Energy Efficient Transmission Research Articles

Research on the New Hydrostatic Transmission System of Wheel Loaders Based on Fuzzy Sliding Mode Control

To improve the control performance and energy efficiency of the hydrostatic transmission (HST) system of wheel loaders, this study proposes a novel variable structure dual-motor hydrostatic transmission system, accompanied by a multivariable control strategy based on fuzzy sliding mode control. By constructing a simulation model of the transmission system, the performance of the novel transmission system is verified, and the control effects of common control strategies are compared. The simulation results show that the proposed control strategy and system have good matching and can adapt to disturbances actively. Field experiment results show that the proposed solution can achieve smooth automatic shifting of wheel loaders, while effectively adjusting system pressure, flow, and power. Compared with the traditional hydrodynamic torque converter loader transmission system, its transmission efficiency is effectively increased by 30%, and the efficiency is increased by 8% compared with the traditional hydrostatic transmission system This achievement is of great significance for improving the working efficiency of wheel loaders and reducing energy consumption. The future research focus is to further improve the multivariable control strategy, achieve intelligent operation, and improve the efficiency and reliability of the transmission system.

Stepless space-regulation of topological acoustic controller with high fault tolerance

In this paper, the stepless space-regulation of topological acoustic transmission channels with high fault tolerance is proposed through introducing structural defect dislocations into a topological acoustic controller. Due to the stability of topological order against local disturbance, the acoustic wave transmission is immune to dislocation boundaries with strong stability, and thus the topological acoustic controller has high fault tolerance. By continuous changing the dislocation, the position relationship between the outgoing and incident acoustic signals no longer limited to the integer multiple distance related to the lattice size, and can realize the efficient acoustic energy transmission without energy loss at the fractional multiple distance, that is, the topological controller can realize lossless acoustic energy transmission and reception in arbitrary position relationship. Furthermore, the coupling relationship between the defect dislocation and the topological acoustic channel is explored, which can realize the stepless space-regulation of the lossless channel in the wide band range. In addition, by further introducing multi-layer continuous dislocations, this high-fault-tolerant topological acoustic controller still has strong stability, and multiple error factors do not affect the transmission results, which greatly reduces the difficulty of manufacturing. Finally, the stepless space-regulation of topological acoustic channels and the high-fault-tolerant topological acoustic controller that are easy to manufacture are verified by our experiments. This research paves the way for the engineering applications of acoustic micro-control, micro-nano fabrication, remote acoustic energy transmission manipulation, acoustic measurement, weak signal processing, acoustic flexible control and other micro-shape and multi-functional acoustic devices, and will bring more inspiration to other classical wave communication fields such as light wave, electromagnetic wave and so on.

Developmental transformation of Ca2+ channel-vesicle nanotopography at a central GABAergic synapse

The coupling between Ca2+ channels and release sensors is a key factor defining the signaling properties of a synapse. However, the coupling nanotopography at many synapses remains unknown, and it is unclear how it changes during development. To address these questions, we examined coupling at the cerebellar inhibitory basket cell (BC)-Purkinje cell (PC) synapse. Biophysical analysis of transmission by paired recording and intracellular pipette perfusion revealed that the effects of exogenous Ca2+ chelators decreased during development, despite constant reliance of release on P/Q-type Ca2+ channels. Structural analysis by freeze-fracture replica labeling (FRL) and transmission electron microscopy (EM) indicated that presynaptic P/Q-type Ca2+ channels formed nanoclusters throughout development, whereas docked vesicles were only clustered at later developmental stages. Modeling suggested a developmental transformation from a more random to a more clustered coupling nanotopography. Thus, presynaptic signaling developmentally approaches a point-to-point configuration, optimizing speed, reliability, and energy efficiency of synaptic transmission.

