Applied sciences

Bulletin of the Polish Academy of Sciences Technical Sciences

Content

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 6

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Abstract

Traffic accident prediction is a crucial component of an intelligent traffic system, which is important to maintain citizen safety and decrease economic losses. Current methods for traffic accident prediction based on deep learning fail to consider the driving mechanisms of traffic accidents, so a novel traffic accident prediction method based on multi-view spatial-temporal learning is proposed, which represents the driving mechanism of traffic accidents from multiple views. Firstly, for the urban regions divided by grids, a new augmentation was designed to augment the spatial semantic information of regions through learnable semantic embedding, then deformable convolutional networks with non-fixed convolution kernels are used to learn dynamic spatial dependencies between regions and gated recurrent units are used to learn temporal dependencies, which can capture dynamic spatial-temporal evolution patterns of traffic accidents. Secondly, long short-term memory is employed to learn the traffic flow breakdown from the flow difference of adjacent time steps in each region to recognize the traffic accident precursor in the risk environment. Thirdly, accident patterns in different regions are learned from historical traffic flow to determine whether the flow is the dominant factor and capture the spatial heterogeneity of traffic accidents. Finally, the above features are fused for accident prediction at the regional level. Experiments are conducted on two real datasets, and the experimental results show that the proposed method outperforms eight benchmark methods.
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Authors and Affiliations

Jian Feng
1
ORCID: ORCID
Tian Liu
1
ORCID: ORCID
Yuqiang Qiao
2

  1. College of Computer Science & Technology, Xi’an University of Science and Technology, Xi’an 710000, China
  2. Shaanxi Branch, China United Network Communications Group Co., Ltd., Xi’an 710000, China
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Abstract

The main causes of aviation accidents in recent years are mostly related to pilot operational errors and pilot operational characteristics directly reflect flight quality. Hence, flight quality and flight safety are inseparable. Improving the assessment method of flight quality is of great significance for building a competency-based and evidence-based flight training system as well as enhancing flight safety. However, the problem is that some of the existing research is one-sided, and the assessment accuracy is not high. We propose a flight quality assessment method based on KOA-CNN-GRU-self-attention for the whole flight phase to accurately assess the flight quality and to improve and supplement the existing system. Firstly, the QAR data of the whole flight phase is selected and divided into three data sets according to the three indexes of operational smoothness, accuracy, and promptness, which are respectively substituted into the PCA comprehensive evaluation model to assess flight quality. Then, the evaluation results are labelled with the rating as the input of CNN-GRU-self-attention, and the parameters are optimized using KOA. Finally, the evaluation of flight quality for the three indexes was achieved by training the KOA-CNN-GRU-self-attention model. Thet est results show that the accuracy of operational smoothness, accuracy, and promptness reaches 98.73%, 95.07%, and 97.18%, respectively, and the assessment outcome is better and higher than the existing model. The model is also compared and analyzed with three base models CNN, QDA, XGBoost, and three fusion models CNN-self-attention, GRU-self-attention, CNN-GRU-self-attention, which show overall better results in accuracy, recall, precision, and F1-Score.
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Authors and Affiliations

Tianyi Wu
1
Zichun Lin
2
Jianan Huang
1
Yuxi Ding
1
Ansaierding Maihemuti
1
Xiaowei Xu
1

  1. School of Automobile and Traffic Engineering, Wuhan University of Science and Technology, Wuhan 430065, China
  2. Faculty of Materials, Wuhan University of Science and Technology, Wuhan 430081, China
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Abstract

