Search Results (187)

This study systematically investigated the structural damage and electrochemical performance changes in 18650 cylindrical lithium-ion batteries under multiple impacts through a 10 kg drop-hammer impact test. The experimental results showed that as the state of charge (SOC) increased from 25% to 75%, the battery’s stiffness increased and its impact resistance improved, but the electrolyte leakage intensified, with a higher risk of leakage at high SOCs. An increase in the impact force led to enhanced voltage fluctuations and a continuous increase in deformation. After an impact of 500 mm, the voltage decreased about 0.02 V, while after an impact of 1000 mm, it dropped about 0.04 V. Axial impacts caused a sudden voltage drop to 1.96 V, resulting in permanent failure; compared with planar impacts, cylindrical surface impacts are more likely to cause compression in the middle and warping at both ends, significantly increasing the risk of internal short circuits. CT scans revealed that the battery porosity can reach up to 3.09% under high impact energy, and the deformation rate can reach 28.39%. The research results provide a quantitative experimental basis for the impact-resistant design and safety assessment of power batteries. Full article

With the ongoing advancement of triboelectric nanogenerator (TENG) technology, a novel internal integrated monitoring sensor has been introduced for traditional industrial equipment. A multilayer triboelectric material deep groove ball triboelectric nanogenerator (DGTG) device has been proposed to monitor the rotational speed and slip state of the rolling elements. The DGTG utilizes a copper inner ring charge supplementation mechanism to maintain the maximum charge density on the rolling element, thereby ensuring a strong electrical signal output. The deviation between the output frequency of the electrical signal and the theoretical value allows for effective monitoring of the slip state during bearing operation. Experimental results demonstrate that when the inner ring speed ranges from 100 to 2000 rpm, the open-circuit voltage generally remains above 30 V. The short-circuit current signal exhibits a fitting coefficient of R² = 0.99997 with respect to the roller’s rotational speed frequency and motor speed, while the open-circuit voltage signal shows a fitting coefficient of R² = 0.99984, indicating a strong linear relationship and a good response to varying speeds. Compared to the traditional photoelectric sensors commonly used in industry, the measurement difference between the three signals is consistently less than 5.5%, and real-time monitoring of the slip rate is possible when compared to the theoretical value. The DGTG developed in this study occupies minimal space, offers high reliability, and fully leverages the bearing structure, enabling real-time monitoring of bearing speed and slip. Full article

To explore possible design solutions for induction motors, we designed and tested a three-phase small-power induction motor with a can-type rotor and a stationary internal ferromagnetic core, a design not previously described in the technical literature. This three-phase motor combines certain features of a reliable solid-rotor motor, a two-rotor layer motor, and a motor in which the rotating thin aluminium layer is separated from the stationary inner ferromagnetic core. The motor prototype was based on a mass-produced, small-power, three-phase squirrel-cage motor. Its operating properties and characteristics were tested, highlighting its potential application as a special-purpose drive or a very interesting case for teaching purposes in laboratories of electrical machines. Measurements confirmed theoretical predictions and enabled the formation of a motor equivalent circuit with shunt and series branch parameters, among which magnetization reactance and rotor resistance varied with rotational speed. The main advantages of the motor are its simple rotor construction, low rotational speed, low-rotor inertia and good dynamics, as well as reliable operation across the entire range of useful torque from no-load to short-circuit conditions, without the risk of overheating. Full article

Lithium plating (LP), as a specific degradation mechanism in lithium-ion batteries (LIBs), has been thoroughly investigated regarding formation conditions and potential safety hazards, but it is yet unknown how this effect influences the mechanical properties of batteries in the case of mechanical deformation. To address this issue, pouch cells used in EVs were artificially aged (AA) to a state of health of 80–82% in conditions that predominantly cause the formation of LP. These cells were subjected to a mechanical abuse load, and safety-relevant parameters, such as tolerated deformation level, failure force, and the process of thermal runaway (TR), were analyzed and compared with respective fresh (F) and aged cells of the same type. Complementary microscopy analyses were carried out to compare the found changed mechanical response with the different layer morphology caused by LP. The tests did exhibit a significantly different mechanical response of cells in the three states but also clearly altered short-circuiting behavior. The tolerated peak force at discharge state dropped by −28% and at charge state by −37% compared to fresh cells, while the deformation at failure slightly increased by +6% for the AA cells. A clear reduction in stiffness (−16%) of the LP cells was attributed to the formed layer, identified as mossy LP. The significantly stronger voltage drop at failure, seen for the LP cells, was associated with severe exothermal reactions of LP in contact with air and moisture during TR. This study revealed the strong influence of LP on the mechanical properties of LIBs. However, the transferability of the findings to other cell chemistries or formats is unclear, emphasizing the need for further investigations in this research field. Full article