Trust Aware Nero Fuzzy Based Agglomerative Hierarchical Clustering with Secure Whale Optimization Routing for Enhancing Energy Efficiency in WSN

Wireless sensor networks (WSNs) comprise a network of dispersed, carefully positioned sensor nodes in their deployment environment to monitor and collect data on natural phenomena. These sensor nodes collaborate to transmit data via multi-hop communication, ultimately reaching a central base station for processing. However, WSNs face significant challenges due to the resource-constrained nature of these devices and the harsh, open environments in which they operate. Addressing energy optimization and ensuring secure communication are primary concerns in the successful operation of WSNs. This paper introduces anovelTrust aware Neuro Fuzzy Clustering head selection (TNFCH) and agglomerative hierarchical clustering approach (AHC) with Secure Whale Optimization (SWO) Algorithm Routing to enhance energy-efficient transmission in WSNs. Our proposed protocol (TNFCH-AHWO) efficiently organizes nodes by utilizing neural network and Fuzzy logic then securely transfers the data into the communication network. We employ a Trust calculation algorithm in our system to ensure Trust and data integrity, facilitating efficient lightweight operations such as key generation, encryption, decryption, and verification. This ensures hop-to-hop authentication among the nodes in WSNs. To assess the performance of our proposed protocol, we conducted simulations using the NS3 simulator. The findings of the simulation show that the suggested protocol greatly enhances various performance metrics, including energy consumption analysis, throughput, network delay, network lifetime, and packet delivery ratio when compared to existing protocols.

Research of thermal load in an energy efficient mechatronic truck transmission considering energy losses

The article examines the heating of a truck’s energy efficient mechatronic transmission during operation of an electric motor in maximum power mode. Particular attention is paid to the process of modeling conjugate heat transfer and its impact on the energy efficiency of mechatronic transmission. To solve this problem, computational fluid dynamics (CFD) methods are used, in particular the finite volume method (FVM), which allows for an accurate assessment of heat flows between different environments inside the transmission. Analysis of thermodynamic processes occurring in mechatronic transmission is of great importance for optimizing its operation and increasing reliability. The simulation results demonstrate the influence of various factors, such as driving speed, loads and temperature conditions, on the efficiency of heat exchange and, as a result, on the energy efficiency of the entire vehicle. These research contribute to the development of more efficient cooling systems and improved performance of trucks.

ВЛИЯНИЕ ВЛАЖНОСТИ ОБРАБАТЫВАЕМОГО ЗЕРНА НА РАСПРЕДЕЛЕНИЕ ПОЛЯ СВЧ ОТ ПОЛУКРУГЛЫХ ЩЕЛЕВЫХ ВОЛНОВОДОВ

This article focuses on the utilization of microwave fields in installations for drying, pre-sowing treatment, and grain disinfection to enhance productivity and reduce energy consumption. The study examines the design of semi-circular waveguides with slotted radiators for the uniform distribution of microwave fields in a dense grain layer. Additionally, the research investigates the influence of grain moisture on the efficiency of microwave-convective installations. Using the CST Microwave Studio software, the effect of moisture on the distribution of microwave fields in the grain layer and energy transmission efficiency was investigated. The results showed that as the moisture content of the processed grain increased from 14 % to 26 %, the radiation efficiency decreased by 15.1 %, and the overall radiation efficiency decreased. Moisture variation also leads to changes in the characteristics of radiation efficiency with changes in the magnetron emission frequency.

Определение качества и энергоэффективности передачи электрической энергии низкого напряжения

Providing consumers with high quality electric power with minimum transmission losses is one of the problems of electric power transmission through power grids. Increasing reactive power of electric consumers, estimated by the load power factor, results in an increase in electricity losses and quality deterioration. To evaluate the influence of the load power factor on the transmission of active load power and to determine the quality and energy efficiency of electricity transmission through power lines, the authors analyzed the change in the parameters of one phase of a three-phase network without compensation and with reactive power compensation. The set task was solved using methods of calculation of linear electric circuits of alternating current, according to the given values of total or active load power, its resistance and the resistance of power line wires. Then the processes of power transmission in low-voltage electric networks of alternating current were simulated using the Electronics Workbench software. The authors take a case of the electric power system consisting of consumers’ (load) electric receptors receiving power supply through the power line connected to the low-voltage busbars of the power transformer. They prove that its parameters are mainly changed when changing the value of the system current determined by the load and transmission line resistances. The quality of low-voltage electrical energy transmission depends on the voltage loss in the power line wires and is determined by the load current and its full resistance. The energy efficiency of electrical energy transmission depends on the power loss in the power line wires and is determined by the amount of active power consumed by the load and the ratio of the active resistance of the power line and the load.

