of Metallurgy and Materials Science PAN

Power Systems and Power Electronics

J. Rąbkowski and M. Jasiński, Warsaw University of Technology

International Editorial Advisory Board

R. Asthana, University of Wisconsin-Stout, Menomonie, USA

Xu Binshi, China Association of Plant Engineering, Beijing, P.R. China

F. Blaabjerg, Aalborg University, Denmark

C. Cecati, University of L’Aquila, Italy

A. Cichocki, RIKEN Institute, Tokyo, Japan

M. David, National Polytechnique de Toulouse, France

R. Ebner, Materials Centre Leoben, Leoben, Austria

E. Fornasini, University of Padova, Padova, Italy

L.G. Franquelo, University of Sevilla, Spain

M. Gad-el-Hak, Virginia Commonwealth University, Richmond, USA

M. Giersig, Free University of Berlin, Germany

D. van Gemert, Catholic University Leuven, KU Leuven, Belgium

L. Keviczky, Hungarian Academy of Sciences, Budapest, Hungary

V. Kučera, Czech Technical University in Prague, Prague, Czech Republic

R. Kennel, Technical University Munich, Germany

T.A. Kowalewski, Institute of Fundamental Technological Research PAN

E. Levi, Liverpool John Moore University, UK

G. Maier, Technical University of Milan, Milan, Italy

K.F. Man, City University of Hong Kong,

R. Maniewski, Institute of Biocybernetics and Biomedical Engineering PAN

H.A. Mang, Austrian Academy of Sciences, Vienna, Austria

H. Mihashi, Tohoku University, Aoba-ku, Sendai, Japan

S. Mindess, University of British Columbia, Vancouver, Canada

D.A. Mlynski, University of Karlsruhe, Karlsruhe, Germany

A.S. Nowak, University of Michigan, Ann Arbor, USA

K. Ohnishi, Keio University, Yokohama, Japan

A. Öberg, Linköping University, Linköping, Sweden

W. Pedrycz, University of Alberta, Canada

M. Razeghi, Northwestern University, Evanston, USA

J. Rodriguez, University of Andres Bello, Santiago, Chile

J.V. Sloten, Catholic University Leuven, Leuven, Belgium

B.M. Wilamowski, University of Auburn, Alabama, USA

A.L. Yarin, University of Illinois at Chicago, USA

Du Xiangwan, Chinese Academy of Engineering, China

J. Żurada, Department of Computer Engineering, University of Louisville, USA

Editorial Office:

Pałac Kultury i Nauki

Wydział IV Nauk Technicznych PAN

Pl. Defilad 1

PL 00-901 Warszawa

Managing Editor:

Renata Podraza, e-mail: Renata.Podraza@pan.pl

Finance:

Katarzyna Łasak, e-mail: Katarzyna.Lasak@pan.pl

The Bulletin of the Polish Academy of Sciences Technical Sciences is an open access journal with all content available with no charge in full text version.

The journal content is available under the licencse CC BY 4.0 https://creativecommons.org/licenses/by/4.0/.

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Content

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4

1 Contents 4/2024

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4

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2 Development of high-temperature permanent magnet synchronous motor for autonomous robotic navigation: a design and finite element analysis approach

Anand M , Sundaram M , Sivakumar P , Angamuthu A

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150108 | DOI: 10.24425/bpasts.2024.150108

Keywords: permanent magnet synchronous motor (PMSM) high temperature torque density power density efficiency

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Abstract

Traditional industrial robots come with prime movers, i.e. electric motors (EMs), which range from a few hundred to just a few kilo watts of power ratings. However, for autonomous robotic navigation systems, we require motors which are lightweight with the aspect of high torque and power density. This aspect is very critical when the EMs in robotic navigations are subjected to harsh high temperature survival conditions, where the sustainability of the performance metrics of the electromagnetic system of the EMs degrades with the prevailing high temperature conditions. Hence, this research work addresses and formulates the design methodology to develop a 630 W high temperature PMSM (HTPMSM) in the aspect of high torque and power density, which can be used for the autonomous robotic navigation systems under high temperature survival conditions of 200°C. Two types of rotor configurations i.e. the surface permanent magnet type (SPM) and the interior permanent magnet type (IPM) of HTPMSM are examined for its optimal electromagnetic metrics under the temperature conditions of 200◦C. The 630 W HTPMSM is designed to deliver the rated torque of 2 Nm within the volumetric & diametric constraints of DxL, which comes at 80 × 70 mm at the rated speed of 3 000 rpm with the survival temperature of 200°C and target efficiency greater than 90%. The FEM based results are validated through the hardware prototypes for both SPM and IPM types, and the results confirm the effectiveness of the proposed design methodology of HTPMSM for sustainable autonomous robotic navigation applications.

