Search Results (853)

In this paper, the concept of symmetry is utilized to design active fault tolerant trajectory-tracking control of autonomous distributed-drive electric vehicles—that is, the construction and the solution of active fault tolerant trajectory-tracking controllers are symmetrical. This paper presents a hierarchical fault tolerant control strategy for improving the trajectory-tracking performance of autonomous distributed-drive electric vehicles (ADDEVs) under steer-by-wire (SBW) system failures. Since ADDEV trajectory dynamics are inherently affected by complex traffic conditions, various driving maneuvers, and other road environments, the main control objective is to deal with the ADDEV trajectory-tracking control challenges of system uncertainties, SBW failures, and external disturbance. First, the differential steering dynamics model incorporating a 3-DOF coupled system and stability criteria based on the phase–plane method is established to characterize autonomous vehicle motion during SBW failures. Then, by integrating cascade active disturbance rejection control (ADRC) with Karush–Kuhn–Tucker (KKT)-based torque allocation, the active fault tolerant control framework of trajectory tracking and lateral stability challenges caused by SBW actuator malfunctions and steering lockup is addressed. The upper-layer ADRC employs an extended state observer (ESO) to estimate and compensate against uncertainties and disturbances, while the lower-layer utilizes KKT conditions to optimize four-wheel torque distribution to compensate for SBW failures. Simulations validate the effectiveness of the controller with serpentine and double-lane-change maneuvers in the co-simulation platform MATLAB/Simulink-Carsim^® (2019). Full article

Over the last few decades, polymer composites have been rapidly making inroads in critical applications of electrical storage devices such as batteries and supercapacitors. Structural supercapacitor composites (SSCs) have emerged as multifunctional materials capable of storing energy while bearing mechanical loads, offering lightweight and compact solutions for energy systems. This study investigates the functionalization of Bisphenol A-based thermosetting polymers with ionic liquids, aiming to synthesize dual-functional structural electrolytes for SSC fabrication. A multifunctional sandwich structure was subsequently fabricated, in which the fabricated SSC served as the core layer, bonded between two structurally robust outer skins. The core layer was fabricated using carbon fibre layers coated with 10% graphene nanoplatelets (GNPs), while the skin layers contained 0.25% GNPs dispersed in the resin matrix. The developed device demonstrated stable operation up to 85 °C, achieving a specific capacitance of 57.28 mFcm⁻² and an energy density of 179 mWhm⁻² at room temperature. The performance doubled at 85 °C, maintaining excellent capacitance retentions across all experimented temperatures. The flexural strength of the developed sandwich SSC at elevated temperature (at 85 °C) was 71 MPa, which exceeds the minimum requirement for roofing sheets as specified in Australian building standard AS 4040.1 (Methods of testing sheet roof and wall cladding, Method 1: Resistance to concentrated loads). Finite element analysis (FEA) was performed using Abaqus CAE to evaluate structural integrity under mechanical loading and predict damage initiation zones under service conditions. The simulation was based on Hashin’s failure criteria and demonstrated reasonable accuracy. This research highlights the potential of multifunctional polymer composite systems in renewable energy infrastructure, offering a robust and energy-efficient material solution aligned with circular economy and sustainability goals. Full article

