bluuebunny/crossref_metadata_2025 huggingface dataset:
A Particle Shift Prior Information Fusion Localization Algorithm for the Autonomous Internet of Vehicles
Authors: Chen Qian , Tang Xin , Su Zhaoyu , Li Xiaohuan , Wang Duiwu
Published: June 2022

Ensuring that a vehicle can obtain its real location in a high-precision prebuilt map is one of the most important tasks of the Autonomous Internet of Vehicles (AIoV). In this work, we show that the resampling of the particle filter (PF) algorithm is optimized by using the prior information of particles that shift real localizations to improve vehicle localization accuracy without changing the existing PF process, i.e., the particle shift filter (PSF). The number of particles is critical to their convergence efficiency. We perform quantitative and qualitative analyses of how to improve particle localization accuracy while ensuring timeliness, without increasing the number of particles. Moreover, the cumulative error of the particles increases with time, and the localization accuracy and robustness decrease. Our findings show that the initial particle density is 159 particles/m3, and the cumulative variance of the PSF particles is improved by 27%, 29%, and 82% at the x-, y-, and z-axes, respectively, under the same conditions as the PF algorithm, while the calculation time only increases by 10.6%. Moreover, the cumulative mean error is reduced by 0.74 m, 0.88 m, and 0.68 m at the x-, y-, and z-axes, respectively, indicating that the localization error of the PSF changes less with time. All experiments were performed using open-source software and datasets.
A High-Efficiency High-Power-Density SiC-Based Portable Charger for Electric Vehicles
Authors: Ditze Stefan , Ehrlich Stefan , Weitz Nikolai , Sauer Marco , Aßmus Frank , Sacher Anne , Joffe Christopher , Seßler Christoph , Meißner Patrick
Published: June 2022

This paper proposes a portable 11 kW off-board charger for electric vehicles. In the ac/dc stage, a three-phase power factor correction (PFC) in Vienna topology is chosen. The loss and volume of the PFC inductance are calculated over a wide range of parameters and optimized with regard to design, winding, and core material. A three-phase LLC resonant converter operating at 1 MHz is chosen for the galvanically isolated dc/dc stage. A parametrizable loss model of the high-frequency transformer and the resonance inductor is developed to minimize volume, weight, and losses. With the help of an automated algorithm using these loss models, the inductive components are optimized in terms of winding specification, magnetic material, and core geometry, verified by finite element analysis and measurements. For the ac/dc stage, 900 V SiC devices are adopted, and 1200 V SiC devices are used in the primary and secondary sides of the dc/dc stage. A variable dc-link voltage is utilized to adjust the charging profile and to operate the LLC resonant converter at the most efficient point near the series resonance frequency. A mechatronically integrated portable air-cooled off-board charger prototype with 11 kW, three-phase 400 VAC input, and 620–850 VDC output is realized and tested. The prototype demonstrates a power density of 2.3 kW/liter (37.7 W/in³), a peak efficiency of 96%, and 95.8% efficiency over the defined battery voltage range.
A Layered Approach to Threat Modeling for 5G-Based Systems
Authors: Farooqui Muhammad Najmul Islam , Arshad Junaid , Khan Muhammad Mubashir
Published: June 2022

The rise of 5G networks promises a wide range of cutting-edge services with the aim of achieving high performance and reliability. Cutting-edge applications facilitated by 5G architecture make use of various enabling technologies, which introduce various new and emerging security threats and attacks. Threat modeling is a proactive approach to identify security requirements, as well as potential threats and vulnerabilities, and prioritize remediation methods. In addition, 5G networks are complex and are usually divided into separate layers to foster the understanding and management of different functionalities. The open nature of 5G envisages that multiple vendors and service providers might be working on network deployment and service provisioning; it is therefore necessary to address and categorize the threats at each layer distinctly. This paper presents a threat model for 5G-based systems. It leverages the layered 5G architecture, identifying threat categories and mapping these to corresponding layers. It also analyzes enabling technologies affected by identified threats along with threat actors, entry points, and the impact of threat categories. Through the development of this threat model, we envisage facilitating further research into specific threats and mechanisms to protect against them.
A Multi-Lingual Speech Recognition-Based Framework to Human-Drone Interaction
Authors: Choutri Kheireddine , Lagha Mohand , Meshoul Souham , Batouche Mohamed , Kacel Yasmine , Mebarkia Nihad
Published: June 2022

