Hasil untuk "Applications of electric power"

Jinping Liu, Jian Jiang, Chuanwei Cheng et al.

Yang Zou, Puchuan Tan, Bojing Shi et al.

Soft wearable electronics for underwater applications are of interest, but depend on the development of a waterproof, long-term sustainable power source. In this work, we report a bionic stretchable nanogenerator for underwater energy harvesting that mimics the structure of ion channels on the cytomembrane of electrocyte in an electric eel. Combining the effects of triboelectrification caused by flowing liquid and principles of electrostatic induction, the bionic stretchable nanogenerator can harvest mechanical energy from human motion underwater and output an open-circuit voltage over 10 V. Underwater applications of a bionic stretchable nanogenerator have also been demonstrated, such as human body multi-position motion monitoring and an undersea rescue system. The advantages of excellent flexibility, stretchability, outstanding tensile fatigue resistance (over 50,000 times) and underwater performance make the bionic stretchable nanogenerator a promising sustainable power source for the soft wearable electronics used underwater. Flexible devices such as solar cells and nanogenerators are attractive for powering wearable electronics, but waterproof capabilities would extend applications. Here the authors report a bionic stretchable nanogenerator that is capable of harvesting energy and multi-position motion monitoring underwater.

Zhong Lin Wang

Although the contact electrification (CE) (or usually called ‘triboelectrification’) effect has been known for over 2600 years, its scientific mechanism still remains debated after decades. Interest in studying CE has been recently revisited due to the invention of triboelectric nanogenerators (TENGs), which are the most effective approach for converting random, low-frequency mechanical energy (called high entropy energy) into electric power for distributed energy applications. This review is composed of three parts that are coherently linked, ranging from basic physics, through classical electrodynamics, to technological advances and engineering applications. First, the mechanisms of CE are studied for general cases involving solids, liquids and gas phases. Various physics models are presented to explain the fundamentals of CE by illustrating that electron transfer is the dominant mechanism for CE for solid–solid interfaces. Electron transfer also occurs in the CE at liquid–solid and liquid–liquid interfaces. An electron-cloud overlap model is proposed to explain CE in general. This electron transfer model is extended to liquid–solid interfaces, leading to a revision of the formation mechanism of the electric double layer at liquid–solid interfaces. Second, by adding a time-dependent polarization term P s created by the CE-induced surface electrostatic charges in the displacement field D , we expand Maxwell’s equations to include both the medium polarizations due to electric field ( P ) and mechanical aggitation and medium boundary movement induced polarization term ( P s). From these, the output power, electromagnetic (EM) behaviour and current transport equation for a TENG are systematically derived from first principles. A general solution is presented for the modified Maxwell’s equations, and analytical solutions for the output potential are provided for a few cases. The displacement current arising from ε∂E/∂t is responsible for EM waves, while the newly added term ∂ P s/∂t is responsible for energy and sensors. This work sets the standard theory for quantifying the performance and EM behaviour of TENGs in general. Finally, we review the applications of TENGs for harvesting all kinds of available mechanical energy that is wasted in our daily life, such as human motion, walking, vibration, mechanical triggering, rotating tires, wind, flowing water and more. A summary is provided about the applications of TENGs in energy science, environmental protection, wearable electronics, self-powered sensors, medical science, robotics and artificial intelligence.

A. Haregewoin, A. Wotango, B. Hwang

Kunming Shi, Bin Sun, Xingyi Huang et al.

Abstract Piezoelectric nanogenerators (PENGs) with good flexibility and high outputs have promising and outstanding applications for harvesting mechanical energy and powering electronics. In this work, PENGs are fabricated by using electrospun nanocomposite fiber mats comprising barium titanate (BT) nanoparticles, graphene nanosheets and poly(vinylidene fluoride) (PVDF). When the nanocomposite fiber mats are composed of 0.15 wt% graphene nanosheets and 15 wt% BT nanoparticles, the open-circuit voltage and electric power of the PENG can reach as high as 11 V and 4.1 μW under a loading frequency of 2 Hz and a strain of 4 mm, and no apparent decline of the open-circuit voltage is observed after 1800 cycles in the durability test. In addition, the PENG generate a peak voltage as high as 112 V during a finger pressing-releasing process, which can light up 15 LEDs and drive an electric watch. The improved output of the PENG is ascribed to the synergistic contribution of the BT nanoparticles and graphene nanosheets to the piezoelectric performance enhancement of the nanocomposite fibers. This study shows that the nanocomposite fiber based flexible PENGs are promising mechanical energy harvesters and effective power sources for portable electronic and wearable devices.

Line A. Roald, David Pozo, Anthony Papavasiliou et al.

