Search Results (1,978)

This paper proposes an event-triggered extension of duty-ratio-based model predictive direct speed control (DR-MPDSC) for permanent magnet synchronous motor (PMSM) drives in electric vehicle (EV) applications. The main contribution is the development of an event-triggered execution framework specifically tailored to DR-MPDSC, in which control updates are performed only when the speed tracking error violates a prescribed condition, rather than at every sampling instant. Unlike conventional MPDSC and time-triggered DR-MPDSC schemes, the proposed strategy achieves a significant reduction in control execution frequency while preserving fast dynamic response and closed-loop stability. An optimized duty-ratio formulation is employed to regulate the effective application duration of the selected voltage vector within each sampling interval, resulting in reduced electromagnetic torque ripple and improved stator current quality. An extended Kalman filter (EKF) is integrated to estimate rotor speed and load torque, enabling disturbance-aware predictive speed control without mechanical torque sensing. Furthermore, a unified field-weakening strategy is incorporated to ensure wide-speed-range operation under constant power constraints, which is essential for EV traction systems. Simulation and experimental results demonstrate that the proposed event-triggered DR-MPDSC achieves steady-state speed errors below 0.5%, limits electromagnetic torque ripple to approximately 2.5%, and reduces stator current total harmonic distortion (THD) to 3.84%, compared with 5.8% obtained using conventional MPDSC. Moreover, the event-triggered mechanism reduces control update executions by up to 87.73% without degrading transient performance or field-weakening capability. These results confirm the effectiveness and practical viability of the proposed control strategy for high-performance PMSM drives in EV applications. Full article

To improve DC-bus voltage regulation of bidirectional DC/DC converters in photovoltaic–energy storage DC microgrids, this paper proposes an improved linear active disturbance rejection control (LADRC) strategy based on observation error reconstruction. In conventional LADRC, the linear extended state observer (LESO) is driven solely by the output tracking error, which may lead to weakened disturbance excitation after rapid error convergence and thus degraded disturbance estimation performance. To address this limitation, an observation error reconstruction mechanism is introduced, in which a reconstructed error variable incorporating higher-order estimation deviation information is used to redesign the LESO update law. This modification fundamentally enhances the disturbance-driving mechanism without excessively increasing observer bandwidth, resulting in improved mid- and high-frequency disturbance estimation capability. The proposed method is analyzed in terms of disturbance estimation characteristics, frequency-domain behavior, and closed-loop stability. Comparative simulations and hardware-in-the-loop experiments under typical load and photovoltaic power step variations within the safe operating range demonstrate that the proposed LADRC–PI significantly outperforms conventional PI and LADRC–PI control. Experimental results show that the maximum DC-bus voltage fluctuation is reduced by over 60%, and the voltage recovery time is shortened by approximately 40–50% under the tested operating conditions. Full article

To combat the critical hurdles of thermal buildup and low-temperature shutdown events in 5G-enabled smart wearables, a high-performance flexible composite film based on ellagic acid-modified single-walled carbon nanotubes (EA-SWCNTs) and aramid nanofibers (ANF) was designed and developed. The influence mechanism of the loading amount of the conductive network on the electrothermal properties of the composite material was focused on. The results show that through the π-π stacking non-covalent modification strategy, the uniform dispersion of EA-SWCNTs on the layer of ANF substrate and the construction of an ordered layered structure were successfully achieved. The prepared composite film could reach a steady-state temperature of 171 °C under a driving voltage of 3.5 V. In addition, it exhibits excellent electrothermal response characteristics and cyclic stability. It could reach the steady-state voltage within 10 s and shows no obvious performance degradation after multiple cycles. This composite film shows broad application prospects in fields such as intelligent wearable devices and flexible electronic protection. Full article