In recent years, human–drone interaction has received increasing interest from the scientific community. When interacting with a drone, humans assume a variety of roles, the nature of which are determined by the drone’s application and degree of autonomy. Common methods of controlling drone movements include by RF remote control and ground control station. These devices are often difficult to manipulate and may even require some training. An alternative is to use innovative methods called natural user interfaces that allow users to interact with drones in an intuitive manner using speech. However, using only one language of interacting may limit the number of users, especially if different languages are spoken in the same region. Moreover, environmental and propellers noise make speech recognition a complicated task. The goal of this work is to use a multilingual speech recognition system that includes English, Arabic, and Amazigh to control the movement of drones. The reason for selecting these languages is that they are widely spoken in many regions, particularly in the Middle East and North Africa (MENA) zone. To achieve this goal, a two-stage approach is proposed. During the first stage, a deep learning based model for multilingual speech recognition is designed. Then, the developed model is deployed in real settings using a quadrotor UAV. The network was trained using 38,850 records including commands and unknown words mixed with noise to improve robustness. An average class accuracy of more than 93% has been achieved. After that, experiments were conducted involving 16 participants giving voice commands in order to test the efficiency of the designed system. The achieved accuracy is about 93.76% for English recognition and 88.55%, 82.31% for Arabic and Amazigh, respectively. Finally, hardware implementation of the designed system on a quadrotor UAV was made. Real time tests have shown that the approach is very promising as an alternative form of human–drone interaction while offering the benefit of control simplicity.
A Low-Latency Streaming On-Device Automatic Speech Recognition System Using a CNN Acoustic Model on FPGA and a Language Model on Smartphone
Authors: Park Jaehyun , Noh Hyeonkyu , Nam Hyunjoon , Lee Won-Cheol , Park Hong-June
Published: June 2022

This paper presents a low-latency streaming on-device automatic speech recognition system for inference. It consists of a hardware acoustic model implemented in a field-programmable gate array, coupled with a software language model running on a smartphone. The smartphone works as the master of the automatic speech recognition system and runs a three-gram language model on the acoustic model output to increase accuracy. The smartphone calculates and sends the Mel-spectrogram of an audio stream with 80 ms unit input from the built-in microphone of the smartphone to the field-programmable gate array every 80 ms. After ~35 ms, the field-programmable gate array sends the calculated word-piece probability to the smartphone, which runs the language model and generates the text output on the smartphone display. The worst-case latency from the audio-stream start time to the text output time was measured as 125.5 ms. The real-time factor is 0.57. The hardware acoustic model is derived from a time-depth-separable convolutional neural network model by reducing the number of weights from 115 M to 9.3 M to decrease the number of multiply-and-accumulate operations by two orders of magnitude. Additionally, the unit input length is reduced from 1000 ms to 80 ms, and to minimize the latency, no future data are used. The hardware acoustic model uses an instruction-based architecture that supports any sequence of convolutional neural network, residual network, layer normalization, and rectified linear unit operations. For the LibriSpeech test-clean dataset, the word error rate of the hardware acoustic model was 13.2% and for the language model, it was 9.1%. These numbers were degraded by 3.4% and 3.2% from the original convolutional neural network software model due to the reduced number of weights and the lowering of the floating-point precision from 32 to 16 bit. The automatic speech recognition system has been demonstrated successfully in real application scenarios.
Greengage Grading Method Based on Dynamic Feature and Ensemble Networks
Authors: Chen Keqiong , Li Weitao , An Jiaxi , Bu Tianrui
Published: June 2022

To overcome the deficiencies of the traditional open-loop cognition method, which lacks evaluation of the cognitive results, a novel cognitive method for greengage grading based on dynamic feature and ensemble networks is explored in this paper. First, a greengage grading architecture with an adaptive feedback mechanism based on error adjustment is constructed to imitate the human cognitive mechanism. Secondly, a dynamic representation model for convolutional feature space construction of a greengage image is established based on the entropy constraint indicators, and the bagging classification network for greengage grading is built based on stochastic configuration networks (SCNs) to realize a hierarchical representation of the greengage features and enhance the generalization of the classifier. Thirdly, an entropy-based error model of the cognitive results for greengage grading is constructed to describe the optimal cognitive problem from an information perspective, and then the criteria and mechanism for feature level and feature efficiency regulation are given out within the constraint of cognitive error entropy. Finally, numerous experiments are performed on the collected greengage images. The experimental results demonstrate the effectiveness and superiority of our method, especially for the classification of similar samples, compared with the existing open-loop algorithms.
Joint User Scheduling and Resource Allocation in Distributed MIMO Systems with Multi-Carriers
Authors: Bu Yinglan , Zong Jiaying , Xia Xinjiang , Liu Yang , Yang Fengyi , Wang Dongming
Published: June 2022