Electrical networks face operational challenges from power quality-affecting disturbances. Since disturbance signatures directly affect classifier performance, optimized feature selection becomes critical for accurate power quality assessment. The pursuit of robust feature extraction inevitably constrains the dimensionality of the discriminative feature set, but the complexity of the recognition model will be increased and the recognition speed will be reduced if the feature vector dimension is too high. Building upon the aforementioned requirements, in this paper, we propose a feature extraction framework that combines improved symplectic geometric mode decomposition, refined generalized multiscale quantum entropy, and refined generalized multiscale reverse dispersion entropy. Firstly, based on the intrinsic properties of power quality disturbance (PQD) signals, the embedding dimension of symplectic geometric mode decomposition and the adaptive mode component screening method are improved, and the PQD signal undergoes tri-band decomposition via improved symplectic geometric mode decomposition (ISGMD), yielding distinct high-frequency, medium-frequency, and low-frequency components. Secondly, utilizing the enhanced symplectic geometric mode decomposition as a foundation, the perturbation features are extracted by the combination of refined generalized multiscale quantum entropy and refined generalized multiscale reverse dispersion entropy to construct high-precision and low-dimensional feature vectors. Finally, a double-layer composite power quality disturbance model is constructed by a deep extreme learning machine algorithm to identify power quality disturbance signals. After analysis and comparison, the proposed method is found to be effective even in a strong noise environment with a single interference, and the average recognition accuracy across different noise environments is 97.3%. Under the complex conditions involving multiple types of mixed perturbations, the average recognition accuracy is maintained above 96%. Compared with the existing CNN + LSTM method, the recognition accuracy of the proposed method is improved by 3.7%. In addition, its recognition accuracy in scenarios with small data samples is significantly better than that of traditional methods, such as single CNN models and LSTM models. The experimental results show that the proposed strategy can accurately classify and identify various power quality interferences and that it is better than traditional methods in terms of classification accuracy and robustness. The experimental results of the simulation and measured data show that the combined feature extraction methodology reliably extracts discriminative feature vectors from PQD. The double-layer combined classification model can further enhance the model’s recognition capabilities. This method has high accuracy and certain noise resistance. In the 30 dB white noise environment, the average classification accuracy of the model is 99.10% for the simulation database containing 63 PQD types. Meanwhile, for the test data based on a hardware platform, the average accuracy is 99.03%, and the approach’s dependability is further evidenced by rigorous validation experiments. Full article

In recent times, copper oxide nanosheets (CONSs) have shown a broad spectrum of industrial uses due to their unique properties, including high electrical conductivity, surface-enhanced catalytic activity, etc. Therefore, industrial processes involved in their manufacture can give rise to airborne particulates. Several in vivo studies have reported toxicity of these nanoparticles due to their interactions with biological molecules. Generally, literature-based assessment of their toxicity has centered on experimental findings. In this paper, we report for the first time, trend in CONSs interactions in intracellular and extracellular fluids, using the Nonlinear Mean Field Poisson–Boltzmann theory. Our theoretical prediction for zeta potential in the extracellular fluid environment align with published values in the literature. Based on this theoretical approach, we also demonstrate that double layer disjoining pressure due to interacting double layers of CONSs is generally higher in intracellular fluids. The findings of our theoretical approach highlight the importance of predicting the extent of cellular uptake potential of CONSs in organs that are prone to such airborne environmental particulates. Full article

This paper compares two types of interior permanent magnet synchronous motors (IPMSMs) to determine the most effective arrangement for electric vehicle (EV) applications. The comparison is based on torque ripple, power, efficiency, and mechanical objectives. The study introduces a novel technique that optimizes notching parameters in a selected motor topology by inserting a ship-shaped notch into the bridge area between double U-shaped layers. In addition, this study presents two comprehensive approaches of robust combinatorial optimization that are used in machines for the first time. In the first approach, modeling is performed to identify important variables using Pearson Correlation and the mathematical model of the Anisotropic Kriging model from the Surrogate model. Then, in the second approach, the proposed algorithm, Multi-Objective Genetics Algorithm (MOGA), and Surrogate Quadratic Programming (SQP) are combined and implemented on the Anisotropic Kriging model to choose a robust model with minimum error. The algorithm is then verified with FEM results and compared with other conventional optimization algorithms, such as the Genetics Algorithm (GA) and the Particle Swarm Optimization algorithm (PSO). The motor characteristics are analyzed using the Finite Element Method (FEM) and global map analysis to optimize the performance of the IPMSM for EV applications. A comparative study shows that the enhanced PMSM developed through the optimization process demonstrates superior performance indices for EVs. Full article