In modern drive systems, the aim is to ensure their operational safety. Damage can occur not only to the components of the motor itself but also to the power electronic devices included in the frequency converter and sensors in the measurement circuit. Critical damage to the electric drive that makes its further exploitation impossible can be prevented by using fault-tolerant control (FTC) algorithms. These algorithms are very often combined with diagnostic methods that assess the degree and type of damage. In this paper, a fault classification algorithm using an artificial neural network (ANN) is analyzed for stator phase current sensors in AC motor drives. The authors confirm that the investigated classification algorithm works equally well on two different AC motors without the need for significant modifications, such as retraining the neural network when transferring the algorithm to another object. The method uses a stator current estimator to replace faulty sensor measurements in a vector control structure. The measured and estimated currents are then subjected to a classification process using a multilayer perceptron (MLP), which has the advantage of small structure size as compared to deep learning structures. The uniqueness of the method lies in the use of data in the training set that are not dependent on the parameters of a specific motor. Four types of current sensor faults were studied, namely total signal loss, gain error, offset and signal saturation. Simulations were performed in a MATLAB/SIMULINK environment for drive systems with an induction motor (IM) and a permanent magnet synchronous motor (PMSM). The results show that the algorithm correctly evaluates the type of damage in more than 99.6% of cases regardless of the type of motor. Therefore, the results presented here may help to develop universal diagnostic methods that will work on a wide variety of motors.
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Authors and Affiliations

Krystian Teler
1
ORCID: ORCID
Maciej Skowron
1
ORCID: ORCID
Teresa Orłowska-Kowalska
1
ORCID: ORCID

  1. Wroclaw University of Science and Technology, Department of Electrical Machines, Drives and Measurements, Wrocław, Poland
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Abstract

This study introduces a two-step reinforcement learning (RL) strategy tailored for "The Lord of the Rings: The Card Game", a complex multistage strategy card game. The research diverges from conventional RL methods by adopting a phased learning approach, beginning with a foundational learning step in a simplified version of the game and subsequently progressing to the complete, intricate game environment. This methodology notably enhances the AI agent’s adaptability and performance in the face of the unpredictable and challenging nature of the game. The paper also explores a multi-phase system where distinct RL agents are employed for various decision-making phases of the game. This approach has demonstrated remarkable improvement, with the RL agents achieving a winrate of 78.5 % at the highest difficulty level.
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Authors and Affiliations

Konrad Godlewski
1
Bartosz Sawicki
1
ORCID: ORCID

  1. Warsaw University of Technology, Poland
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Abstract

The paper proposes a deep-learning approach to the recognition of melanoma images. It relies on the application of many different architectures of CNN combined in the form of an ensemble. The units of the highest efficiency are selected as the potential members of the ensemble. Different methods of arrangement of the ensemble members are studied and the limited number of the best units are included in the final form of an ensemble. The results of numerical experiments performed on the ISIC2017 database have shown the very high efficiency of the proposed ensemble system. The best accuracy in recognition of melanoma from nonmelanoma cases obtained by the ensemble was 96.54% at AUC = 0.9909, sensitivity 94.71%, and specificity 97.67%. These values are superior to the results presented for this ISIC2017 database.
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Authors and Affiliations

Fabian Gil
1
Stanisław Osowski
2
ORCID: ORCID

  1. Warsaw University of Technology, Warsaw, Poland
  2. Military University of Technology, Warsaw, Poland
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Abstract

This study introduces an innovative algorithm that leverages terrestrial laser scanning (TLS) and the fuzzy analytic hierarchy process (FAHP) for the optimization of building repair methodologies. Focusing on multi-criteria decision-making (MCDM), itshowcases a methodology for evaluating and selecting the most effective repair strategy for building elements, balancing various conflicting criteria. The research applies TLS for rapid and accurate geometric data acquisition of engineering structures, demonstrating its utility in structural diagnostics and technical condition assessment. A case study on a single-family residential building, experiencing floor deformation in a principal ground-floor room, illustrates the practical application. Maximum deflection and floor deflection distribution were measured using TLS. Utilizing FAHP for analysis, the decision model identifies the most advantageous repair method from a building user’s perspective. This approach not only provides a systematic framework for selecting optimal repair solutions but also highlights the potential of integrating advanced scanning technologies and decision-support methods in the field of building materials and structural engineering.
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Authors and Affiliations

Zbigniew Walczak
1
Barbara Ksit
2
ORCID: ORCID
Anna Szymczak-Graczyk
1

  1. Department of Construction and Geoengineering, Faculty of Environmental and Mechanical Engineering, Poznan University of Life Sciences,Pi ˛atkowska 94E, 60-649 Poznan, Poland
  2. Institute of Building Engineering, Faculty of Civil and Transport Engineering, Poznan University of Technology,Piotrowo 5, 60-965 Poznan, Poland
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Abstract