Compared with the traditional collocated multi-input multi-output system (C-MIMO), distributed MIMO (D-MIMO) systems have the advantage of higher throughput and coverage, making them strong candidates for next-generation communication architecture. As a practical implementation of a D-MIMO cooperative network, the multi-TRP (multiple transmission/reception point) system becomes a hotspot in the research of advanced 5G. Different from previous research on a cooperative D-MIMO network with single narrowband transmission, this paper proposes a joint optimization scheme to address the user scheduling problem along with carrier allocation to maximize the total spectral efficiency (SE) in the downlink of coherent multi-TRP systems with multi-carriers. We establish a joint optimization model of user scheduling and resource allocation to maximize the system spectral efficiency under the constraints of power consumption and the backhaul capacity limits at each RAU (remote antenna unit), as well as the QoS (quality of service) requirement at each user. Since the optimization model is both non-covex and non-smooth, a joint optimization algorithm is proposed to solve this non-convex combinatorial optimization problem. We first smooth the mixed-integer problem by employing penalty functions, and after decoupling the coupled variables by introducing auxiliary variables, the original problem is transformed into a series of tractable convex optimization problems by using successive convex approximation (SCA). Numerical results demonstrate that the proposed joint optimization algorithm for user scheduling and resource allocation can reliably converge and achieve a higher system SE than the general multi-TRP system without carrier allocation, and this advantage is more pronounced under a higher backhaul capacity or higher power consumption constraints.
Marker-Based 3D Position-Prediction Algorithm of Mobile Vertiport for Cabin-Delivery Mechanism of Dual-Mode Flying Car
Authors: Bae Hyansu , Lee Jeongwook , Lee Kichang
Published: June 2022

This paper presents an image-processing technique for cabin delivery employing local localization and docking in a mobile station, which is a mobile vertiport for the use of dual-mode flying cars. A dual-mode flying automobile with an aerial electric vehicle (AEV), a ground electric vehicle (GEV), and a cabin is a future method of transportation that can be used in both the air and on the ground. To enable AEVs to land in a specific position, a landing site is necessary. The proposed AEV uses vertical take-off and landing, and a vertiport landing site is required. As vertical take-off and landing sites require a lot of space and are challenging to operate in multiple positions, we suggest a mobile vertiport that can fit into a small space. A mobile station is appropriate for dual-mode flying cars since it includes critical activities such as transporting AEVs from the ground and charging as well as a cabin-delivery system. The mobile station can generate a path to the AEV by calculating the relative position using the markers attached to the AEV and estimating the position of the landing AEV. The mobile station detects a marker for precise positioning correction, followed by exact position correction for cabin delivery, to travel to the accurate position of the AEV. To increase the success rate of cabin delivery, docking markers are identified and the angle position error between the mobile station and cabin is computed and corrected to rectify the position between the cabin and the mobile station for cabin delivery. In addition, the experimental results revealed a mechanically correctable error range that encompassed all experimental values. Consequently, this study showed that image processing may be used to create a mobile station for dual-mode flying automobiles.
Single-Branch Wide-Swing-Cascode Subthreshold GaN Monolithic Voltage Reference
Authors: Bimbi Cesare , Pennisi Salvatore , Privitera Salvatore , Pulvirenti Francesco
Published: June 2022

A voltage reference generator in GaN IC technology for smart power applications is described, analyzed, and simulated. A straightforward design procedure is also highlighted. Compared to previous low-power monolithic solutions, the proposed one is based on a single branch and on transistors operating in a subthreshold. The circuit provides a nearly 2.7 V reference voltage under 4 V to 24 V supply at room temperature and with typical transistor models. The circuit exhibits a good robustness against large process variations and improves line regulation (0.105 %V) together with a reduction in area occupation (0.05 mm2), with a reduced current consumption of 2.7 µA (5 µA) in the typical (worst) case, independent of supply. The untrimmed temperature coefficient is 200 ppm/°C.
A Circuit-Based Wave Port Boundary Condition for the Nodal Discontinuous Galerkin Time-Domain Method
Authors: Zhu Shichen , Shi Yan , Ban Zhenguo
Published: June 2022

Waveguide-like transmission line (WLTL) structures, including rectangular waveguides, circular waveguides, and coaxial lines, have been widely used in microwave engineering. Determining how to efficiently model WLTLs has become vital for the design of various WLTL-based devices. In this paper, a circuit-based wave port boundary condition (CWPBC) is developed and applied in the discontinuous Galerkin time-domain (DGTD) method to accurately simulate these structures for the first time. In the CWPBC, modal voltages and currents of a WLTL are defined, and circuits based on modal voltages and currents are introduced. By co-simulating the modal circuit and the WLTL modeled using the DGTD method, various modal fields can be excited in the WLTL, and at the same time, the WLTL can be terminated without reflections. No extra costs or approximations are used in the proposed CWPBC, and there is no requirement of either the extension of the computational domains widely used in perfectly matched layer (PML) termination or the longitudinal field continuity used in the reported DGTD method. The proposed method can easily obtain the postprocessing parameters, including S-parameters and port power. Numerical results, including rectangular waveguide filters, circular waveguide horns, and coaxial-fed electromagnetic bandgaps (EBG), are given to validate the effectiveness of the proposed CWPBC.
A Constant Current Wireless Power Transfer Scheme with Asymmetric Loosely Coupled Transformer for Electric Forklift
Authors: Liu Xuecheng , Zhou Jing , Yang Aixi , Gao Jian , Li Qiang
Published: June 2022