With the increasing integration of renewable energy into power grids, voltage source converter-based high-voltage direct current (VSC-HVDC) stations often adopt hybrid grid-following (GFL) and grid-forming (GFM) control strategies to improve adaptability to varying grid strengths. In many existing schemes, the hybrid coefficient changes abruptly, which may produce large transient current overshoots and compromise the safe and stable operation of converters. An adaptive hybrid GFL-GFM control framework equipped with a hybrid coefficient transition regulation is proposed. Small-signal state–space models are established and eigenvalue analysis confirms stability over the considered short-circuit ratio (SCR) range. The regulating method is activated only during coefficient transitions and is inactive in steady-state, thereby preserving the operating-point eigenvalue properties. Dynamic equations of the converter current change rate are derived to reveal the key role of the hybrid-coefficient change rate in driving transient current overshoots, based on which a real-time hybrid coefficient regulating method is developed to shape coefficient transitions. Simulations on a 500 kV/2100 MW VSC-HVDC project demonstrate reduced transient current overshoot and power oscillations during SCR variations, with robustness under moderate parameter deviations as well as representative SCR assessment error and update delay. Full article

Mitochondrial Ca²⁺ signaling is increasingly recognized as a key integrator of synaptic activity, metabolism, and redox balance within the tripartite synapse. At excitatory synapses, Ca²⁺ influx through ionotropic glutamate receptors and voltage-gated channels is sensed and transduced by strategically positioned mitochondria, whose Ca²⁺ uptake and release tune tricarboxylic acid cycle activity, adenosine triphosphate synthesis, and reactive oxygen species (ROS) generation. Through these Ca²⁺-dependent processes, mitochondria are proposed to help set the threshold at which glutamatergic activity supports synaptic plasticity and homeostasis or, instead, drives hyperexcitability and excitotoxic stress. Here, we synthesize how mitochondrial Ca²⁺ dynamics in presynaptic terminals, postsynaptic spines, and perisynaptic astrocytic processes regulate glutamate uptake, recycling, and release, and how subtle impairments in these pathways may prime synapses for failure well before overt energetic collapse. We further examine the reciprocal interplay between Ca²⁺-dependent metabolic adaptations and glutamate homeostasis, the crosstalk between mitochondrial Ca²⁺ and ROS signals, and the distinct vulnerabilities of neuronal and astrocytic mitochondria. Finally, we discuss how disruption of this Ca²⁺-centered mitochondria–glutamatergic axis contributes to synaptic dysfunction and circuit vulnerability in neurodegenerative diseases, with a particular focus on Alzheimer’s disease. Full article

There are observed unprecedented dynamics in transportation electrification—especially in electric vehicles (even being tested as autonomous units in some regions). The expected improvements in charging and driving distances strive toward higher power levels of passenger cars, public transportation, and trucks, thus leading to elevations of on-board voltage levels. It is expected that the kilovolt level will be crossed soon, thus implying testing at a few kV. To achieve efficient power conversion while maintaining high-power density, new classes of wide-band semiconductors are being implemented; however, fast-switching and ultra-short rise times may result in faster electrical insulation deterioration. The challenges and trends in the development of the high-voltage insulation of various EV components are analyzed. Insulation performance evaluation criteria are discussed, including partial discharges and monitoring approaches. In this context, the development of the transportation segment’s electrification is closely connected with high-voltage insulation problems. Full article