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Authors and Affiliations

Anand M

e-mail:

ORCID:

Sundaram M

Sivakumar P

e-mail:

ORCID:

Angamuthu A

Department of Electrical and Electronics Engineering, PSG College of Technology, Tamilnadu, India

3 On applications of computer algebra systems in queueing theory calculations

Marcin Ziółkowski

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150199 | DOI: 10.24425/bpasts.2024.150199

Keywords: classical queueing models queueing systems with random volume customers and sectorized memory buffer generalized L'Hospital's rule Stieltjes convolution Laplace and Laplace–Stieltjes transforms

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Abstract

In the present paper, the most important aspects of computer algebra systems applications in complicated calculations for classical queueing theory models and their novel modifications are discussed. We mainly present huge computational possibilities of Mathematica environment and effective methods of obtaining symbolic results connected with the most important performance characteristics of queueing systems. First of all, we investigate effective solutions to computational problems appearing in queueing theory such as: finding final probabilities for Markov chains with a huge number of states, calculating derivatives of complicated rational functions of one or many variables with the use of classical and generalized L’Hospital’s rules, obtaining exact formulae of Stieltjes convolutions, calculating chosen integral transforms used often in the above-mentioned theory and possible applications of generalized density function of random variables and vectors in these computations. Some exemplary calculations for practical models belonging both to classical models and their generalizations are attached as well.

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Authors and Affiliations

Marcin Ziółkowski

e-mail:

ORCID:

Institute of Information Technology, Warsaw University of Life Sciences – SGGW, Poland

4 Rotor flux and EEMF observer for interior permanent magnet synchronous machine

Deepak Vyas , Marcin Morawiec , Daniel Wachowiak

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150327 | DOI: 10.24425/bpasts.2024.150327

Keywords: field oriented-control interior permanent magnet synchronous machine model-based method sensorless control saliency-based techniques

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Abstract

In recent years, the use of the interior permanent magnet synchronous machine (IPMSM) in various applications has grown significantly due to numerous benefits. Sensors are used to achieve high efficiency and good dynamic response in IPMSM drives but due to their high cost and reduced overall size of the system, sensorless control techniques are preferred. Non-sinusoidal distribution of rotor flux and slot harmonics are present in the considered IPMSM. In this article, these problems are considered control system disturbances. With the above-mentioned problems, the classical observer structure based on (d-q) fails to estimate at low-speed ranges. This article proposes an observer structure based on a rotor flux vector in (��-��) stationary reference frame, which works using the adaptive control law to estimate speed and position, and a non-adaptive EEMF-based observer to estimate speed and position. Moreover, a comparative analysis between both observer structures at different speed ranges is also considered in this article. The effectiveness of the observer structure is validated by simulation tests and experimental tests using the sensorless control system with a field-oriented control scheme for a 3.5 kW IPMSM drive system.

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Authors and Affiliations

Deepak Vyas

e-mail:

ORCID:

Marcin Morawiec

e-mail:

ORCID:

Daniel Wachowiak

e-mail:

ORCID:

Department of Electric Drives and Energy Conversion, Faculty of Electrical and Control Engineering and EkoTech Center, Gdansk University of Technology, ul. Narutowicza 11/12, 80-233 Gdansk, Poland

5 Agent-based system for continuous control and its application to activated sludge process

Jakub Pośpiech , Witold Nocoń , Krzysztof Stebel

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150114 | DOI: 10.24425/bpasts.2024.150114

Keywords: adaptive control agent-based control control of dissolved oxygen model-based predictive control multiagent systems practical validation

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Abstract

This paper presents a concept of architecture and ontology layouts for the development of multiagent model-based predictive control systems. The presented architecture provides guidelines to simplify the development of agent-based systems and improve their maintainability. The proposed multiagent system (MAS) layout is split into multiple subsystems that include agents dedicated to performing assigned tasks. MAS implementation was prepared which can use provided algorithms and actuators and can react to changes in its environment to reach the best available control quality. An example of MAS based on the proposed architecture is shown in the application of dissolved oxygen (DO) concentration control in a laboratory-activated sludge setup with a biological reactor. For that application, MAS incorporates agent-based controllers from the boundary-based predictive controllers (BBPC) family. Presented experiments prove the flexibility, resilience, and online reconfiguration ability of the proposed multiagent system.