Due to the numerous advantages such as being convenient, safe, and contactless, wireless power transfer (WPT) is becoming the mainstream charging method for electric vehicles. This paper presents a constant current WPT system with asymmetric loosely coupled transformer for electric forklifts using lead-acid batteries. First, based on the Neumann formula, this paper analyzes the mutual inductance of the coaxial rectangular coil, and designs an asymmetric loosely coupled transformer based on the practical application requirements, which makes the secondary side light and miniaturized. Second, the WPT system is analyzed in terms of the requirements of constant current charging, and the dual-LCL compensation is proposed according to the output current and power requirements. The transfer characteristics and anti-interference capability of the topology are analyzed. The constant current output feature of the system under the condition of variable load is demonstrated. After that, a dual-active bridge secondary-side independent control strategy is proposed, the phase shift angle is adjusted to ensure constant charging current and high efficiency of the system. Finally, a wireless charging experimental platform is established in accordance with the proposed asymmetric loosely coupled transformer and WPT system. The system can achieve 45 A constant current output and 3 kW output power with 91.2% transmission efficiency.
Research on Buffer Characteristics of a New 2D Digital Buffer Valve for Vehicle Shift
Authors: Zhang Qihui , Liu Yi , Xiong Wei , Ruan Jian , Tang Jun , Tan Janping
Published: June 2022

The clutch is currently developing towards high power, high stability, and intelligent operation. The traditional hydraulic buffering valve mostly uses a passive hydraulic buffer valve or a high speed on-off valve and a proportion valve. It has a single buffering characteristic and poor adaptability. It is difficult to meet the requirements. Therefore, a new theory and a new method are proposed. In the field of clutch oil pressure control, the 2D digital buffer valve is designed using 2D digital technology. The structure of the 2D digital buffering valve is described. Based on the working principle of the valve, a mathematical model is set up. MATLAB/Simulink is used to solve the model. The results are analyzed in this paper. Finally, a valve test platform is built and an experimental study carried out. The research indicates that the 2D digital buffering valve has a good static characteristic. The linearity is 9.25%, and the hysteresis is 0.106. The response time of the 2D digital buffer valve is about 55 ms, and the valve overshoot is only 18.62%. During shifting, the maximum deviation is 0.165 MPa, and the steady-state error is 0.056 MPa. Different buffer control signals as the input and the output of the valve can follow the input change. The experimental and simulation results are consistent. The rationality of the mathematical model has been verified.
Securing Color Video When Transmitting through Communication Channels Using DT-CWT-Based Watermarking
Authors: Alkanhel Reem , Abdallah Hanaa A.
Published: June 2022

In this paper, a color video watermarking system based on SVD in the complex wavelet domain is proposed. The process of inserting copyright information in video bit streams is known as video watermarking. It has been advocated in recent years as a solution to the problem of unlawful digital video alteration and dissemination. An effective, robust, and invisible video watermarking algorithm is proposed in this paper. The two-level dual tree complex wavelet transform (DT-CWT) and singular value decomposition are used to create this approach, which was built on a cascade of two powerful mathematical transforms. This hybrid technique demonstrates a high level of security as well as various levels of attack robustness. The proposed algorithm was used to the test for imperceptibility and robustness, and this resulted in excellent grades. We compared our suggested method to a DWT-SVD-based technique and found it to be far more reliable and effective.
Simulation of the Steam Gasification of Japanese Waste Wood in an Indirectly Heated Downdraft Reactor Using PRO/II™: Numerical Comparison of Stoichiometric and Kinetic Models
Authors: Talero Gabriel , Kansha Yasuki
Published: June 2022

The conversion of biomass to olefin by employing gasification has recently gained the attention of the petrochemical sector, and syngas composition is a keystone during the evaluation of process design. Process simulation software is a preferred evaluation tool that employs stoichiometric and kinetic approaches. Despite the available literature, the estimation errors of these simulation methods have scarcely been contrasted. This study compares the errors of stoichiometric and kinetic models by simulating a downdraft steam gasifier in PRO/II. The quantitative examination identifies the model that best predicts the composition of products for the gasification of Japanese wood waste. The simulation adopts reaction mechanisms, flowsheet topology, reactions parameters, and component properties reported in the literature. The results of previous studies are used to validate the models in a comparison of the syngas composition and yield of products. The models are used to reproduce gasification at temperatures of 600∼900 °C and steam-to-biomass mass ratios of 0∼4. Both models reproduce experimental results more accurately for changes in the steam-to-biomass mass ratio than for temperature variations. The kinetic model is more accurate for predicting composition and yields, having global errors of 3.91%-mol/mol and 8.16%-g/gBM, respectively, whereas the simple stoichiometric model has an error of 7.96%-mol/mol and 16.21%-g/gBM.
Estimation of Unmeasured Room Temperature, Relative Humidity, and CO2 Concentrations for a Smart Building Using Machine Learning and Exploratory Data Analysis
Authors: Kaligambe Abraham , Fujita Goro , Keisuke Tagami
Published: June 2022