Statistical evaluation of regenerative braking of trucks with energy efficient mechatronic transmission

The article assesses the capabilities of regenerative braking in terms of braking efficiency when studying the motion of a model of an energy-efficient electric vehicle with a mechatronic transmission using motion cycles recorded on real vehicles. Based on statistical data, a study of driving conditions was conducted, the required braking power and the required braking deceleration were calculated, and the obtained requirements were compared with the capabilities of the traction motors installed on the vehicle, taking into account the peak short-term characteristic. Based on the results of the work, a conclusion was made that the use of energy-efficient traction electric motors allows in 86% of cases to do without using the service braking system, providing the required level of deceleration according to the studied motion cycles, which fully corresponds to serial models of electric trucks.

Delay Aware 6TiSCH IIoT Networks for Energy Efficient Data Transmission by Adopting Federated Learning and Edge Computing

Delay Aware 6TiSCH IIoT Networks for Energy Efficient Data Transmission by Adopting Federated Learning and Edge Computing

Research on acoustic control of coupled vibration system of transducers using acoustic surface and topological defect structures

<sec>How to regulate the sound waves in the coupled vibration system of complex power ultrasonic transducers and design high-performance transducer systems has always been an urgent problem in the field of power ultrasound. Research has found that introducing various defects within the transducer system can improve the performance of the transducer coupled vibration system to a certain extent. However, the drawbacks of high loss, narrow frequency band, and sensitivity to structural parameters limit the further practical application of defect type phononic crystal transducer coupled vibration systems.</sec><sec>In order to improve the limitations of the coupled vibration system of defect-type phononic crystal transducers, effectively reduce energy loss, and enhance the efficiency of energy transmission, this paper introduces a topological defect structure with energy localization effect and a sound surface structure with high energy transmission efficiency into the coupled vibration system of the transducer. In this study, the acoustic surface structure and topological defect structure are used to excite defect states with energy localization effects and high energy transmission efficiency surface states, effectively regulating the vibration of the transducer coupled vibration system, and constructing a transducer coupled vibration system with high quality factor, low loss, and high energy transmission efficiency. By flexibly designing the geometric size parameters of the acoustic surface structure and defects, the vibration of the transducer coupled vibration system can be effectively controlled, thereby meeting the different functional requirements of the transducer coupled vibration system.</sec><sec>However, due to the excessive design parameters of surface structure and topological defect structure, the complexity of the design will be multiplied, greatly reducing the success rate of the design. Therefore, this study uses data analysis technology to establish a performance prediction model for the transducer coupled vibration system, in order to achieve the accurate prediction of system performance and change the shortcomings of low design efficiency and low success rate brought by traditional empirical trial and error methods.</sec><sec>In order to verify the effectiveness of the research, the coupled vibration system of the transducer is studied in simulation and experiment in this work. The simulation and experimental results indicate that the acoustic surface structure and topological defect structure can effectively regulate sound waves to improve the performance of the transducer coupled vibration system.</sec>

1177Optimized Energy Utilization in Cognitive Radio Networkswith Congestion Control

Various real-time applications can be handled through wireless sensor networks, which consist of a wide range of sensor nodes. A novel congestion control mechanism is proposed on optimized rates for energy-efficient transmissions. To reduce energy consumption across the network, a rate-based congestion control algorithm based on cluster routing is presented. By reducing the end-to-end delay, rate control improves the network life time over a large simulation period. Clustering is initially performed using novel routing algorithms. After that, rate control is implemented using an energy optimization strategy suitable for high packet delivery ratios. Finally, packets are sent with maximum throughput using regionOptimization-driven routing. The simulation is performed on the NS2 simulation platform. Finally, performances are evaluated with respect to average delay in end to end nodes, delivery ratio ofpackets, throughput, energy efficiency, energy consumption and reliability. Novel routing with an energy optimal algorithm (NREOA) reduces energy consumption as the network progresses and a variation of 20% compared with existing protocols.