Gas turbines are widely used for power generation globally, and their greenhouse gas emissions have increasingly drawn public attention. Compliance with environmental regulations necessitates sophisticated emission measurement techniques and tools. Traditional sensors used for monitoring emission gases can provide inaccurate data due to malfunction or miscalibration. Accurate estimation of gas turbine emissions, such as particulate matter, carbon monoxide, and nitrogen oxides, is crucial for assessing the environmental impact of industrial activities and power generation. This study used five different machine learning models to predict emissions from gas turbines, including AdaBoost, XGBoost, k-nearest neighbour, and linear and random forest models. Random search optimization was used to set the regression parameters. The findings indicate that the AdaBoost regressor model provides superior prediction accuracy for emissions compared to other models, with an accuracy of 99.97% and a mean squared error of 2.17 on training data. This research offers a practical modelling approach for forecasting gas turbine emissions, contributing to the reduction of air pollution in industrial applications.
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Authors and Affiliations

Emrah Aslan
1
ORCID: ORCID

  1. Dicle University, Silvan Vocational School, Diyarbakır, Turkey
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Abstract

Nowadays, cold-formed steel (CFS) has become widely used in the field of lightweight structures. In 2016, the Budapest University of Technology and Economics initiated a research study on a unique structural system using CFS and utilized ultra-lightweight concrete as an encasing material. This material serves as continuous bracing that improves CFS element resistance, stability behavior and performance, while also manifesting heat insulation capabilities, thus helping achieve sustainability goals. This paper is considered a continuation of previous research conducted by the authors. An experimental investigation was carried out on encased CFS columns subjected to eccentric loading. A total of fourteen stub-columns, with two distinct thicknesses, were subjected to various loading conditions for testing. The test results showed that local failure controlled the behavior of all the tested elements. The reduction in capacity resulting from eccentricity with respect to centric resistance varied between 20% and 52%, depending on the load position applied and on the core thickness of the tested steel elements. Moreover, the test outcomes were compared to the Eurocode analytical solution of pure steel elements. The overall load increment ranged from 46% to 18%, with a more noticeable bracing impact observed in the case of slender elements. Material tests also supplement the results.
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Authors and Affiliations

Ahmed Alabedi
1
ORCID: ORCID
Péter Hegyi
1

  1. Department of Structural Engineering, Budapest University of Technology and Economics, Hungary
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Abstract

The basic measuring element of vibrating-wire strain gauges is a steel piano wire, functioning in the elastic range. This element is constantly under tension. Therefore, its material gradually deforms permanently. This deformation causes its stress to relax. This relaxation results in measurement errors of the strain gauges. This error, as demonstrated by both in situ and laboratory tests, can reach values of even several percent of the strain gauge measuring range (FSR) over periods of 10 years. Therefore, a concept of a differential strain gauge was proposed, for the construction of which two measuring wires would be used. Changing the input value of the strain gauge, i.e. a displacement of one of its anchors in relation to the other one would cause one wire to lengthen while the other wire shortened identically. The measured displacement would be calculated based on the difference in the frequency of the wire vibrations. In this way, the influence of the simultaneous relaxation of the wires on the measurement result would be greatly reduced. Based on this concept, a prototype differential strain gauge for measuring concrete deformation was realized. In addition to two wires, it also contains two electromagnets, placed together with the wires in a common body-housing. After the strain gauge was assembled, its first tests were carried out under laboratory conditions.
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Authors and Affiliations

Adam Kanciruk
1
ORCID: ORCID
Elżbieta Matus
1
ORCID: ORCID

  1. Strata Mechanics Research Institute Polish Academy of Sciences, Poland
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Abstract