Smart buildings that utilize innovative technologies such as artificial intelligence (AI), the internet of things (IoT), and cloud computing to improve comfort and reduce energy waste are gaining popularity. Smart buildings comprise a range of sensors to measure real-time indoor environment variables essential for the heating, ventilation, and air conditioning (HVAC) system control strategies. For accuracy and smooth operation, current HVAC system control strategies require multiple sensors to capture the indoor environment variables. However, using too many sensors creates an extensive network that is costly and complex to maintain. Our proposed research solves the mentioned problem by implementing a machine-learning algorithm to estimate unmeasured variables utilizing a limited number of sensors. Using a six-month data set collected from a three-story smart building in Japan, several extreme gradient boosting (XGBoost) models were designed and trained to estimate unmeasured room temperature, relative humidity, and CO2 concentrations. Our models accurately estimated temperature, humidity, and CO2 concentration under various case studies with an average root mean squared error (RMSE) of 0.3 degrees, 2.6%, and 26.25 ppm, respectively. Obtained results show an accurate estimation of indoor environment measurements that is applicable for optimal HVAC system control in smart buildings with a reduced number of required sensors.
Theoretical and Experimental Investigation on Thermal Characteristics of Railway Double-Row Tapered Roller Bearing
Authors: Gao Pengfei , Tang Wuchu , Cui Yunxian , Wang Yuchen , Mo Guowei , Yin Junwei
Published: June 2022

The research on the thermal characteristics of railway double-row tapered roller bearing is of great significance for its structural design and operation monitoring. We established the quasi-static mechanical model of the bearing according to the test conditions, and we obtained the load distribution and kinematic parameters of the bearing. We studied the temperature distribution of railway double-row tapered roller bearing under test conditions through finite element analysis, which was consistent with the test results. We built a bearing testbed to study the effects of different rotating speeds on the temperature distribution of the bearing inner ring, outer ring, and roller. The results show that the speed dramatically affects the bearing inner ring. With the rate increase, the temperature difference between the inner and outer rings decreases gradually, and the temperature at the large end of the roller is the highest.
Half-Duplex and Full-Duplex DF Wireless Energy Harvesting Relaying in Rayleigh Fading
Authors: Sun Hui , Han Fengxia , Zhao Shengjie , Deng Hao
Published: June 2022

With the further development and wide application of wireless technology in 6G, people are increasingly inseparable from wireless devices, from the ground to the air. The power consumption and service life of devices have become an urgent problem to be solved. In this paper, the energy harvesting relaying system based on the power splitting method with unidirectional DF half-duplex and full-duplex relay is proposed. The relay node is powered by itself through energy harvesting. Specifically, we analyze the system capacity, and the formula of system outage probability is also obtained. Simulation results show the performance of the half-duplex and full-duplex system. With a smaller power splitting factor, more energy is harvested, the outage probability is lower, and the capacity is higher.
Piston Thermal Analysis of Heavy Commercial Vehicle Diesel Engine Using Lanthanum Zirconate Thermal-Barrier Coating
Authors: Fei Chunguang , Lei Tong , Qian Zuoqin , Shu Zihao
Published: June 2022

When a commercial vehicle diesel engine works for an extended period of time at the torque spot, it can easily cause a mechanical failure due to the high temperature of the piston. In this paper, the temperature plug method was used to measure the temperature of the piston at the maximum torque spot. In order to reduce the failure caused by high temperature, the finite element analysis software Ansys was used in this paper to study the effects of different thicknesses of ceramic coatings on the piston surface of a diesel engine on the maximum temperature of the piston substrate. The bonding layer of the ceramic coating was NiCoCrAlY with a thickness of 0.1 mm, and the insulating layer was a La2Zr2O7 coating with respective thicknesses of 0.2 mm, 0.3 mm, 0.5 mm, 0.7 mm, and 0.9 mm. When the thickness of the ceramic coating was increased from 0.3 mm to 1.0 mm, the maximum temperature of the piston base decreased from 347.9 °C to 267.46 °C. This showed that the use of a thermal-barrier coating can effectively reduce the maximum temperature of the piston and greatly improve the safety of engine operation.
Preparing the Public Opinion in the Community to Accept Distributed Energy Systems and Renewable Energy
Authors: Friman Hen , Banner Ifaa , Sitbon Yafa , Einav Yulia , Shaked Nava
Published: June 2022

Global energy consumption has reached unprecedented levels over the last century due to population growth and economic growth. There have been significant changes in the global energy economy to reduce greenhouse gas emissions and air pollutants. Due to this trend, many countries around the world are promoting electric technologies as fuel-saving alternatives. The Israeli energy industry integrates renewable sources into its supply system and streamlines consumption. Nevertheless, Israelis know too little about smart meters, energy storage systems, and other modern power grid technology, which enables a decentralized approach to energy management referred to as distributed energy systems (DES). Using distributed energy systems to generate energy on-site and manage loads can reduce costs, improve reliability, and secure revenue. An effective public education program can help prepare public opinion and reduce barriers to smart use and energy efficiency in the home. By educating schoolchildren, we will present a way to prepare the public in the community to accept distributed energy systems and renewable energy. In challenging times, it is vital to make great efforts and to remember that change begins with education and that the best way to achieve intelligent usage and energy efficiency is to start with our children.
A Load-Independent Self-Oscillating Control of Domino Wireless Power Transfer Systems for High-Voltage Power Grid Monitoring Equipment
Authors: Wang Kaiyuan , Liang Rui , Yang Yun
Published: June 2022