Hybrid MRT and ZF Learning for Energy-Efficient Transmission in Multi-RIS-Assisted Networks

Hybrid MRT and ZF Learning for Energy-Efficient Transmission in Multi-RIS-Assisted Networks

A novel self‐interference cancellation architecture based on asymmetrical power divider and its closed‐loop control

AbstractThe asymmetric radio frequency (RF) self‐interference cancellation (SIC) architecture is studied, and the closed‐loop control of RF SIC based on software radio is realized. This system uses a circulator to isolate the receiving and transmitting chains, and its RF reconstruction chain is composed of a 4‐tap filter with fixed delay and tunable attenuation for each tap. The optimization of tap filter and asymmetric power divider's power allocation ratio is discussed. In the experiment, sensing, calibration, optimization algorithms and hardware control programs were proposed. A closed‐loop gradient descent algorithm for tuning the variable attenuator is implemented on the GNU Radio. From 910 MHz to 930 MHz, the isolation between the receiving and transmitting ports increases 40 dB, achieving an isolation of more than 65 dB and the transmission energy efficiency increases by 60%.

Game-Theoretic Optimization Of Intelligent Iot Networks For Enhanced Resource Management In Precision Agriculture

The burgeoning application of Internet of Things (IoT) technologies in agriculture has revolutionized precision farming practices. Intelligent IoT networks equipped with sensors, actuators, and edge computing capabilities offer real-time monitoring and intelligent control over crucial agricultural parameters. However, optimizing resource allocation and network performance in these dynamic environments remains a complex challenge due to competing interests among network devices and potential interference between neighboring farms. This paper proposes a novel approach for optimizing intelligent IoT networks in precision agriculture using game theory. We first model the network as a non-cooperative game where individual devices act as rational players aiming to maximize their own utilities, represented by factors like data transmission success, energy efficiency, and resource utilization. We then employ Nash equilibrium and its refinements to determine stable and efficient network configurations. To address the potential for strategic manipulation and ensure collective benefit, we further introduce cooperative game mechanisms, such as coalition formation and resource sharing protocols, to incentivize collaborative behavior among devices. The efficacy of the proposed approach is evaluated through extensive simulations with realistic agricultural scenarios. Results demonstrate significant improvements in network performance metrics, including higher data throughput, reduced energy consumption, and improved resource utilization compared to traditional non-game-theoretic approaches. We conclude by discussing the real-world implementation challenges and future research directions in game-theoretic optimization of intelligent IoT networks for sustainable and efficient precision agriculture.

Significance of nanoparticle shape factors on MHD nanofluid flow across a slender surface

ABSTRACT This research scrutinizes the significance of nanoparticle shapes over the magnetized flow of engine-oil-based Ti6Al4V nanoliquid across a surface of varied thickness under the action of Buongiorno slip effects. The transmuted dimensionless equations and edge restrictions are exercised using the bvp5c scheme. This research’s prime purpose is to enhance the thermal transmission rate due to the suspension of spherical- or laminar-shaped nanoparticles (SSNs) or (LSNs) into the base liquid. The computational outcomes for flow, energy, and concentration fields were explored via plots and numerical illustrations. Evidently, energy transmission efficiency is developed in SSNs as compared with LSNs. The Buongiorno slip and nonuniform heat source factors tend to enrich the Nusselt number. The shape factor of nanoparticles is significant in enhancing or diminishing the heat flow rate.

An energy-aware heart disease prediction system using ESMO and optimal deep learning model for healthcare monitoring in IoT