To meet the demands of deep grid integration of renewable energy and long-distance power transmission, this paper presents a hybrid multi-infeed DC system architecture that includes an AC power source (AC), a voltage source converter (VSC), and a modular multilevel converter (MMC). Addressing the limitations of traditional differential protection—such as insufficient sensitivity under high-resistance grounding and susceptibility to false operations under out-of-zone disturbances—this paper introduces an enhanced current differential criterion based on dynamic phasor analysis. By effectively decoupling DC bias and load current components and optimizing the calculation of action and braking quantities, the proposed method enables the rapid and accurate identification of typical faults, including high-resistance grounding, three-phase short circuits, and out-of-zone faults. A multi-scenario simulation platform is built using MATLAB to thoroughly validate the improved criterion. Simulation results demonstrate that the proposed method offers excellent sensitivity, selectivity, and resistance to false operations in multi-infeed complex systems. It achieves fast fault detection (~2.0 ms), strong sensitivity to high-resistance internal faults, and low false tripping under a variety of test scenarios, providing robust support for next-generation DC protection systems. Full article

The electrodynamics of current provide much of our technology, from telegraphs to the wired infrastructure powering the circuits of our electronic technology. Current flow is analyzed by its own rules that involve the Maxwell Ampere law and magnetism. Electrostatics does not involve magnetism, and so current flow and electrodynamics cannot be derived from electrostatics. Practical considerations also prevent current flow from being analyzed one charge at a time. There are too many charges, and far too many interactions to allow computation. Current flow is essential in biology. Currents are carried by electrons in mitochondria in an electron transport chain. Currents are carried by ions in nerve and muscle cells. Currents everywhere follow the rules of current flow: Kirchhoff’s current law and its generalizations. The importance of electron and proton flows in generating ATP was discovered long ago but they were not analyzed as electrical currents. The flow of protons and transport of electrons form circuits that must be analyzed by Kirchhoff’s law. A chemiosmotic theory that ignores the laws of current flow is incorrect physics. Circuit analysis is easily applied to short systems like mitochondria that have just one internal electrical potential in the form of the Hodgkin Huxley Katz (HHK) equation. The HHK equation combined with classical descriptions of chemical reactions forms a computable model of cytochrome c oxidase, part of the electron transport chain. The proton motive force is included as just one of the components of the total electrochemical potential. Circuit analysis includes its role just as it includes the role of any other ionic current. Current laws are now needed to analyze the flow of electrons and protons, as they generate ATP in mitochondria and chloroplasts. Chemiosmotic theory must be replaced by an electro-osmotic theory of ATP production that conforms to the Maxwell Ampere equation of electrodynamics while including proton movement and the proton motive force. Full article

This study investigates a lithium-ion battery failure in heating insoles that ignited during normal walking while powered off. Through comprehensive material characterization, electrical testing, thermal analysis, and mechanical gait simulation, we systematically excluded electrical or thermal abuse as failure causes. X-ray/CT imaging localized the ignition source to the lateral heel edge of the pouch cell, correlating precisely with peak mechanical stress identified through gait analysis. Remarkably, the cyclic load was less than 10% of the single crush load threshold specified in safety standards. Key findings reveal multiple contributing factors as follows: the uncoated polyethylene separator’s inability to prevent stress-induced internal short circuits, the circuit design’s lack of battery health monitoring functionality that permitted undetected degradation, and the hazardous placement inside clothing that exacerbated burn injuries. These findings necessitate a multi-level safety framework for lithium-ion battery products, encompassing enhanced cell design to prevent internal short circuit, improved circuit protection with health monitoring capabilities, optimized product integration to mitigate mechanical and environmental impact, and effective post-failure containment measures. This case study exposes a critical need for product-specific safety standards that address the unique demands of wearable lithium-ion batteries, where existing certification requirements fail to prevent real-use failure scenarios. Full article