Real-time monitoring devices are popularly utilized in modern power grids. To ensure long-term operations of the monitoring systems under complex outdoor conditions, a reliable and stable power supply is essential. In this paper, a general analysis of domino wireless power transfer (WPT) systems with load-independent outputs is proposed to realize a constant power supply for the monitoring equipment. In addition, the methodology of analyzing the self-oscillating points of the proposed domino WPT systems is deduced. The availability and feasibility of the proposed analysis and control method are verified by both simulation and experiment results based on a four-coil WPT system.
Experimental Study on the Thermal Performance of 3D-Printed Enclosing Structures
Authors: Nemova Darya , Kotov Evgeny , Andreeva Darya , Khorobrov Svyatoslav , Olshevskiy Vyacheslav , Vasileva Irina , Zaborova Daria , Musorina Tatiana
Published: June 2022

Three-dimensional printing, or additive manufacturing, is one of the modern techniques emerging in the construction industry. Three-Dimensional Printed Concrete (3DPC) technology is currently evolving with high demand amongst researchers, and the integration of modular building systems with this technology would provide a sustainable solution to modern construction challenges. This work investigates and develops energy-efficient 3D-printable walls that can be implemented worldwide through energy efficiency and sustainability criteria. Numerical research and experimental investigations, bench tests with software packages, and high-precision modern equipment have been used to investigate the thermal performance of 3DPC envelopes with different types of configurations, arrangements of materials, and types of insulation. The research findings showed that an innovative energy-efficient ventilated 3DPC envelope with a low thermal conductivity coefficient was developed following the climatic zone. The annual costs of heat energy consumed for heating and carbon footprint were determined in the software package Revit Insight to assess the energy efficiency of the 3D-printed building. The thermal properties of the main wall body of the tested 3D-printed walls were calculated with on-site monitoring data. The infrared thermography technique detected heterogeneous and non-uniform temperature distributions on the exterior wall surface of the 3DPC tested envelopes.
The Effects of Soiling and Frequency of Optimal Cleaning of PV Panels in Palestine
Authors: Abdallah Ramez , Juaidi Adel , Abdel-Fattah Salameh , Qadi Mahmoud , Shadid Montaser , Albatayneh Aiman , Çamur Hüseyin , García-Cruz Amos , Manzano-Agugliaro Francisco
Published: June 2022

The performance of photovoltaic (PV) solar panels is dependent on certain factors, such as dust effects. Even though Palestine’s energy issues are well-known, no research has been undertaken on the soiling effect on solar energy generation in Palestine’s climatic circumstances. The study’s findings can aid Palestine’s efforts to achieve long-term energy sustainability and solar energy use. Outdoor research was conducted in Tulkarm, Palestine, to explore the impact of dust on PV systems. The current study examined the impact of dust accumulation based on the Mediterranean climate. To accomplish this, a one-year experiment was conducted from 1 January to 31 December 2021. An 85-kW PV power plant at Tulkarm was utilized in the study. Knowing the efficiency reduction over time will aid in minimizing cleaning expenses by selecting the most appropriate cleaning interval. The results concluded that in January, February, November, and December, there will be a two-month cleaning period, monthly cleaning in March and October, as well as two weeks of cleaning in April and May. It may also be concluded that the plant should be cleaned weekly throughout the months of June, July, August, and September. This recommendation is necessary to maintain the PV panel plant operating at peak efficiency.
Low Power Sensor Location Prediction Using Spatial Dimension Transformation and Pattern Recognition
Authors: Lee Wonchan , Jeong Chang-Sung
Published: June 2022

A method of positioning a location on a specific object using a wireless sensor has been developed for a long time. However, due to the error of wavelengths and various interference factors occurring in three-dimensional space, accurate positioning is difficult, and predicting future locations is even more difficult. It uses IoT-based node pattern recognition technology to overcome positioning errors or inaccurate predictions in wireless sensor networks. It developed a method to improve the current positioning accuracy in a sensor network environment and a method to learn a pattern of position data directly from a wavelength receiver. The developed method consists of two steps: The first step is a method of changing location data in 3D space to location data in 2D space in order to reduce the possibility of positioning errors in 3D space. The second step is to reduce the range of the moving direction angle in which the data changed in two dimensions can be changed in the future and to predict future positions through pattern recognition of the position data. It is to calculate the expected position in the future. In conclusion, three-dimensional positioning accuracy was improved through this method, and future positioning accuracy was also improved. The core technology was able to reduce inevitable errors by changing the spatial dimension from 3D to 2D and to improve the accuracy of future location prediction by reducing the range of the movable direction angle of the location data changed to 2D. It was also possible to obtain the result that the prediction accuracy increases in proportion to the amount of data accumulated in the wavelength receiver and the learning time. In the era of the Fourth Industrial Revolution, this method is expected to be utilized in various places, such as smart cities, autonomous vehicles, and disaster prediction.
An Experimental Study of Drift Caused by Partial Shading Using a Modified DC-(P&O) Technique for a Stand-Alone PV System
Authors: Singhal Ashish Kumar , Beniwal Narendra Singh , Beniwal Ruby , Lalik Krzysztof
Published: June 2022