Sealing is an important prerequisite for downhole heater work. This paper proposes a combination of soft and hard, and welding sealing programs, which were analysed using theoretical calculations, numerical simulation, and in-situ testing. The results show that 316 stainless steel can meet the stuffing seal requirements. The first stuffing leads to compression and gradual reduction, while the second stuffing essentially does not deform. Stuffing deformation fills the gap in the sealing hole, creating a sealing layer. The compression rate is 0.43%, 8.45%, and 12.64%, indicating that the locking stress should be more than 2000 N. The temperature at the weld is heated by heat conduction and distributed in a concentric circle. Thermal stress will influence the 50 mm barrier, but the 100 mm boundary will be mostly unaffected. Actually, the thermal stress that destroys the weld seal may be reduced by adjusting the heater output or raising the gas injection rate. During the beginning of the in-situ heat injection, the temperature of the heating rods rises simultaneously with the outlet temperature. Consequently, both show opposite tendencies. The heat generated by the heating rods will cause the injected gas to be preheated in advance.
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Authors and Affiliations

Qiang Li
1 2
ORCID: ORCID
Qingfeng Bu
3
Xiaole Li
3
Hao Zeng
4

  1. 1 State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Effective Development, Beijing 100083, China
  2. State Center for Research and Development of Oil Shale Exploitation, Beijing 102206, China
  3. College of Construction Engineering, Jilin University, Changchun 130026, China
  4. Sinopec Petroleum Exploration and Production Research Institute, Beijing 100083, China
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Abstract

The paper presents chosen results of experimental tests performed on physical mock-ups of tensegrity triplex modules, approximately 1.2 m tall and of 0.5 m diameter, made of steel. A uniform and uniaxial static compressive loading is applied to three upper nodes of the modules at six different self-stress levels. Cable forces are measured using specially crafted force transducers of an electro-resistive strain-gauge type. Two types of struts with different slenderness are incorporated to analyze the influence of buckling on the behaviour of the modules. A simple three-parameter mathematical model is presented to explain the behaviour of the modules and discuss the obtained experimental data. The results show nonlinear behaviour in the equilibrium path, as well as, rapidly decreasing axial stiffness in the post-critical phase. An increase in prestress has a small influence on the stiffness in the chosen range of compressive loading. The experimental results are valuable for purposes of verification and validation of numerical studies and fill the lack of experimental data in the literature.
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Authors and Affiliations

Andrzej Rutkiewicz
1
ORCID: ORCID
Leszek Małyszko
1
ORCID: ORCID

  1. Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, Poland
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Abstract

Test artifacts, resembling real machine parts, allow for quantitative evaluation of system performance and provide insight into individual errors, aiding in improvement and standardization of additive manufacturing. The article provides a comprehensive overview of existing test artifacts, categorized based on geometric features and the material used. Various measurement techniques such as stylus profilometry and computed tomography are employed to assess these artifacts. It is also shown that the selective laser melting (SLM) technology and titanium alloys are prevalent in artifact creation. Specific artifact categories include slits, angular aspects, length parameters, variable surfaces, and others, each accompanied by examples from research literature, highlighting diverse artifact designs and their intended applications. The paper critically discusses the main problems with existing geometries. It underscores the importance of user-friendly and unambiguous artifacts for dimensional control, particularly in surface metrology. Furthermore, it anticipates the continued growth of metrological verification in future manufacturing environments, emphasizing the need for precise and reliable measurement results to support decision-making under production conditions.
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Authors and Affiliations

Patryk Mietliński
1
Bartosz Gapiński
1
Jolanta B. Królczyk
2
Piotr Niesłony
2
Marta Bogdan-Chudy
2
Anna Trych-Wildner
3
Natalia Wojciechowska
3
Grzegorz M. Królczyk
2
Michał Wieczorowski
1
Tomasz Bartkowiak
1
ORCID: ORCID

  1. Poznan University of Technology, Poland
  2. Opole University of Technology, Poland
  3. Central Office of Measures (GUM), Poland
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Abstract