This paper presents the design and fabrication of a triboelectric nanogenerator based on a Quadruple Parallel-cavity Helmholtz Resonator (4C–HR TENG) for the efficient harvesting of noise energy in marine engine room environments. The device utilizes sound waves to drive periodic contact and separation between polytetrafluoroethylene (PTFE) particles in the resonant cavity and the vibrating diaphragm as well as the upper electrode plate, thereby converting sound energy into mechanical energy and finally into electrical energy. The device consists of an acoustic waveguide with a length of 350 mm and both width and height of 60 mm, along with a Helmholtz Resonator with a diameter of 60 mm and a height of 40 mm. Experimental results indicate that under resonance conditions with a sound pressure level of 109.8 dB and a frequency of 110 Hz, the device demonstrates excellent output performance, achieving a peak output voltage of 250 V and a current of 4.85 μA. We analyzed and investigated the influence mechanism of key parameters (filling ratio, sound pressure level, the height between the electrode plates, and particle size) on the output performance. Through COMSOL Multiphysics simulation analysis, the sound pressure enhancement effect and the characteristic of concentrated diaphragm center displacement at the first-order resonance frequency were revealed, verifying the advantage of the four-cavity structure in terms of energy distribution uniformity. In practical applications, the minimum responsive sound pressure level corresponding to the operating frequency range of the 4C–HR TENG was determined. The output power reaches a maximum of 0.27 mW at a load resistance of 50 MΩ. At a sound pressure level of 115.1 dB, the device can charge a 1 μF capacitor to 4.73 V in just 32 s and simultaneously illuminate 180 LEDs in real-time, demonstrating its potential for environmental noise energy harvesting and micro-energy supply applications. This study provides new insights and experimental evidence for the efficient recovery of noise energy. Full article

Grid-Scale Battery Energy Storage Systems (GS-BESS) play a crucial role in modern power grids, addressing challenges related to integrating renewable energy sources (RESs), load balancing, peak shaving, voltage support, load shifting, frequency regulation, emergency response, and enhancing system stability. However, harnessing their full potential and lifetime requires intelligent operational strategies that balance technological performance, economic viability, and environmental sustainability. This systematic review examines how artificial intelligence (AI)-based intelligent optimization enhances GS-BESS performance, focusing on its techno-economic, environmental impacts, and policy and regulatory implications. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we review the evolution of GS-BESS, analyze its advancements, and assess state-of-the-art applications and emerging AI techniques for GS-BESS optimization. AI techniques, including machine learning (ML), predictive modeling, optimization algorithms, deep learning (DL), and reinforcement learning (RL), are examined for their ability to improve operational efficiency and control precision in GS-BESSs. Furthermore, the review discusses the benefits of advanced dispatch strategies, including economic efficiency, emissions reduction, and improved grid resilience. Despite significant progress, challenges persist in data availability, model generalization, high computational requirements, scalability, and regulatory gaps. We conclude by identifying emerging opportunities to guide the next generation of intelligent energy storage systems. This work serves as a foundational resource for researchers, engineers, and policymakers seeking to advance the deployment of AI-enhanced GS-BESS for sustainable, resilient power systems. By analyzing the latest developments in AI applications and BESS technologies, this review provides a comprehensive perspective on their synergistic potential to drive sustainability, cost-effectiveness, and energy systems reliability. Full article

To address the issue of voice leakage during the rapid deployment of meeting rooms, a piezoelectric flexible interference structure (PFIS) for active sound masking is developed in this paper. The PFIS uses rubber as the base, allowing it to bend or fold, offering good flexibility. The PFIS generates vibration through direct contact with the target object, without the need for adhesives or installation, fulfilling the need for rapid deployment. The experiment studied the driving of PFIS under three types of interference signals, analyzing the interference performance of PFIS by combining the vibration response of the surface of the table. The results show that the vibration response generated by PFIS on the surface of the table is significantly greater than when only a human voice is present. When a 3.5 kg weight is added to the surface of PFIS, its vibration performance increases by 5.6 times. Furthermore, increasing the voltage enhances the vibration interference effect of the PFIS across the entire frequency range; after adding weight, the vibration interference performance of the PFIS is significantly improved for frequencies above 2500 Hz. It has been verified that PFIS has strong vibration interference performance, effectively masking the vibrations of objects under human voice, providing a new technical solution for information security protection in sensitive areas. Full article