There is tremendous potential in solar energy to meet future electricity demands. Partial shading (PS) and drift are two major problems that must be addressed simultaneously to achieve the maximum power point (MPP) of a stand-alone PV system, which are discussed in this paper. Both of these factors contribute to the voltage drop due to heavy steady-state oscillation. The partial shading and drift problem are associated with severe rapid changes in the insolation. A modified drift-control perturbation and observation DC-(P&O) approach was investigated using a low-cost programmable hardware solution, i.e., the ARM Cortex M4 32-bit Microcontroller (MC) (STM32F407VGT6), with efficient embedded programming and Waijung block sets for real-time solutions. The experimental setup was accomplished on a 40-watt solar panel. It was found that the proposed method had a significant impact on drift control during abrupt changes in current and voltage caused by shading effects, with the controller conversion efficiency of 80.39% and 94.48% with percentage absolute errors of 7.3 and 7.2 for cases with and without PS and drift, respectively.
A Modified SOGI-PLL with Adjustable Refiltering for Improved Stability and Reduced Response Time
Authors: Herrejón-Pintor Gilberto A. , Melgoza-Vázquez Enrique , Chávez Jose de Jesús
Published: June 2022

The controls of most power electronic inverters connected to an electrical power system (EPS) rely on the precise determination of the voltage magnitude, frequency, and phase angle at the point of common coupling. One of the most widely used approaches for measuring these quantities is the phase-locked loop (PLL); however, the precision of this measurement is affected during transients in the EPS and is a function of the type of event and the architecture of the PLL. PLLs based on the second-order generalized integrator (SOGI) are widely used in power converter synchronization, offering an adaptive or fixed-parameter prefilter with low-pass and band-pass characteristics. This article proposes a variant of the SOGI-PLL that offers improved stability and a faster response time. This is accomplished by decoupling the effect of the SOGI’s gains and adding feedback. The modification is carried out in the state space model of the SOGI. Manipulating the attenuation moves the poles of the SOGI to improve the stability. The performance of the proposed PLL is verified and validated under the processor-in-the-loop (PIL) approach.
Methodology for the Estimation of Electrical Power Consumed by Locomotives on Undocumented Railroad Tracks
Authors: Rodriguez-Cabal Miguel Angel , Herrera-Jaramillo Diego Alejandro , Bastidas-Rodriguez Juan David , Villegas-Ceballos Juan Pablo , Montes-Villa Kevin Smit
Published: June 2022

The energy consumption estimation of a locomotive for a particular route is important for the selection of a locomotive technology, the improvement of the energy management system, the evaluation of the locomotive’s potential energy generation, among others. The methodologies reported in the literature usually assume that the information of the railway track is available; however, in some cases, the track information is incomplete, not available, or the route is still in a planning stage. Therefore, this paper proposes a methodology to estimate the energy consumption and the potential energy generation of a locomotive when the railway track information is not available or incomplete. The methodology begins by extracting the main technical information of the locomotive to be analyzed. Then, the route is traced on Google Earth with steps of 100 m and the obtained information is processed to generate the longitude, latitude, elevation, and distance of the points along the route. From such information, it is possible to generate the slope and curvature profiles, while the speed profile can be obtained from the track operator or the regulations of a specific country. With that information, it is possible to estimate the equivalent power of the locomotive at each point of the route to finally calculate the consumed energy. The proposed methodology is validated with two case studies. The first one compares the results with a methodology available in the literature for the same route and locomotive, while the second case shows the applicability of the proposed methodology for a route without information.
Film Boiling Conjugate Heat Transfer during Immersion Quenching
Authors: Kamenicky Robin , Frank Michael , Drikakis Dimitris , Ritos Konstantinos
Published: June 2022

Boiling conjugate heat transfer is an active field of research encountered in several industries, including metallurgy, power generation and electronics. This paper presents a computational fluid dynamics approach capable of accurately modelling the heat transfer and flow phenomena during immersion quenching: a process in which a hot solid is immersed into a liquid, leading to sudden boiling at the solid–liquid interface. The adopted methodology allows us to couple solid and fluid regions with very different physics, using partitioned coupling. The energy equation describes the solid, while the Eulerian two-fluid modelling approach governs the fluid’s behaviour. We focus on a film boiling heat transfer regime, yet also consider natural convection, nucleate and transition boiling. A detailed overview of the methodology is given, including an analytical description of the conjugate heat transfer between all three phases. The latter leads to the derivation of a fluid temperature and Biot number, considering both fluid phases. These are then employed to assess the solver’s behaviour. In comparison with previous research, additional heat transfer regimes, extra interfacial forces and separate energy equations for each fluid phase, including phase change at their interface, are employed. Finally, the validation of the computational approach is conducted against published experimental and numerical results.
Improving the Efficiency of Curved Wells’ Operation by Means of Progressive Cavity Pumps
Authors: Isaev Anatoliy Andreevich , Aliev Mekhrali Mirzali Ogly , Drozdov Alexander Nikolaevich , Gorbyleva Yana Alekseevna , Nurgalieva Karina Shamilyevna
Published: June 2022