ABSTRACT: The Internet of Things (IoT), which provides seamless connectivity between people and things, improves our quality of life. In the medical field, predictive analytics can help transform a reactive healthcare (HC) strategy into a proactive one. The HC industry embraces cutting-edge artificial intelligence and machine learning (ML) technologies. ML’s area of deep learning has the revolutionary potential to reliably analyze massive volumes of data quickly, produce insightful revelations and solve challenging issues. This article proposes an energy-aware heart disease prediction (HDP) system based on enhanced spider monkey optimization (ESMO) and a weight-optimized neural network for an IoT-based HC environment. The proposed work consists of two essential phases: energy-efficient data transmission and HDP. In energy-efficient transmission, the cluster leaders are optimally selected using ESMO and the cluster formation is done based on Euclidean distance. In HDP, the patient data are collected from the dataset, and essential features are extracted. After that, the dimensionality reduction is carried out using the modified linear discriminant analysis approach to reduce over-fitting issues. Finally, the HDP uses the enhanced Archimedes weight-optimized deep neural network (EAWO-DNN). The simulation findings demonstrate that the proposed optimal clustering mechanism enhances the network’s lifespan by consuming minimal energy compared to the existing techniques. Also, the proposed EAWO-DNN classifier achieves higher prediction accuracy, precision, recall and f-measure than the conventional methods for predicting heart disease in IoT. Communicated by Ramaswamy H. Sarma

Retracted: A High-Efficiency Deep-Learning-Based Antivibration Hammer Defect Detection Model for Energy-Efficient Transmission Line Inspection Systems

Retracted: A High-Efficiency Deep-Learning-Based Antivibration Hammer Defect Detection Model for Energy-Efficient Transmission Line Inspection Systems

Hybrid Compression Algorithm for Energy Efficient Image Transmission in Wireless Sensor Networks Using SVD-RLE in Voluminous Data Applications

Hybrid Compression Algorithm for Energy Efficient Image Transmission in Wireless Sensor Networks Using SVD-RLE in Voluminous Data Applications

Impact of Power Consumption Models on the Energy Efficiency of Downlink NOMA Systems

While non-orthogonal multiple access (NOMA) improves spectral efficiency, it adds complexity to the receivers due to successive interference cancellation (SIC). Prior studies on the energy efficiency of NOMA overlook the SIC overhead and rely on simplistic power consumption models (PCM). To fill this gap, we first introduce PCM-κ that accounts for SIC-related power expenditure. Then, to investigate the energy efficiency of NOMA and joint transmission (JT)-coordinated multipoint (CoMP) NOMA, we formulate a power allocation problem for maximizing the energy efficiency and propose a global approach running at a centralized entity and a local algorithm running at a base station. We evaluate the energy efficiency using PCM-κ and two PCMs commonly used in the literature. Numerical analysis suggests that using simplistic PCMs leads to a few orders of magnitude overestimation of energy efficiency, especially when the receivers have low rate requirements. Despite the superiority of JT-CoMP NOMA over conventional NOMA in finding a feasible power allocation, the difference in their energy efficiency is only marginal when users have identical rate requirements and more significant in more heterogeneous settings with users having different rate requirements. Moreover, when conventional NOMA is feasible, the optimal solution for JT-CoMP NOMA converges to conventional NOMA.

Energy efficient data transmission using multiobjective improved remora optimization algorithm for wireless sensor network with mobile sink

<span lang="EN-US">A wireless sensor network (WSN) is a collection of nodes fitted with small sensors and transceiver elements. Energy consumption, data loss, and transmission delays are the major drawback of creating mobile sinks. For instance, battery life and data latency might result in node isolation, which breaks the link between nodes in the network. These issues have been avoided by means of mobile data sinks, which move between nodes with connection issues. Therefore, energy aware multiobjective improved remora optimization algorithm and multiobjective ant colony optimization (EA-MIROA-MACO) is proposed in this research to improve the WSN’s energy efficiency by eliminating node isolation issue. MIRO is utilized to pick the optimal cluster heads (CHs), while multiobjective ant colony optimization (MACO) is employed to find the path through the CHs. The EA-MIROA-MACO aims to optimize energy consumption in nodes and enhance data transmission within a WSN. The analysis of EA-MIROA-MACO’s performance is conducted by considering the number of alive along with dead nodes, average residual energy, and network lifespan. The EA-MIROA-MACO is compared with traditional approaches such as mobile sink and fuzzy based relay node routing (MSFBRR) protocol as well as hybrid neural network (HNN). The EA-MIROA-MACO demonstrates a higher number of alive nodes, specifically 192, over the MSFBRR and HNN for 2,000 rounds.</span>