Winding interturn short-circuit (ISCF) fault is a common problem which occurs in distribution transformers due to multiple internal and external factors. Unfortunately, the variations in electric parameters under a slight fault are tiny and hardly used as effective characteristics for the detection and protection system. To address this issue, a low-cost robust detection method of ISCF based on the port voltage–current (ΔU-I) locus characteristic is presented in this paper. The mathematical model of the three-phase distribution transformer with ISCF is first established. Then, the ΔU-I locus function and relevant characteristic parameters are analyzed, respectively, which can reflect the healthy and faulty conditions. The axis length ratio between the major axis length and the minor axis length in the ΔU-I ellipse curve is defined as the fault indicator for the sensitivity and robustness of fault diagnosis. Moreover, this method can reduce the number of sensors and has strong robustness against load fluctuations. In the end, the theoretical analysis and simulation results verify the effectiveness of the ΔU-I locus characteristic. Full article

Recurrent catastrophic inverter failures significantly undermine the reliability and economic viability of utility-scale photovoltaic (PV) power plants. This paper presents a comprehensive investigation of severe inverter destruction incidents at the Kopli Solar Power Plant, Estonia, by integrating controlled laboratory simulations with extensive field monitoring. Initially, detailed laboratory experiments were conducted to replicate critical DC-side short-circuit scenarios, particularly focusing on negative DC input terminal faults. The results consistently showed these faults rapidly escalating into multi-phase short-circuits and sustained ground-fault arcs due to inadequate internal protection mechanisms, semiconductor breakdown, and delayed relay response. Subsequently, extensive field-based waveform analyses of multiple inverter failure events captured identical fault signatures, thereby conclusively validating laboratory-identified failure mechanisms. Critical vulnerabilities were explicitly identified, including insufficient isolation relay responsiveness, inadequate semiconductor transient ratings, and ineffective internal insulation leading to prolonged arc conditions. Based on the validated findings, the paper proposes targeted inverter design enhancements—particularly advanced DC-side protective schemes, rapid fault-isolation mechanisms, and improved internal insulation practices. Additionally, robust operational and monitoring guidelines are recommended for industry-wide adoption to proactively mitigate future inverter failures. The presented integrated methodological framework and actionable recommendations significantly contribute toward enhancing inverter reliability standards and operational stability within grid-connected photovoltaic installations. Full article

Internal short-circuit (ISC) is a critical failure mode in lithium-ion (Li-ion) batteries that can trigger thermal runaway and pose serious risks to both environmental and human safety. Early-stage ISC faults are particularly challenging to detect due to their subtle characteristics and the masking effects of voltage fluctuations. To address these challenges, this study proposes a rapid and accurate ISC diagnosis method based on the connectivity-based outlier factor (COF) algorithm. The key innovation lies in the preprocessing of terminal voltage to amplify fault signatures and suppress natural fluctuations, thereby enhancing sensitivity to early anomalies. The COF algorithm is then applied to identify ISC faults in real time. Validation under urban-dynamometer driving schedule (UDDS) conditions demonstrates the method’s effectiveness: it successfully detects early ISC faults with an equivalent resistance as high as 100 Ω within 207 s of onset. This unsupervised, data-driven approach improves fault detection speed and accuracy, contributing to the advancement of safe, reliable, and sustainable LIB deployment in clean energy and transportation systems. Full article

Efficient thermal management is critical for the performance, safety, and longevity of lithium-ion batteries, particularly in new energy vehicles. This paper presents the development and application of a NiCr/NiSi thin-film thermocouple fabricated via magnetron sputtering on a polyimide substrate, aiming to provide high-precision, fast-response internal temperature measurements for lithium-ion battery systems. The thermocouple demonstrates a Seebeck coefficient of approximately 40.95 μV/°C and a repeatability error of only 0.45%, making it highly suitable for capturing transient thermal events. The main innovation of this work lies in the comprehensive integration of simulation and experimental validation to optimize the thermocouple’s performance for lithium-ion battery applications. This includes static calibration, external short-circuit, and puncture tests, which collectively confirm the thermocouple’s reliability and accuracy. Additionally, the study explores the impact of ambient temperature variations on internal battery temperatures, revealing a nearly linear increase in internal temperature with rising ambient conditions. The findings offer valuable insights for improving battery thermal management systems, establishing early warning thresholds for thermal runaway, and enhancing the overall safety of lithium-ion battery applications. Full article