Capacitive deionization (CDI) is a novel water treatment technology based on the principle of double-electric-layer adsorption, which stores ions in the solution on the surface of electrodes by applying a low potential difference to achieve desalination. CDI has the advantages of low operating voltage (<1.2 V), small equipment footprint, low energy consumption, low cost and environmental friendliness. The performance of CDI is heavily dependent on the electrode materials. Carbon-based materials are widely used in CDI systems because of the large specific surface areas, lower price, and remarkable stability. To improve the CDI performance, extensive research efforts have been made for the modification of carbon-based materials. Defects in carbon-based materials play an important role in electrochemical processes and the introduction of defects is an important method to modify carbon-based materials. However, there is a lack of systematic summary of modification of carbon-based materials through introducing defects in CDI system. Therefore, this study makes the first attempt to review the modification of carbon-based materials of CDI based on defect engineering. The mechanism of enhancing CDI performance of carbon-based materials with the induction of different defects is analyzed and the future research prospects are proposed. Full article

Waterflooding, a key method for secondary hydrocarbon recovery, has been employed since the early 20th century. Over time, the role of water chemistry and ions in recovery has been studied extensively. Low-salinity water (LSW) injection, a common technique since the 1930s, improves oil recovery by altering the wettability of reservoir rocks and reducing residual oil saturation. Recent developments emphasize the integration of LSW with various recovery methods such as CO₂ injections, surfactants, alkali, polymers, and nanoparticles (NPs). This article offers a comprehensive perspective on how LSW injection is combined with these enhanced oil recovery (EOR) techniques, with a focus on improving oil displacement and recovery efficiency. Surfactants enhance the effectiveness of LSW by lowering interfacial tension (IFT) and improving wettability, while ASP flooding helps reduce surfactant loss and promotes in situ soap formation. Polymer injections boost oil recovery by increasing fluid viscosity and improving sweep efficiency. Nevertheless, challenges such as fine migration and unstable flow persist, requiring additional optimization. The combination of LSW with nanoparticles has shown potential in modifying wettability, adjusting viscosity, and stabilizing emulsions through careful concentration management to prevent or reduce formation damage. Finally, building on discussions around the underlying mechanisms involved in improved oil recovery and the challenges associated with each approach, this article highlights their prospects for future research and field implementation. By combining LSW with advanced EOR techniques, the oil industry can improve recovery efficiency while addressing both environmental and operational challenges. Full article

Nanofluidic memristors are an emerging class of devices that harness ion transport in confined nanoscale environments to achieve tunable resistance states, mimicking biological synaptic functions. The regulation of ion migration, accumulation, and depletion in nanofluidic channels is fundamentally governed by chemical principles, including surface charge modulation, electrostatic interactions, and ion adsorption and desorption processes. This review provides a comprehensive overview of the chemical foundations of nanofluidic memristors, including electric double layer theory, ion transport dynamics, and interfacial chemistry. Additionally, this review further explores how interfacial chemical modifications, such as functionalization with charged species, pH-responsive coatings, and ionic selectivity molecules, influence nanofluidic memristive behaviors. Representative case studies are discussed to illustrate the practical implementation of these principles in applications ranging from neuromorphic computing to biosensing and energy storage. By bridging fundamental chemical theories with real-world applications, this review aims to provide insights into the rational design of next-generation nanofluidic memristive devices. Full article

Electrochemical water splitting for hydrogen production is considered a key pathway for achieving sustainable energy conversion. However, the sluggish reaction kinetics of the oxygen evolution reaction (OER) and high overpotentials severely hinder the large-scale application of water electrolysis technology. Nickel–iron layered double hydroxide (NiFe-LDH) has gained attention as a promising non-precious metal OER catalyst due to its abundant active sites and good intrinsic activity. However, its relatively low conductivity and charge transfer efficiency limit the improvement of catalytic performance. Therefore, this study used a simple hydrothermal method to generate a NiFe-LDH/Cs_0.32WO₃ heterojunction composite catalyst, relying on the excellent electronic conductivity of Cs_0.32WO₃ to improve overall charge transfer efficiency. According to electrochemical testing results, the modified NiFe-LDH/Cs_0.32WO₃-20 mg achieved a low overpotential of 349 mV at a current density of 10 mA cm⁻², a Tafel slope of 67.0 mV dec⁻¹, and a charge transfer resistance of 65.1 Ω, which represent decreases of 39 mV, 23.1%, and 40%, respectively, compared to pure NiFe-LDH. The key to performance improvement lies in the tightly bonded heterojunction interface between Cs_0.32WO₃ and NiFe-LDH. X-ray photoelectron spectroscopy (XPS) shows a distinct interfacial charge transfer phenomenon, with a notable negative shift of the W4f peak (0.85 eV), indicating the directional transfer of electrons from Cs_0.32WO₃ to NiFe-LDH. Under the influence of the built-in electric field within the heterojunction, this interfacial charge redistribution improved the electronic structure of NiFe-LDH, increased the proportion of high-valent metal ions, and significantly enhanced the OER reaction kinetics. This study provides new insights for the preparation of efficient heterojunction electrocatalysts. Full article