Y. Kumar, J. Ringenberg, S. Depuru et al.

O. Omitaomu, Haoran Niu

The smart grid is enabling the collection of massive amounts of high-dimensional and multi-type data about the electric power grid operations, by integrating advanced metering infrastructure, control technologies, and communication technologies. However, the traditional modeling, optimization, and control technologies have many limitations in processing the data; thus, the applications of artificial intelligence (AI) techniques in the smart grid are becoming more apparent. This survey presents a structured review of the existing research into some common AI techniques applied to load forecasting, power grid stability assessment, faults detection, and security problems in the smart grid and power systems. It also provides further research challenges for applying AI technologies to realize truly smart grid systems. Finally, this survey presents opportunities of applying AI to smart grid problems. The paper concludes that the applications of AI techniques can enhance and improve the reliability and resilience of smart grid systems.

G. Petrone, G. Spagnuolo, R. Teodorescu et al.

Cuo Wu, Hao Shen, Richard Schroedter et al.

ABSTRACT Reversible weight tuning is critical for edge AI chips, enabling online learning and local inference. Conventionally, the transition from analog interfacial switching to abrupt filamentary switching in memristors is commonly considered irreversible, as high electric fields induce conductive filaments, locking devices in the filamentary state. Here, we report that TiN/HfO2/Pt memristors exhibit stable interfacial switching and achieve voltage‐driven, repeatable interfacial‐to‐filamentary‐to‐interfacial (I‐F‐I) transitions. Systematic electrical characterization demonstrates more than 10 stable I‐F‐I transition sequences, controllable I‐F‐I transition yield exceeding 40%, a preserved resistance window, and an ON/OFF ratio of about 30. High bias activates a fast digital filamentary mode, while low bias restores a linearly tunable analog interfacial mode. Two defect migration models—soft filament and Schottky emission—elucidate this phenomenon. This analog‐digital switching could in the future, enable single‐chip training and inference and support reconfigurable logic‐in‐memory architectures, advancing low‐power artificial neural networks as well as neuromorphic computing for edge AI applications.

Khursheed Sabeel, Maher Al-Greer, Imran Bashir

Lithium-ion cells are increasingly being used as central power storage systems for modern applications, i.e., e-bikes, electric vehicles (EVs), satellites, and spacecraft, and they face significant and constant vibrations. This review examines how these vibrations affect the batteries’ mechanical, thermal, and electrical properties. Vibrations can cause structural issues, such as the separation of electrodes and the deformation of separators. These problems raise internal resistance and lead to localized heat generation. As a result, thermal management becomes more complicated, battery aging accelerates, and safety risks arise, including short circuits and thermal runaways. To tackle these challenges, we need more realistic testing protocols that consider the combined effects of vibrations, temperature, and mechanical stress. Improving thermal management systems (TMSs) using advanced cooling techniques and materials, e.g., phase change solutions, can help to alleviate these problems. It is also essential to design batteries with vibration-resistant materials and enhanced structural integrity to boost their durability. Moreover, vibrations play a significant role in various degradation mechanisms, including dendrite formation, self-discharge, and lithium plating, all of which can reduce battery capacity and lifespan. Our current research builds on these insights using a multiscale physics-based modeling approach to investigate how vibrations interact with thermal behavior and contribute to battery degradation. By combining computational models with experimental data, we aim to develop strategies and tools to enhance lithium-ion batteries’ safety, reliability, and longevity in challenging environments.

Oluwaseun A. Badewa, Ali Mohammadi, Donovin D. Lewis et al.

This paper introduces innovative designs for synchronous electric motors with phase coils and permanent magnets (PM) or DC-excitation coils embedded in the stator. Alongside concentrated phase coils in dedicated slots, the spoke-type PMs offer high flux intensification, while the option for DC-excitation coils eliminates demagnetization risks. Since the rotor has no active electromagnetic components, the machine can achieve high-speed operation while enabling advanced cooling systems focused solely on the stator. A special implementation with a “wave” or “serpentine” DC-excitation winding which has the potential for reduced losses depending on the motor aspect ratio is presented. The operation, control, and polarity of the DC-excited variant are analyzed using analytical equations and an examination of the airgap field. The design of experiment-based sensitivity analyses and multi-objective optimization employing differential evolution (MODE) is used to analyze the machine topologies for a power rating of 100kW motor at a speed of 3,000rpm, which is typical for industrial applications. The conflicting objectives of maximizing average torque and minimizing motor losses are considered in both the inner and outer rotor configurations of the proposed motor topologies. Discussions on the performance of the selected “best” designs from each topology and their competitiveness compared to state-of-the-art motors are presented. A DC-excited outer rotor design is analyzed and proposed for EV applications, considering different drive cycles, and a prototype of a PM inner rotor design is constructed and tested, showing competitive performance even at high operating temperatures.