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Authors and Affiliations

Jakub Pośpiech

e-mail:

ORCID:

Witold Nocoń

e-mail:

ORCID:

Krzysztof Stebel

e-mail:

ORCID:

Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland

6 An adaptive energy management approach for battery-supercapacitor hybrid energy storage system

Gökhan Yüksek , Alkan Alkaya

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150203 | DOI: 10.24425/bpasts.2024.150203

Keywords: lithium batteries energy management systems renewable energy hybrid energy storage supercapacitor

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Abstract

Energy storage systems (ESS) are indispensable in daily life and have two types that can offer high energy and high power density. Hybrid energy storage systems (HESS) are obtained by combining two or more energy storage units to benefit both types. Energy management systems (EMS) are essential in ensuring the reliability, high performance, and efficiency of HESS. One of the most critical parameters for EMS is the battery state of health (SoH). Continuous monitoring of the SoH provides essential information regarding the system status, detects unusual performance degradations and enables planned maintenance, prevents system failures, helps keep efficiency at a consistently high level, and helps ensure energy security by reducing downtime. The SoH parameter depends on parameters such as depth of discharge (DoD), charge and discharge rate (C-rate), and temperature. Optimal values of these parameters directly affect the lifetime and operating performance of the battery. The proposed adaptive energy management system (AEMS) uses the SoH parameter of the battery as the control input. It provides optimal control by dynamically updating the C-rate and DoD parameters. In addition, the supercapacitor integrated into the system with filter-based power separation prevents deep discharge of the batteries. Under the proposed AEMS control, HESS has been observed to generate 6.31% more energy than a system relying solely on batteries. This beneficial relationship between supercapacitors and batteries efficiently managed by AEMS opens new possibilities for advanced energy management in applications ranging from electric vehicles to renewable energy storage systems.

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Authors and Affiliations

Gökhan Yüksek

e-mail:

ORCID:

Alkan Alkaya

e-mail:

ORCID:

Department of Electrical and Electronics Engineering, Faculty of Engineering, Mersin University, Ciftlikkoy 33100, Mersin, Turkey

7 Comprehensive online estimation of object signals for a control system with an adaptive approach and incomplete measurements

Tadeusz Kwater , Przemysław Hawro , Paweł Krutys , Marek Gołębiowski , Grzegorz Drałus

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150111 | DOI: 10.24425/bpasts.2024.150111

Keywords: online estimation and control nonlinear differential equations adaptive gain modification measurements window random lack of measurements

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Abstract

This paper presents the novel estimation algorithm that generates all signals of an object described by nonlinear ordinary differential equations based only on easy-to-implement measurements. Unmeasured signals are estimated by using an adaptive approach. For this purpose, a filtering equation with a continuously modified gain vector is used. Its value is determined by an incremental method, and the amount of correction depends on the current difference between the generated signal and its measured counterpart. In addition, the study takes into account the aging process of measurements and their random absence. The application of the proposed approach can be realized for any objects with a suitable mathematical description. A biochemically polluted river with an appropriate transformation of the notation of partial differential equations was chosen as an object. The results of numerical experiments are promising, and the process of obtaining them involves little computational necessity, so the approach is aimed at the needs of control implemented online.

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Authors and Affiliations

Tadeusz Kwater

e-mail:

ORCID:

Przemysław Hawro

e-mail:

ORCID:

Paweł Krutys

e-mail:

ORCID:

Marek Gołębiowski

e-mail:

ORCID:

Grzegorz Drałus

e-mail:

ORCID:

Faculty of Technical Engineering, State University of Applied Sciences in Jaroslaw, Poland
Faculty of Electrical and Computer Engineering, Rzeszow University of Technology, Poland

8 Selection of reference model for adaptive PMSM drive based on MRAC approach

Rafał Szczepański , Tomasz Tarczewski , Lech Grzesiak

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e149177 | DOI: 10.24425/bpasts.2024.149177

Keywords: PMSM drive model-reference adaptive control Widrow-Hoff rule Adaptation Procedure for Optimization Algorithms

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Abstract

The selection of a reference model (RM) for a Model-Reference Adaptive Control is one of the most important aspects of the synthesis process of the adaptive control system. In this paper, the four different implementations of RM are developed and investigated in an adaptive PMSM drive with variable moment of inertia. Adaptation mechanisms are based on the Widrow-Hoff rule (W-H) and the Adaptation Procedure for Optimization Algorithms (APOA). Inadequate order or inaccurate approximation of RM for the W-H rule may provide poor behavior and oscillations. The results prove that APOA is robust against an improper selection of RM and provides high-performance PMSM drive operation.