The electromechanical composite transmission technology for tracked vehicles demonstrates excellent performance in energy efficiency, mobility, and ride comfort. However, due to frequent operation under harsh conditions, the components of the electric drive system, such as drive motors, are prone to failures. This paper proposes three fault-tolerant control methods for three typical fault scenarios of the electromechanical composite transmission system (ECTS) to ensure the normal operation of tracked vehicles. Firstly, an ECTS and the electromechanical coupling dynamics model of the tracked vehicle are established. Moreover, a double-layer anti-windup PID control for motors and an instantaneous optimal control strategy for the engine are proposed in the fault-free case. Secondly, an anti-windup PID control law for motors and an engine control strategy considering the state of charge (SOC) and driving demands are developed in the case of single-side drive motor failure. Thirdly, a B4 clutch control strategy during starting and a steering brake control strategy are proposed in the case of electric drive system failure. Finally, in the straight-driving condition of the tracked vehicle, the throttle opening is set as 0.6, and the motor failure is triggered at 15 s during the acceleration process. Numerical simulations verify the fault-tolerant control strategies’ feasibility, using the tracked vehicle’s maximum speed and acceleration at 30 s as indicators for dynamic performance evaluation. The simulation results show that under single-motor fault, its straight-line driving power drops by 33.37%; with electric drive failure, the drop reaches 43.86%. The vehicle can still maintain normal straight-line driving and steering under fault conditions. Full article

It is well known that aqueous solutions can emit electromagnetic waves in the radio frequency range. However, the physical nature of this process is not yet fully understood. In this work, the possible role of gas nanobubbles formed in the bulk liquid is considered. We develop a theoretical model based on the concept of gas bubbles stabilized by ions, or “bubstons”. The role of bicarbonate and hydronium ions in the formation and stabilization of bubstons is explained through the use of quantum chemical simulations. A new model of oscillating bubstons, which takes into account the double electric layer formed around their gas core, is proposed. Theoretical estimates of the frequencies and intensities of oscillations of such compound species are obtained. It was determined that oscillations of negatively charged bubstons can occur in the GHz frequency range, and should be accompanied by the emission of electromagnetic waves. To validate the theoretical assumptions, we used dynamic light scattering (DLS) and showed that, after subjecting aqueous solutions to vigorous shaking with a force of 4 or 8 N (kg·m/s²) and a frequency of 4–5 Hz, the volume number density of bubstons increased by about two orders of magnitude. Radiometric measurements in the frequency range of 50 MHz to 3.5 GHz revealed an increase in the intensity of radiation emitted by water samples upon the vibrational treatment. It is argued that, according to our new theoretical model, this radiation can be caused by oscillating bubstons. Full article

The electroosmotic flow (EOF) of non-Newtonian fluids plays a significant role in microfluidic systems. The EOF of Powell–Eyring fluid within a parallel-plate microchannel, under the influence of both electric field and pressure gradient, is investigated. Navier’s boundary condition is adopted. The velocity distribution’s approximate solution is derived via the homotopy perturbation technique (HPM). Optimized initial guesses enable accurate second-order approximations, dramatically lowering computational complexity. The numerical solution is acquired via the modified spectral local linearization method (SLLM), exhibiting both high accuracy and computational efficiency. Visualizations reveal how the pressure gradient/electric field, the electric double layer (EDL) width, and slip length affect velocity. The ratio of pressure gradient to electric field exhibits a nonlinear modulating effect on the velocity. The EDL is a nanoscale charge layer at solid–liquid interfaces. A thinner EDL thickness diminishes the slip flow phenomenon. The shear-thinning characteristics of the Powell–Eyring fluid are particularly pronounced in the central region under high pressure gradients and in the boundary layer region when wall slip is present. These findings establish a theoretical base for the development of microfluidic devices and the improvement of pharmaceutical carrier strategies. Full article