The related work of the diamond burnishing processes focused on improvements in surface quality. The study aims to optimize burnishing factors, including the spraying distance of the nozzle (S), the inlet pressure of the cold air (I), and the quantity of the liquid CO2 (L) of the cool and cryogenic-assisted diamond burnishing operation for minimizing energy consumed (EC) and arithmetical mean surface height roughness (Sa). Burnishing responses are modelled based on the radial basis function network and full factorial data. The entropy method, improved grey wolf optimizer, non-dominated sorting genetic algorithm II, and technique for order of preference by similarity to the ideal solution were implemented to calculate the weights, produce solutions, and select the best outcome. As a result, the optimal data of the S, I, and L were 15.0 mm, 3.0 bar, and 11.0 L/min, respectively. The Sa and EC were reduced by 20.4% and 3.8%, respectively, at the optimality. The optimized outcomes could be employed to improve energy efficiency and machining quality for the internal diamond burnishing process. The optimizing technique could be used to solve complicated issues for different burnishing operations. The cool and cryogenic-assisted diamond burnishing process could be utilized for machining different internal holes.
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Authors and Affiliations

An-Le Van
1 2
Truong-An Nguyen
3
Xuan-Ba Dang
4
Trung-Thanh Nguyen
3
ORCID: ORCID

  1. Faculty of Engineering and Technology, Nguyen Tat Thanh University, 300A Nguyen Tat Thanh, Ho Chi Minh City 700000, Vietnam
  2. Vo Van Ngan Street, Linh Chieu Ward, Thu Duc City, Ho Chi Minh City 700000, Vietnam
  3. Faculty of Mechanical Engineering, Le Quy Don Technical University, 236 Hoang Quoc Viet, Ha Noi 100000, Vietnam
  4. Department of Automatic Control, Ho Chi Minh City University of Technology and Education,
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Abstract

The working environment and objects of agricultural machinery are different from those of automobiles, and agricultural machinery is greatly affected by such working environment and working conditions, while its power output system is more complex. Agricultural machinery not only has drive output, but also PTO output and hydraulic output, which together constitute the output system of agricultural machinery. Agricultural machinery conditions can be divided into road transportation working conditions and field operation working conditions. The working conditions of agricultural machinery can be divided into different load conditions according to the different traction tools and whether the hydraulic and PTO work, such as ploughing, rotary tillage, fertilization and transportation. Therefore, developing hybrid electric agricultural machinery systems that are suitable for various complex working conditions holds great theoretical significance and practical value. This should be done bearing mind the complex working conditions of agricultural machinery systems in agricultural work and the intricate challenges in designing hybrid agricultural machinery systems. In this paper, a two-dimensional matrix is used to represent the physical structure and dynamics of the multi-channel power output agricultural mechanism. A hierarchical two-dimensional matrix method for the generation and screening of hybrid electric agricultural machinery systems with multi-power output power is also proposed. The components of agricultural machinery are divided into an input layer and an output layer, and these components are coded and defined, and then transformed into a matrix. The hierarchical two-dimensional matrix method is used to generate and screen the hybrid electric agricultural mechanism type. Through the stratification of the matrix, complexity of the configuration generation is reduced, and the constraints are applied to the basic screening of the configurations generated. The rationality of the configurations obtained after generation and screening is verified by Simulink simulation. The results show that the configuration screened by this method can meet the performance requirements of agricultural machinery.
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Authors and Affiliations

Baogang Li
1 2
Jinbo Pan
1
ORCID: ORCID
Rui Sun
1
Yuhuan Li
Zunmin Liu
1
Wanyou Huang
2
Hanjun Jiang
1
Fuhao Liu
1

  1. School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China
  2. Key Laboratory of Transportation Industry for Transport Vehicle Detection, Diagnosis and Maintenance Technology, Jinan 250357, China
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Abstract

This article aims to present the results of tunnel tests and field tests of small-scale horizontal-axis wind turbines. The article proposes a new concept of turbine rotor adapted to improve efficiency at low wind speeds. The methodology for calculating the rotor and generator is shown. The turbine construction solution is presented briefly, along with the technology for manufacturing turbine components and assembly. An analysis of the obtained results is also conducted.
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Authors and Affiliations