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Authors and Affiliations

Rafał Szczepański

e-mail:

ORCID:

Tomasz Tarczewski

e-mail:

ORCID:

Lech Grzesiak

e-mail:

ORCID:

Department of Automatics and Measurement Systems, Nicolaus Copernicus University, Grudziadzka 5, 87-100 Torun, Poland
Institute of Control and Industrial Electronics, Warsaw University of Technology, Koszykowa 75, 00-662 Warsaw, Poland

9 The discrete, fractional order model of a two-dimensional temperature field using Grünwald-Letnikov definition

Krzysztof Oprzędkiewicz

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150332 | DOI: 10.24425/bpasts.2024.150332

Keywords: fractional order systems heat transfer equation fractional order state equation Grünwald-Letnikov definition practical stability accuracy convergence thermal camera

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Abstract

In the paper a new, fractional order, discrete model of a two-dimensional temperature field is addressed. The proposed model uses Grünwald-Letnikov definition of the fractional operator. Such a model has not been proposed yet. Elementary properties of the model: practical stability, accuracy and convergence are analysed. Analytical conditions of stability and convergence are proposed and they allow to estimate the orders of the model. Theoretical considerations are validated using exprimental data obtained with the use of a thermal imaging camera. Results of analysis supported by experiments point that the proposed model assures good accuracy and convergence for low order and relatively short memory length.

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Authors and Affiliations

Krzysztof Oprzędkiewicz

e-mail:

ORCID:

AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Kraków, Poland

10 An analysis of the influence of famous people’s posts on social networks on the cryptocurrency exchange rate

Sergii Telenyk , Grzegorz Nowakowski , Olena Gavrilenko , Mykhailo Miahkyi , Olena Khalus

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150117 | DOI: 10.24425/bpasts.2024.150117

Keywords: cryptocurrency exchange rate forecasting algorithms posts on social networks methods of statistical analysis information technology of intellectual analysis

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Abstract

In this work, the level of influence of the posts published by famous people on social networks on the formation of the cryptocurrency exchange rate is investigated. Celebrities who are familiar with the financial industry, especially with the cryptocurrency market, or are somehow connected to a certain cryptocurrency, such as Elon Musk with Dogecoin, are chosen as experts whose influence through social media posts on cryptocurrency rates is examined. This research is conducted based on statistical analysis. Real cryptocurrency exchange rate forecasts for the selected time period and predicted ones for the same period, obtained using three algorithms, are utilized as a dataset. This paper uses methods such as statistical hypotheses regarding the significance of Spearman’s rank correlation coefficient and Pearson’s correlation. It is confirmed that the posts by famous people on social networks significantly affect the exchange rates of cryptocurrencies.

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Authors and Affiliations

Sergii Telenyk

e-mail:

ORCID:

Grzegorz Nowakowski

e-mail:

ORCID:

Olena Gavrilenko

e-mail:

ORCID:

Mykhailo Miahkyi

e-mail:

ORCID:

Olena Khalus

e-mail:

ORCID:

Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155 Cracow, Poland
National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute,” Prosp. Peremohy 37, Kyiv, Ukraine

11 Enhancing nano grid connectivity through the AI-based cloud computing platform and integrating recommender systems with deep learning architectures for link prediction

Nagaraju Sonti , Rukmini M S S , Venkatappa Reddy P

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150113 | DOI: 10.24425/bpasts.2024.150113

Keywords: cloud computing link prediction cloud recommendation nano-grid application deep learning

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Abstract

Cloud computing has become ubiquitous in modern society, facilitating various applications ranging from essential services to online entertainment. To ensure that quality of service (QoS) standards are met, cloud frameworks must be capable of adapting to the changing demands of users, reflecting the societal trend of collaboration and dependence on automated processing systems. This research introduces an innovative approach for link prediction and user cloud recommendation, leveraging nano-grid applications and deep learning techniques within a cloud computing framework. Heuristic graph convolutional networks predict data transmission links in cloud networks. The trust-based hybrid decision matrix algorithm is then employed to schedule links based on user recommendations. The proposed model and several baselines are evaluated using real-world networks and synthetic data sets. The experimental analysis includes QoS, mean average precision, root mean square error, precision, normalized square error, and sensitivity metrics. The proposed technique achieves QoS of 73%, mean average precision of 59%, root mean square error of 73%, precision of 76%, normalized square error of 86%, and sensitivity of 93%. The findings suggest that integrating nano-grid and deep learning techniques can effectively enhance the QoS of cloud computing frameworks.