Due to the increase in energy demand, photocatalytic hydrogen (H₂) production has received enormous interest from the scientific community due to its simplicity and cost-effectiveness. The photocatalyst (PC) plays a vital role in H₂ evolution, and it is well understood that an efficient PC should have a larger surface area and better charge separation and transport properties. Previously, extensive efforts were made to prepare the efficient PC for photocatalytic H₂ production. In some cases, pristine catalyst could not catalyze the catalytic reactions due to a fast recombination rate or poor catalytic behavior. Thus, cocatalysts can be explored to boost the photocatalytic H₂ production. In this regard, a promising cocatalyst should have a large surface area, more active sites, decent conductivity, and improved catalytic properties. Molybdenum disulfide (MoS₂) is one of the two-dimensional (2D) layered materials that have excellent optical, electrical, and physicochemical properties. MoS₂ has been widely utilized as a cocatalyst for the photocatalytic H₂ evolution under visible light. Herein, we have reviewed the progress in the fabrication of MoS₂ and its composites with metal oxides, perovskite, graphene, carbon nanotubes, graphitic carbon nitrides, polymers, MXenes, metal-organic frameworks, layered double hydroxides, metal sulfides, etc. for photocatalytic H₂ evolution. The reports showed that MoS₂ is one of the desirable cocatalysts for photocatalytic H₂ production applications. The challenges and future perspectives are also mentioned. This study may be beneficial for the researchers working on the design and fabrication of MoS₂-based PCs for photocatalytic H₂ evolution applications. Full article

The surface electric charge of biomaterials plays a pivotal role in determining their bioactivity and biocompatibility, especially in orthopedic and dental applications. This review analyzes recent progress (2015–2024) in understanding how electric properties, particularly surface charge and zeta potential, modulate cellular adhesion, proliferation, and differentiation. Negatively charged surfaces (−20 to −30 mV) were consistently associated with enhanced osteoblast activity and calcium mineralization, while positively charged surfaces often induced pro-inflammatory responses. We explore theoretical models of the electric double layer (EDL), methods for quantifying surface charge, and strategies for modifying surface potential to enhance biological outcomes. A comparative analysis of materials—hydroxyapatite coatings, PCL scaffolds, titanium surfaces, and piezoceramics—is provided. Finally, we highlight knowledge gaps in mechanistic understanding and emphasize the need for standardized protocols in evaluating the electric properties of biomaterials. Full article

Transition metal oxides (TMOs) are considered to be highly promising materials for supercapacitor electrodes due to their low cost, multiple convertible valence states, and excellent electrochemical properties. However, inherent limitations, including restricted specific surface area and low electrical conductivity, have largely restricted their application in supercapacitors. In this paper, core–shell heterostructures of nickel–iron layered double hydroxide (NiFe-LDH) nanosheets uniformly grown on CuCo₂O₄ nanoneedles were synthesized by hydrothermal and calcination methods. It is found that the novel core–shell structure of CuCo₂O₄@NiFe-LDH improves the electrical conductivity of the electrode materials and optimizes the charge transport path. Under the synergistic effect of the two components and the core–shell heterostructure, the CuCo₂O₄@NiFe-LDH electrode achieves an ultra-high specific capacity of 323.4 mAh g⁻¹ at 1 A g⁻¹. And the capacity retention after 10,000 cycles at 10 A g⁻¹ is 90.66%. In addition, the assembled CuCo₂O₄@NiFe-LDH//RGO asymmetric supercapacitor device achieved a considerable energy density (68.7 Wh kg⁻¹ at 856.3 W kg⁻¹). It also has 89.36% capacity retention after 10,000 cycles at 10 A g⁻¹. These properties indicate the great potential application of CuCo₂O₄@NiFe-LDH in the field of high-performance supercapacitors. Full article