Transformer winding faults (TWFs) can lead to insulation breakdown, internal short circuits, and catastrophic transformer failure. Due to their low current magnitude—particularly at early stages such as inter-turn short circuits, axial or radial displacement, or winding looseness—TWFs often induce minimal impedance changes and generate fault currents that remain within normal operating thresholds. As a result, conventional protection schemes like overcurrent relays, which are tuned for high-magnitude faults, fail to detect such internal anomalies. Moreover, frequency response deviations caused by TWFs often resemble those introduced by routine phenomena such as tap changer operations, load variation, or core saturation, making accurate diagnosis difficult using traditional FRA interpretation techniques. This paper presents a novel diagnostic framework combining Discrete Wavelet Transform (DWT) and Support Vector Machine (SVM) classification to improve the detection of TWFs. The proposed system employs region-based statistical deviation labeling to enhance interpretability across five well-defined frequency bands. It is validated on five real FRA datasets obtained from operating transformers in Gauteng Province, South Africa, covering a range of MVA ratings and configurations, thereby confirming model transferability. The system supports post-processing but is lightweight enough for near real-time diagnostic use, with average execution time under 12 s per case on standard hardware. A custom graphical user interface (GUI), developed in MATLAB R2022a, automates the diagnostic workflow—including region identification, wavelet-based decomposition visualization, and PDF report generation. The complete framework is released as an open-access toolbox for transformer condition monitoring and predictive maintenance. Full article

High-temperature pipelines, as core facilities in the fields of petrochemical and power, are constantly exposed to extreme working conditions ranging from 450 to 600 °C, facing risks of stress corrosion, creep damage, and other defects. Traditional shutdown inspections are time-consuming and costly. Meanwhile, existing electromagnetic acoustic transducers (EMATs) are restricted by their high-temperature tolerance (≤500 °C) and short-term stability (effective working duration < 5 min). This paper proposes a high-frequency circumferential guided wave (CLamb wave) EMAT based on a Halbach permanent magnet array. Through magnetic circuit optimization (Halbach array) and multi-layer insulation design, it enables continuous and stable detection on the surface of 600 °C pipelines for 10 min. The simulations revealed that the Halbach array increased the magnetic flux density by 1.4 times and the total displacement amplitude by 2 times at a magnet’s large lift-off (9 mm). The experimental results show that the internal temperature of the sensor remained stable below 167 °C at 600 °C. It was capable of detecting the smallest defect of a φ3 mm half-hole (depth half of the wall thickness), with a signal attenuation rate of only 0.32%/min. The signal amplitude of Q235 pipelines under high-temperature short-term detection (<5 min) was 1.5 times higher than that at room temperature. However, material degradation under high temperature led to insufficient long-term stability. This study breaks through the bottleneck of long-term detection of high-temperature EMATs, providing a new scheme for efficient online detection of high-temperature pipelines. Full article

As a result of the increase in the number of smart buildings and advances in technology, energy consumption in buildings has become increasingly important. The estimation of energy consumption in buildings is critical for energy efficiency. Accurate estimation of photovoltaic (PV) solar power plant efficiency is crucial for optimizing the performance of renewable energy applications. In this study, advanced machine learning regression models such as XGBoost, CatBoost, LightGBM, AdaBoost and Histogram-Based Gradient Boosting are used to predict PV efficiency based on ten internal features (Open Circuit Voltage (Voc), Short Circuit Current (Isc), Maximum Power (Pmpp), Solar Irradiation Spread (SIS), Maximum Voltage (Vmpp), Maximum Current (Impp), Fill Factor (FF), Parallel Resistance (Rp), Series Resistance (Rs), and Module Temperature (Tm)) of PV module measurements from the Utrecht University Photovoltaic Outdoor Test Facility. As a result, CatBoost outperformed the others, achieving the lowest prediction error MSE of 0.002 and the highest R² value of 0.90. To interpret the model’s predictions, we applied Explainable Artificial Intelligence techniques, in particular SHAP and LIME, which identify key features affecting efficiency and increase model transparency. The integration of these methods provides valuable insights for PV solar power plant design and optimization. Full article

In electrical power systems, shunt reactors control excess reactive power, keeping voltage levels within acceptable limits. As shunt reactors play a crucial role in the operation of electrical systems, it is essential to ensure the use of modern and fast protection schemes for these devices. Furthermore, protection functions must be capable of identifying various fault conditions, including critical operating situations such as turn-to-ground and turn faults, involving only a few short-circuited turns. This paper proposes a comparative evaluation of protection schemes commonly employed by manufacturers to meet the requirements of different grid codes. Thus, the investigation encompasses restricted earth fault, directional, differential, and distance functions. The latter is typically cited as a backup protection function. To support the analyses conducted, an electrical power system with shunt compensation was modeled in the ATPDraw software version 7.3. Through this platform, various internal fault conditions were simulated, encompassing turn-to-ground and turn faults. This facilitated the analysis of the influence of parameters such as the leakage factor value and the number of short-circuited turns. Additionally, external fault conditions were evaluated, including cases involving Current Transformer (CT) saturation. Full article