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Authors and Affiliations

Nagaraju Sonti

e-mail:

ORCID:

Rukmini M S S

Venkatappa Reddy P

Department of ECE, Vignan’s Foundation for Science, Technology & Research, Vadlamudi, Andhra Pradesh, India
Azista Industries Pvt Ltd, Advanced Pixel Research Intelligence Lab, Hyderabad, Telangana, India

12 A system dedicated to Polish automatic speech recognition – overview of solutions

Karolina Pondel-Sycz , Piotr Bilski

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e149818 | DOI: 10.24425/bpasts.2024.149818

Keywords: automatic speech recognition deep neural networks transformer conformer

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Abstract

The paper presents the analysis of modern Artificial Intelligence algorithms for the automated system supporting human beings during their conversation in Polish language. Their task is to perform Automatic Speech Recognition (ASR) and process it further, for instance fill the computer-based form or perform the Natural Language Processing (NLP) to assign the conversation to one of predefined categories. The State-of-the-Art review is required to select the optimal set of tools to process speech in the difficult conditions, which degrade accuracy of ASR. The paper presents the top-level architecture of the system applicable for the task. Characteristics of Polish language are discussed. Next, existing ASR solutions and architectures with the End-To-End (E2E) deep neural network (DNN) based ASR models are presented in detail. Differences between Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN) and Transformers in the context of ASR technology are also discussed.

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Authors and Affiliations

Karolina Pondel-Sycz

Piotr Bilski

e-mail:

ORCID:

The Faculty of Electronics and Information Technology on Warsaw University of Technology, Nowowiejska 15/19 Av., 00-665 Warsaw, Poland

13 High-quality synthesized face sketch using generative reference prior

Sami Mahfoud , Messaoud Bengherabi , Abdelhamid Daamouche , Elhocine Boutellaa , Abdenour Hadid

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150109 | DOI: 10.24425/bpasts.2024.150109

Keywords: generative adversarial networks face sketch synthesis generative reference prior

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Abstract

Face sketch synthesis (FSS) is considered an image-to-image translation problem, where a face sketch is generated from an input face photo. FSS plays a vital role in video/image surveillance-based law enforcement. In this paper, motivated by the recent success of generative adversarial networks (GAN), we consider conditional GAN (cGAN) to approach the problem of face sketch synthesis. However, despite the powerful cGAN model ability to generate fine textures, low-quality inputs characterized by the facial sketches drawn by artists cannot offer realistic and faithful details and have unknown degradation due to the drawing process, while high-quality references are inaccessible or even nonexistent. In this context, we propose an approach based on generative reference prior (GRP) to improve the synthesized face sketch perception. Our proposed model, which we call cGAN-GRP, leverages diverse and rich priors encapsulated in a pre-trained face GAN for generating highquality facial sketch synthesis. Extensive experiments on publicly available face databases using facial sketch recognition rate and image quality assessment metrics as criteria demonstrate the effectiveness of our proposed model compared to several state-of-the-art methods.

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Authors and Affiliations

Sami Mahfoud

1 3

e-mail:

ORCID:

Messaoud Bengherabi

e-mail:

ORCID:

Abdelhamid Daamouche

e-mail:

ORCID:

Elhocine Boutellaa

e-mail:

ORCID:

Abdenour Hadid

e-mail:

ORCID:

University of Algiers 3, Faculty of Economic, Commercial and Management Sciences, Laboratory of Governance and Modernizationof Public Management, 02 Ahmed Ouaked Street Dely Ibrahim 16302, Algiers, Algeria
Sorbonne University Abu Dhabi, Sorbonne Center for Artificial Intelligence, Abu Dhabi, UAE
Center for Development of Advanced Technologies, Telecom Division, P.O. Box 17 Baba-Hassen 16303, Algiers, Algeria
SUniversity M’Hamed Bougara of Boumerdes, Institute of Electrical and Electronic Engineering, Laboratory of Signals and Systems,Boumerdes, 35000, Algeria

14 Interval type 2 fuzzy PI-enhanced state space model for battery management in battery electric utility vehicles operating in an indoor logistics environment

Arun Kumar R. , Sankar Ganesh R.