This paper proposes a solution to the problem of improving the reliability of the operation of progressive cavity pump units in deviated and directional wells. High dogleg severity significantly contributes to rod breakage; rods often break close to the “elbows” with a dogleg severity of 2 deg/10 m or higher. Statistical analyses were used to identify the frequency of failures and their impact on the reliability of a PCP unit. The design layout and mathematical model for pump rods’ torsional vibrations in the curved section of a wellbore were developed. A simulation of the curved section was performed. This article provides the basic formulas needed to design a rotating rod string using two reduced discs. The creation of an additional crooked section resulted in multiple reductions in the “resonant” rotational speed and rigidity in the mathematical model. Determining the moment of inertia of the reduced discs’ mass made it possible to determine the sucker-rod string’s stiffness, the circular rotation frequency, and the number of sucker-rod revolutions under resonance. The number of reduced discs on the sucker-rod string depends on the curvature pattern. In summary, a centralizer for a rotating string was designed to reduce the vibration and shock effects of rods on the tubing.
MTDC Grids: A Metaheuristic Solution for Nonlinear Control
Authors: Yousaf Muhammad Zain , Raza Ali , Abbas Ghulam , Ullah Nasim , Al-Ahmadi Ahmad Aziz , Yasin Abdul Rehman , Jamil Mohsin
Published: June 2022

This scientific paper aims to increase the voltage source converter (VSC) control efficiency in a multi-terminal high voltage direct current (MTDC) network during dynamic operations. In the proposed study, the Mayfly algorithm (MA) is used to modify the control parameters of VSC stations. Traditional strategies that modify VSC control settings using approximate linear models fail to produce optimal results because VSCs are nonlinear characteristics of the MTDC system. Particle swarm optimization (PSO) may produce optimal outcomes, but it is prone to becoming stuck in a local optimum. To modify the proportional-integral (P.I.) control parameters of the VSC station, the Mayfly algorithm, a modified form of PSO, is used. The suggested algorithm’s objective function simultaneously optimizes both the outer and inner control layers. A four-terminal MTDC test system is developed in PSCAD/EMTDC to assess the benefits of the proposed algorithm. For VSCs, a comparison of classical, PSO, and proposed MA-based tuned parameters is carried out. The integral of time multiplied by absolute error (ITAE) criterion is used to compare the performance of classical, PSO, and a proposed algorithm for VSC controller parameters/gains. With an ITAE value of 6.8521 × 10−6, the MA-based proposed algorithm computes the optimal values and outperforms its predecessor to adjust the VSCs controller gains. For (i) wind farm power variation, (ii) AC grid load demand variation, and (iii) ultimate permanent VSC disconnection, steady-state and dynamic performances are evaluated. According to the results, the proposed algorithm based MTDC system performs well during transients.
Changes in Energy-Related Carbon Dioxide Emissions of the Agricultural Sector in Poland from 2000 to 2019
Authors: Gołaś Zbigniew
Published: June 2022

This paper analyzes the changes in carbon dioxide (CO2) emissions related to energy consumption in the Polish agricultural sector between 2000 and 2019. Based on the Logarithmic Mean Divisia Index (LMDI), the changes in agricultural CO2 emissions are viewed in the context of changes in six factors, i.e., CO2 emission intensity, substitution of fossil fuels, penetration of renewable energies, energy intensity, labor productivity and number of employees. The analysis demonstrated that total energy consumption declined over the study period; this was related to a reduction in the intake of energy derived from solid fossil fuels (−1.05%), crude oil (−1.01%), electricity (−4.89%), and heat (−1.37%), and to an increased consumption of natural gas (5.78%) and biofuels (0.82%). Furthermore, it follows from the analysis that changes in CO2 emissions witnessed in that period were consistent with changes in energy consumption levels; this resulted from a negligible transformation of the energy mix (largely determined by fossil fuels). Generally, CO2 emissions declined over the study period at a rate comparable (−0.9%) to that of the reduction in energy consumption (−1.03%). In light of the LMDI method, the reduction in CO2 emissions from fuel consumption in the Polish agricultural sector was mainly driven by a reduction in energy intensity and in employment. Conversely, rapid growth in labor productivity was the key factor in increasing carbon dioxide emissions. Compared to these impacts, changes in other factors (i.e., emission intensity, energy mix and penetration of renewable energies) had an extremely small or marginal effect on the variation in CO2 emissions.