Md Masum Billah, Ahmed Hemeida, Karolina Kudelina et al.

ABSTRACT This study addresses the challenges of machine learning‐based condition monitoring of induction machines under varying load conditions, which can result in low accuracy at unmeasured loading levels. A hybrid data augmentation framework is developed that combines multiple regression models and ensemble learning techniques to generate feature values at any unmeasured loading levels. The proposed method requires feature computation from only four measured loading levels under healthy, one, two and three broken rotor bars conditions as training data, enabling feature values augmentation for other loading levels. In this study, the augmentation method is applied to generate feature values at two intermediate levels (50% and 75%) and one extreme level (100%) and the corresponding results are presented. This hybrid data augmentation method not only produces accurate feature values for intermediate loading levels but also performs exceptionally well in extrapolating feature values at extreme loading levels. Incorporating this generated data during the training phase resolves generalisation issues and substantially improves the classification accuracy of machine learning models. In particular, the integration of ensemble learning techniques helped to increase accuracy from 38.75%, 42.75% and 60%–100% for the K‐nearest neighbours, support vector machine and decision tree models, respectively, at the 100% loading level.

Yuliang Zhu, Xiaobo Wang, Wenchao Xue et al.

Pb(Mg_1/3Nb_2/3)O₃-PbTiO₃ single crystals (PMN-PT SCs) are widely utilized in high-performance piezoelectric devices due to their exceptional piezoelectric properties. Among the various post-processing techniques for domain engineering in PMN-PT SCs, alternating current polarization (ACP) has become a widely adopted method for enhancing piezoelectric performance. This study proposes a new ultrahigh-temperature field-cooling polarization (UFCP) technique, combining direct current polarization (DCP) and ACP with field cooling above the Curie temperature. Dielectric spectra indicate that the UFCP method promotes electric field-induced phase transitions above the Curie point, forming a stable multiphase configuration. The transverse piezoelectric coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>d</mi></mrow><mrow><mn>31</mn></mrow></msub></mrow></semantics></math></inline-formula> of UFCP SCs is <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1126</mn><mtext> </mtext><mi mathvariant="normal">p</mi><mi mathvariant="normal">C</mi><mo>/</mo><mi mathvariant="normal">N</mi></mrow></semantics></math></inline-formula>, and the electromechanical coupling factor <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>k</mi></mrow><mrow><mn>31</mn></mrow></msub></mrow></semantics></math></inline-formula> is 0.559. Compared with traditional DCP, UFCP increases <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>d</mi></mrow><mrow><mn>31</mn></mrow></msub></mrow></semantics></math></inline-formula> by 68.6%, the mechanical quality factor <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>Q</mi></mrow><mrow><mi>m</mi></mrow></msub></mrow></semantics></math></inline-formula> by 16.7%, and the piezoelectric figure of merit (FOM) by 98.3%. Furthermore, under high-power excitation with a root-mean-square voltage of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>15</mn><mtext> </mtext><mi mathvariant="normal">V</mi></mrow></semantics></math></inline-formula>, UFCP achieves a 343% increase in power and a 130.5% improvement in the FOM compared with DCP, demonstrating its potential for enhancing high-power performance in practical applications.

Qi‐Rui Yin, Zhi‐Ting Zhou, Zhen‐Nan Fan et al.

ABSTRACT The selected electromagnetic field model of a hydro generator directly affects the calculation of the no‐load magnetic field, which in turn affects the grid‐connected power quality of the hydrogenerator and the power transmission safety. Tubular hydro generators have a horizontal structure with less internal space than the conventional vertical hydro generator, which results in a particularly complex and strong internal magnetic field distribution. This study investigated the influence of the selected electromagnetic field model on the calculation of the no‐load magnetic field of a tubular hydro generator. Straight and skewed stator slots were considered for the structure of the hydro generator. Three models were considered: the transient motion electromagnetic field‐circuit coupling model, the transient motion electromagnetic field model, and the static electromagnetic field model. The calculation accuracy and computational efficiency of the three models were evaluated by comparison to measured data. The results were used to make reasonable suggestions for the selection of a suitable electromagnetic field model in different scenarios. The findings are expected to support the electromagnetic field analysis and design of hydro generators.

Tian Yu, Xiaoyuan Wang, Qizhi Dong et al.