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150330 | DOI: 10.24425/bpasts.2024.150330

Keywords: fuzzy network battery electric utility vehicle state-space battery management systems interval type 2 fuzzy

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Abstract

This research presents an advanced control approach for battery management in battery electric utility vehicles (BEUV) operating in indoor logistics environments. The proposed approach utilizes a combination of proportional-integral (PI), fuzzy PI, and interval type 2 fuzzy PI (IT2fuzzyPI) control structures to augment the state space model for battery management. The state space model incorporates the voltage and current of each battery cell as state variables and considers the current demand from the electric motor as an input. By integrating fuzzy logic with PI control and considering uncertainty, the IT2fuzzyPI structure offers improved control recital and system robustness in the occurrence of nonlinearities, uncertainties, and turbulences. The outcomes of the simulation validate the effectiveness of the proposed scheme in managing the battery pack system’s state of charge and controlling the rates of charging and discharging. The IT2fuzzyPI control significantly improves the overall proficiency and longevity of the battery system, making it suitable for battery electric utility vehicles in logistics environments. This research contributes to the field of battery management systems, providing a valuable tool for designing and evaluating high-performance electric vehicles with enhanced control capabilities.

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Authors and Affiliations

Arun Kumar R.

Sankar Ganesh R.

Electrical and Electronics Engineering, V.S.B. Engineering College, Karur, Tamil Nadu, India
Electrical and Electronics Engineering, K.S.R. College of Engineering, Tiruchengode, Tamil Nadu, India

15 Multi-unmanned aerial vehicle odor source location based on improved artificial fish swarm algorithm

Tao Ding , Wenhan Zhong , Yufeng Cai

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150329 | DOI: 10.24425/bpasts.2024.150329

Keywords: odor source location artificial fish swarm algorithm unmanned aerial vehicle active olfaction

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Abstract

Odor source location technology has important application value in environmental monitoring, safety emergency and search and rescue operations. For example, it can be used in post-disaster search and rescue, detection of hazardous gas leakage, and fire source detection. Existing odor source location methods have problems such as low search efficiency, inability to adapt to complex environments, and inaccurate odor source location. In this study, based on unmanned aerial vehicle technology and using swarm intelligence optimization algorithm, an improved artificial fish swarm algorithm (IAFSA) is proposed by combining curiosity in psychology on the basis of retaining the good optimization performance of the artificial fish swarm algorithm. The algorithm quantifies the curiosity of artificial fish searching high-concentration areas through a model, dynamically adjusts the artificial fish field of vision and step length with the calculated curiosity factor, and avoids the oscillation phenomenon in the later stage of the algorithm. Simulation results show that the IAFSA has a higher success rate and smaller location error. Finally, odor source location experiments were carried out in an indoor physical environment, the feasibility of the odor source location method proposed in this study is verified in actual scenarios.

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Authors and Affiliations

Tao Ding

e-mail:

ORCID:

Wenhan Zhong

Yufeng Cai

China Jiliang University, Hangzhou, China
Zhejiang Light Industrial Products Inspection and Research Institute, Hangzhou, China

16 Enhancing MPPT in partially shaded PV modules: a novel approach using adaptive reinforcement learning with neural network architecture

Leelavathi M. , Suresh Kumar V.

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150112 | DOI: 10.24425/bpasts.2024.150112

Keywords: machine learning maximum power point tracking partial shading patterns photovoltaic modules renewable energy

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Abstract

The occurrence of partial shading in solar power systems presents a substantial challenge with widespread implications, sparking extensive research, notably in the field of maximum power point tracking (MPPT). This study emphasizes the critical process of accurately tracking the maximum power points with the characteristic curves of photovoltaic (PV) modules under real-time, diverse partial shading patterns. It explores the various stages of the tracking process and the methodologies employed for optimization. While conventional methods show effectiveness, they often fall short in swiftly and accurately tracking maximum power points with minimal errors. To address this limitation, this research introduces a novel machine learning approach known as adaptive reinforcement learning with neural network architecture (ARL-NNA) for MPPT. The results obtained from ARL-NNA are compared with existing algorithms using the same experimental data. Furthermore, the outcomes are validated through different factors and processing time measurements. The findings conclusively demonstrate the efficacy and superiority of the proposed algorithm in effectively tracking maximum power points in PV characteristic curves, providing a promising solution for optimizing solar energy generation in partial shading patterns. This study significantly impacts various realms of electrical engineering including power engineering, power electronics, industrial electronics, solid-state electronics, energy technology, and other related field of engineering and technology.

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Authors and Affiliations

Leelavathi M.

Suresh Kumar V.