Piotr Strojny
1
ORCID: ORCID

  1. Rzeszow University of Technology, Faculty of Mechanical Engineering and Aeronautics, Department of Aerospace Engineering, al. Powstanców Warszawy 12, 35-959 Rzeszów, Poland
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Abstract

The application of active adhesion control to the traction control system of an electric train holds great appeal for maximizing longitudinal acceleration force. Most of the currently reported works regulate the adhesion between wheel and rail by adjusting the torque reference of a cascade motor drive controller, which suffers from slow speed response and excessive start torque. This article proposes a cascadefree predictive adhesion control strategy for electric trains powered by an interior permanent magnet synchronous motor (IPMSM) to address these issues. The proposed control scheme utilizes an improved perturbation and observation method to predict the time-varying wheel-rail adhesion state and determine the optimal slip speed. The initial setpoint reference command from the driver master is then adjusted to a dynamic reference that continuously adapts to the predicted adhesion conditions. Finally, the predictive speed control method is employed to ensure rapid convergence of the tracking objective. The simulation and hardware-in-the-loop testing results confirm that this approach achieves excellent dynamic performance, particularly during the train start-up phase and in the high-speed weak magnetic area of the IPMSM
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Authors and Affiliations

Jiao Ren
1
Ruiqi Li
2
ORCID: ORCID

  1. Urban Vocational College of Sichuan,Chengdu 610031, China
  2. School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China
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Abstract

The paper presents a kinematics calibration procedure for a lightweight manipulator designed for medical applications. They comprise improving the dexterity of a dysfunctional arm of a handicapped patient in an electric wheelchair as well as supporting biopsies and surgeries. Consequently, there are several manipulator distinguishing features of the manipulator design that are relevant to kinematics calibration. In particular, these are: a small area in the workspace within which the end-effector operates, affordability for non-commercial users, a delicate, dexterous design. In this context we propose a specialized procedure that features a low cost calibration tool enabling the end-effector to reach the correct positions for data acquisition. The key parameters of the calibration tool were obtained by applying two techniques of numerical analysis, workspace clustering and arbitrary choice, and subsequent experimental verification. The procedure exploits classical results concerning the kinematics calibration and is empirically verified by comprehensive simulation and experimental studies.
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Authors and Affiliations

Krzysztof Arent
1
Adam Kurnicki
2
Piotr Portasiak
3
Bartłomiej Stańczyk
4

  1. Department of Cybernetics and Robotics, Faculty of Electronics, Photonics and Microsystems, Wrocław University of Science and Technology,Wybrzeze Wyspiańskiego 27, 50-370 Wrocław, Poland
  2. Department of Automation and Metrology, Electrical Engineering and Computer Science Faculty, Lublin University of Technology, ul. Nadbystrzycka 38A, 20-618 Lublin, Poland
  3. Faculty of Electronics, Photonics and Microsystems, Wrocław University of Science and Technology, Wybrzeze Wyspiańskiego 27, 50-370 Wrocław, Poland
  4. Accrea Medical Robotics, ul. Hiacyntowa 20, 20-143 Lublin, Poland
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Abstract

Lithium-based battery systems (LBS) are used in various applications, from the smallest electronic devices to power generation plants. LBS energy storage technology, which can offer high power and high energy density simultaneously, can respond to continuous energy needs and meet sudden power demands. The lifetime of LBSs, which are seen as a high-cost storage technology, depends on many parameters such as usage habits, temperature and charge rate. Since LBSs store energy electrochemically, they are seriously affected by temperature. High-temperature environments increase the thermal stress exerted on LBS and cause its chemical structure to deteriorate much faster. In addition, the fast charging feature of LBSs, which is generally presented as an advantage, increases the internal temperature of the cell and negatively affects the battery life. The proposed energy management approach ensures that the ambient temperature affects the charging speed of the battery and that the charging speed is adaptively updated continuously. So, the two parameters that harm battery health absorb each other, and the battery has a longer life. A new differential approach has been created for the proposed energy management system. The total amount of energy that can be withdrawn from LBS is increased by 14.18% as compared to the LBS controlled with the standard energy management system using the genetic algorithm optimized parameters. Thus the LBS replacement period is extended, providing both cost benefits and environmentally friendly management by LBSs turning into chemical waste distinctly later.
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Authors and Affiliations