ABSTRACT To improve the torque performance of permanent magnet synchronous reluctance machine (PMSRM) for electric vehicles, a novel torque‐angle approximation PMSRM (TAA_PMSRM) is proposed in this article. This design utilises asymmetric permanent magnets (PMs) and inter‐pole cavity to shift the axis of PM magnetic field, so as to make the peak of the PM torque component approximate to the peak of the reluctance torque component, and to increase the resultant torque without increasing the cost. And asymmetric tangential ribs are introduced to suppress torque ripple effectively. Through the parameter sensitivity analysis, the specific influence of the key structure parameters related to the PM magnetic field shift on the electromagnetic performance of the TAA_PMSRM is clarified, providing a theoretical basis for torque performance optimisation. Based on the step‐by‐step multi‐objective optimisation design, the average torque and torque ripple are optimised while ensuring the mechanical integrity of rotor. A comparative analysis between the proposed TAA_PMSRM and the conventional PMSRM, both optimised using the same method under multiple operating conditions, confirms the torque improvement and overall performance advantages of the proposed design. Finally, a prototype of the TAA_PMSRM is fabricated and tested to validate the simulation accuracy and demonstrate its practical performance benefits.

Naeem Md Sami, Mia Naeini

Helmut Pfützner, Georgi Shilyashki, Neofitos Christodoulou

Abstract Soft magnetic lamination is produced with high width that usually is reduced by cutting. It yields permeability decreases Ɵ and loss increases r . So far, existing corresponding data is not consistent, since derived from strongly different lamination widths W . A consistent, ultra‐rapid test method is suggested, for international standardisation. It is based on a multi‐frequency single sheet tester. A 50 cm long, precisely prepared material sample of W  = 17 cm is inserted into it, for an initial measurement in non‐cut state. Then, it is cut into two 8.5 cm wide strips, for a test in cut state. Changes Ɵ and r are evaluated for induction values B up to 1.8 T. They are rapidly measured for frequencies of 50, 400 and 1000 Hz. Results from steel are described for guillotine cutting, from amorphous ribbon also for scissors. As a general tendency, Ɵ exceeds r by an order of about 3, however, with low reproducibility. Thus, standardisation is suggested for loss‐rise functions r ( B ) only. Examples of r‐functions reveal strong individual differences, as foot‐prints of different products. With increasing f , r ‐values tend to sink. With increasing B , they rise, except for high B of NO steel. Amorphous ribbon shows non‐clarified deviating tendencies. Standardisation of r‐tests promises comparable information on cutting effects, for a given material, through a given cutting tool—but also on the tool's state of wear.

WANG Yushen, CHEN Haoyong, HUANG Yuxiang et al.

ObjectivesTo address the uncertainties of renewable energy output and load faced by virtual power plant (VPP) when participating in electric energy and demand response markets, a robust optimal scheduling strategy considering multiple uncertainties was proposed to reduce the conservativeness of robust optimization and improve the economic benefits of VPP.MethodsA polyhedral uncertainty set based on conditional value at risk (CVaR) was constructed. On this basis, considering the uncertainties of wind power, photovoltaic output and load, a day-ahead two-stage robust optimization model of VPP participating in electric energy and demand response markets was established. Then, using a column-and-constraint generation (C&CG) algorithm and Lagrangian dual theory, the model was divided into a master problem and a sub-problem that can be solved by a solver. Finally, Monte Carlo method was used to generate a large number of wind power, photovoltaic and load data. The proposed strategy was simulated and analyzed, and compared with the optimization results of other schemes.ResultsThe proposed strategy adopting a polyhedral uncertainty set based on CVaR can make full use of historical data. Compared with the scheme using traditional uncertainty set, the total cost of VPP is reduced by about 2%.ConclusionsThe proposed strategy can significantly reduce the conservativeness of robust optimization results and enhance the economy of VPP participation in the market under multiple uncertainties.

Moien Masoumi, Alex Tsao, Charitha Abeyrathne et al.

Abstract This paper introduces a technique aimed at improving the performance of an interior permanent magnet synchronous machine (IPMSM) by reducing torque ripple and radial force harmonics. Unlike conventional IPMSMs, the proposed method employs a variable airgap length that is defined by a mathematical function. Two distinct rotor shapes are investigated to determine the most efficient design. Finite Element Analysis is employed to assess both the electromagnetic and mechanical attributes of the proposed motors. It compares the results for three operating points of the shaped motor with those of a conventional one. The investigation delves into the influence of rotor geometry on key output parameters, including Back Electromotive Force (back‐EMF) harmonics, average torque, cogging torque, torque ripple, efficiency, power factor, and radial force harmonics. The findings indicate that optimising rotor shape can significantly enhance IPMSM performance by reducing torque ripples and radial force harmonics, while simultaneously increasing average torque and efficiency at different operating points.