Thiagarajar College of Engineering, Madurai, Tamil Nadu, India

17 Assessment of safety of masonry buildings near deep excavations: impact of excavations on structures

Radosław Jasiński , Izabela Skrzypczak , Agnieszka Leśniak , Eduardo Natividade

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e149817 | DOI: 10.24425/bpasts.2024.149817

Keywords: structure safety deep excavations excavation impact on masonry structures AHP ULS SLS

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Abstract

The knowledge of the impact and the load-bearing capacity of unstrengthened/strengthened structures is a crucial source of information about the safety of masonry buildings near deep excavations, especially in dense urban areas. Incorrect calculations made for such designs can seriously affect not only an analyzed object but also the adjacent buildings. The safety of masonry buildings can be determined by many factors that are closely related to the hazards presented during the performance of deep excavations. These factors are at first identified and then prioritized. The AHP process in the multi-criteria analysis was used to support the decision-making process related to the verification of factors affecting the safety assessment of masonry buildings in the area of deep excavations. The proper design of building structures, including the verification of the structure strengthening near deep excavations, was found to be the most significant factor determining the safety of such buildings. The methodology for proceeding with the verification of ultimate (ULS) and serviceability (SLS) limit states in accordance with the literature data, current regulations, such as Eurocode 6 and other design standards, and the know-how of the authors, described in this paper was the next stage of the discussed analysis.

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Authors and Affiliations

Radosław Jasiński

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ORCID:

Izabela Skrzypczak

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ORCID:

Agnieszka Leśniak

e-mail:

ORCID:

Eduardo Natividade

e-mail:

ORCID:

Faculty of Civil Engineering, Silesian University of Technology, ul. Akademicka 5, 44-100 Gliwice, Poland
2 Faculty of Civil and Environmental Engineering and Architecture, Rzeszow University of Technology, Al. Powstanców Warszawy 12, ´35-959 Rzeszów, Poland
Faculty of Civil Engineering, Krakow University of Technology, Al. Warszawska 24, 31-155 Kraków, Poland
Instituto Politecnico de Coimbra, Instituto Superior de Engenharia de Coimbra, Rua Pedro Nunes, Quinta da Nora,3030-199 COIMBRA, Portuga

18 Analysis of the influence of karst cave parameters on surface settlement in TBM tunnelling

Bichang Dong , Tao Yang , Binbin Ju , Zhongying Qu , Chao Yi

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150110 | DOI: 10.24425/bpasts.2024.150110

Keywords: karst cave TBM tunnelling surface subsidence grey correlation analysis MIDAS

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Abstract

In order to study the influence of multiple karst cave factors on surface settlement during tunnel boring machine (referred to TBM hereinafter) tunnelling, a three-dimensional numerical model is built by taking a subway project as an example and combining it with MIDAS GTS NX finite element software. Secondly, the influence of the radius, height, angle, vertical net distance and horizontal distance of the karst cave on maximum surface settlement is studied and sorted under the two working conditions of treatment and lack of treatment using the gray correlation analysis method. Additionally, a multi-factor numerical model of the untreated karst cave is established. Finally, based on the preceding research, a multi-factor prediction model for maximum surface settlement is proposed and tested. The results reveal that when the karst cave is not treated, the radius and height of the karst cave have a significant effect on maximum surface settlement. Following cave treatment however, the influence of the cave parameters on maximum settlement of the surface is greatly reduced. The calculating model created in this study offers excellent prediction accuracy and good adaptability.

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Authors and Affiliations

Bichang Dong

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ORCID:

Tao Yang

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ORCID:

Binbin Ju

Zhongying Qu

Chao Yi

School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan Hubei 430063, China
Wuhan Municipal Engineering Design and Research Institute Co., Ltd. Wuhan Hubei 430063, China
China Railway Seven Bureau Group Fourth Engineering Co., Ltd. Wuhan 430200, China

19 Occlusion-aware collision avoidance trajectory planning with potential collision risk assessment for autonomous vehicle

Yubin Qian , Chengzhi Deng , Jiejie Xu , Xianguo Qu , Zhenyu Song

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e149819 | DOI: 10.24425/bpasts.2024.149819

Keywords: occlusion scenarios active collision risk assessment trajectory planning