Gökhan Yüksek
1
ORCID: ORCID
Timur Lale
1
ORCID: ORCID

  1. Department of Electrical and Electronics Engineering, Faculty of Architecture and Engineering, Batman University,Bati Raman Campus 72000, Batman, Turkey
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Abstract

The publication addresses the dynamic state challenges encountered during development of a dual active bridge (DAB) converter within DC microgrid systems. The conventional startup method is identified as instigating a cascade of unfavorable outcomes, encompassing elevated starting current, transformer current asymmetry, DC voltage distortions, EMI and heightened thermal stress on semiconductor components. Additionally, it necessitates precise calibration of magnetic components and diodes. A proposed remedy to these issues is introduced, involving a control method based on an additional phase shift to modulate the current of the primary H bridge. This novel control methodology is posited as a means to mitigate the aforementioned undesirable effects associated with traditional converter initiation techniques. The research also delves into considerations of a proper design procedure for the converter. Emphasis is placed on integrating the novel control methodology into the design framework in order to effectively address challenges arising during transient states. Validation of the proposed solution is substantiated through a series of laboratory tests, the results of which are comprehensively presented in the article. These tests affirm the efficiency of the system when incorporating the novel control methodology, thereby substantiating its practical utility in mitigating the issues identified during the initiation phase of the DAB converter in DC microgrid systems.
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Authors and Affiliations

Serafin Bachman
1
ORCID: ORCID
Marek Turzyński
2

  1. Warsaw University of Technology, Institute of Control and Industrial Electronics, Warsaw, Poland
  2. Gdansk University of Technology, Department of Power Electronics and Electrical Machines
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Abstract

Green energy transformation requires comprehensive strategies that include both innovations in energy production and more efficient energy use. This article investigates the potential for saving electrical energy in industrial automation systems by utilizing bistable switching/relay. Compared to traditional systems, these innovative solutions demonstrate significant reductions in energy consumption. A market analysis of available bistable relays, along with experimental determination of their control conditions, highlights their application potential and indicates the benefits of their implementation. The findings suggest that replacing classical relays with their bistable counterparts could significantly contribute to global sustainability efforts. The article presents the process of redesigning a standard industrial relay into a bistable design. Adding two additional elements achieved the intended bistable functionality. The article calls for increased research and investment in such technologies, emphasizing that the energy-saving potential offered by bistable switching/relay circuits should not be overlooked.
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Authors and Affiliations

Piotr Tetlak
1 2
ORCID: ORCID

  1. University of Zielona Góra, Licealna 9, 65-417 Zielona Góra
  2. RELPOL S.A., ul. 11 Listopada 37, 62-100 Zary, Poland
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Abstract

With the increasing proportion of renewable energy power generation, its accompanying intermittency and volatility problems are becoming increasingly prominent, and the frequency fluctuation of the power system is becoming increasingly severe. Participation in frequency regulation services can be economically rewarding for generating units. The flywheel energy storage system can effectively improve the frequency regulation capability of coal-fired units. In this paper, the improvement of the FM capability of coal-fired units in the operation of a two-area interconnected power system containing wind power is investigated, and a model of a two-area interconnected power system comprising a turbine generator, wind power, and flywheel energy storage is established. The enhancement of the FM capability of coal-fired units by adding a flywheel energy storage system is analyzed. The simulation results show that adding the flywheel energy storage system improves the FM capability of the coal-fired unit to a considerable extent, and the coal-fired unit can decide the flywheel capacity it needs to be equipped with through detailed economic calculations.
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Authors and Affiliations

Shunyi Song
1
Tianshu Qiao
2
ORCID: ORCID
Rui Zhang
1
Shuangyin Liang
2
Yibing Liu
2

  1. Shenzhen Energy Nanjing Holding Co., Ltd, Nanjing, China
  2. School of Energy, Power and Mechanical Engineering, North China Electric Power University, Beijing, China

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