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Abstract

Motion planning for autonomous vehicles relies heavily on perception and prediction results to find a safe, collision-free local trajectory that adheres to traffic rules. However, vehicle perception is frequently limited by occlusion, and the generation of safe local trajectories with restricted perception poses a significant challenge in the field of motion planning. This paper introduces a collision avoidance trajectory planning algorithm that considers potential collision risks, within a hierarchical framework of sampling and optimization. The primary objective of this work is to generate trajectories that are safer and align better with human driver behavior while considering potential collision risks in occluded regions. Specifically, in occlusion scenarios, the state space is discretized, and a dynamic programming algorithm is used for a sampling-based search to obtain initial trajectories. Additionally, the concept of a driving risk field is introduced to describe potential collision risk elements within the human-vehicle-road environment. By drawing inspiration from graph search algorithms, potential collision risk areas are accurately described, and a cost function is proposed for evaluating potential risks in occluded regions. Drivers typically exhibit conservative and cautious driving behavior when navigating through occluded regions. The proposed algorithm not only prioritizes driving safety but also considers driving efficiency, thereby reducing the vehicle’s conservativeness when passing through occlusions. The research results demonstrate that the ego vehicle can actively avoid blind spots and tends to move away from occluded regions, aligning more closely with human driver behavior.

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Authors and Affiliations

Yubin Qian

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ORCID:

Chengzhi Deng

e-mail:

ORCID:

Jiejie Xu

Xianguo Qu

Zhenyu Song

School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, China
Defective Product Administrative Center, State Administration for Market Regulation, Beijing, China

20 Numerical simulation of the influencing factors of array jet shock cooling

Nianyong Zhou , Youxin Zhou , Yingjie Zhao , Qingguo Bao , Guanghua Tang , Wenyu Lv

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150200 | DOI: 10.24425/bpasts.2024.150200

Keywords: array jet enhanced heat exchange numerical simulation

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Abstract

Array jet impingement cooling is a significant technology of enhanced heat dissipation which is fit for high heat flux flow with large area. It is gradually applied to the cooling of electronic devices. However, The research on the nozzle array mode and the uniformity of the cooling surface still has deficiencies. Therefore, the influence of heat flux, inlet temperature, jet height, array mode, and diversion structure on jet impingement cooling performance and temperature distribution uniformity is analyzed through numerical calculation. The results show that the heat transfer coefficient of jet impingement cooling increases linearly with the increment of heat flux and inlet temperature. With the increment of the ratio of jet height to nozzle diameter (H/d), the heat transfer coefficient increases first and then decreases, that is, there is an optimal H/d, which makes the heat transfer performance of the array jet impact cooling best. The temperature uniformity of array jet impact cooling is greatly affected by array mode. The improvement effect of nozzle array mode on temperature uniformity is ranked as sequential >staggered >shield >elliptical array. The overall temperature uniformity and heat transfer coefficient are increased by 5.88% and 7.29% compared with the elliptical array. The heat transfer performance can be further improved by adding a flow channel to the in-line array layout, in which the heat transfer coefficient is increased by 6.53% and the overall temperature uniformity is increased by 1.45%.

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Authors and Affiliations

Nianyong Zhou

e-mail:

ORCID:

Youxin Zhou

Yingjie Zhao

Qingguo Bao

Guanghua Tang

Wenyu Lv

College of Urban Construction, Changzhou University, Changzhou, China

21 Modeling, analysis, and techno-economic assessment of a clean power conversion system with green hydrogen production

Toufik Sebbagh

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 4 | e150115 | DOI: 10.24425/bpasts.2024.150115

Keywords: green hydrogen PV systems electrolysis energy conversion techno-economic optimization

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Abstract

The power sector confronts a crucial challenge in identifying sustainable and environmentally friendly energy carriers, with hydrogen emerging as a promising solution. This paper focuses on the modeling, analysis, and techno-economic evaluation of an independent photovoltaic (PV) system. The system is specifically designed to power industrial loads while simultaneously producing green hydrogen through water electrolysis. The emphasis is on utilizing renewable sources to generate hydrogen, particularly for fueling hydrogen-based cars. The study, conducted in Skikda, Algeria, involves a case study with thirty-two cars, each equipped with a 5 kg hydrogen storage tank. Employing an integrated approach that incorporates modeling, simulation, and optimization, the techno-economic analysis indicates that the proposed system provides a competitive, cost-effective, and environmentally friendly solution, with a rate of 0.239 $/kWh. The examined standalone PV system yields 24.5 GWh/year of electrical energy and produces 7584 kg/year of hydrogen. The findings highlight the potential of the proposed system to address the challenges in the power sector, offering a sustainable and efficient solution for both electricity generation and hydrogen production.

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Authors and Affiliations

Toufik Sebbagh

e-mail:

ORCID:

LGMM Laboratory, University of Skikda, PoBox 26, Road of ElHadaiek, Skikda, 21000, Algeria

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