In order to solve the dynamic analysis and interactive imaging control problems in the deformation process of bionic soft lenses, dielectric elastomer (DE) actuators are separated from a convex lens, and data-driven eye-controlled motion technology is investigated. According to the DE properties, which are consistent with the deformation characteristics of hydrogel electrodes, the motion and deformation effect of eye-controlled lenses under film prestretching, lens size, and driving voltage, is studied. The results show that when the driving voltage increases to 7.8 kV, the focal length of the lens, whose prestretching λ is 4, and the diameter d is 1 cm, varies in the range of 49.7 mm and 112.5 mm. And the maximum focal-length change could reach 58.9%. In the process of eye controlling design and experimental verification, a high DC voltage supply was programmed, and eye movement signals for controlling the lens were analyzed by MATLAB software (R2023b). Eye-controlled interactive real-time motion and tunable imaging of the lens were realized. The response efficiency of soft lenses could reach over 93%. The adaptive lens system developed in this research has the potential to be applied to medical rehabilitation, exploration, augmented reality (AR), and virtual reality (VR) in the future. Full article

Energy-efficient driving is essential for reducing the environmental impacts of road transport, especially for electric passenger vehicles. This research aims to build a data-driven behavioral analysis and energy-consumption evaluation model. The model relies on sensor data from the vehicle’s on-board communication network, primarily the CAN (Controller Area Network) bus. We analyze patterns of key powertrain and battery parameters—such as current, voltage, state of charge (SoC), and power—in relation to driver inputs, such as the accelerator pedal position. In the first stage, we review the literature with a focus on machine learning and clustering methods used in behavioral and energy analysis. We also examine the role of on-board telemetry systems. Next, we develop a controlled measurement architecture. It defines reference consumption maps from dynamometer data across operating points and environmental variables, including SoC, temperature, and load. The longer-term goal is a multidimensional behavioral map and profiling framework that can predict energy efficiency from real-time driver inputs. This work lays the foundation for a future system with adaptive, feedback-based driver support. Such a system can promote intelligent, sustainable, and behavior-oriented mobility solutions. Full article

An equivalent circuit model (ECM) is a highly practical tool for simulating Li-ion battery behavior. There are many relevant studies which compare different ECM variants or suggest algorithms to extract model parameters from the experimental data. However, little attention has been given to the battery tests used for identification of the ECM parameters. Therefore, here the influence of experimental test pulse characteristics on the parameterized ECM accuracy was systematically studied. The test pulse duration was varied in a wide range from 9 s to about 2.5 min. The portion of the relaxation phase data used by the parameter optimization algorithm was also varied in an even wider range. Total 168 ECM parameter sets were obtained. Each parameter set was validated using nine diverse current profiles representing different battery operation conditions, including one based on Urban Dynamometer Driving Schedule (UDDS). The validation results prove that the impact of the test pulse choice on the parameterized ECM accuracy is great to the point that it can overshadow the use of a higher-order Thevenin model. By choosing the optimal parameter set, the simulated voltage root mean square error (RMSE) was reduced to as low as 3.0 mV and 1.2 mV for first- and second-order ECM, respectively, while the second-order model based on arbitrary chosen test pulse on average yields RMSE value above 5 mV. Full article

The p53 tumor suppressor, a key transcription factor, acts as a cellular stress sensor that regulates hundreds of genes involved in responses to DNA damage, oxidative stress, and ischemia. Through these actions, p53 can arrest cell cycle, initiate DNA repair, or trigger cell death. In addition to its nuclear functions, p53 can translocate to mitochondria to promote apoptosis. Studies using isolated mitochondria have suggested that p53 drives the voltage-dependent anion channel (VDAC1) into high molecular mass complexes to mediate apoptosis. VDAC1 is a central regulator of cellular energy production and metabolism and also an essential player in apoptosis, induced by various apoptotic stimuli and stress conditions. We previously demonstrated that VDAC1 oligomerization, induced by various apoptosis stimuli and stress conditions, forms a large pore that enables cytochrome c release from mitochondria, thereby promoting apoptotic cell death. In this study, we show that p53 interacts with VDAC1, modulates its expression levels, and promotes VDAC1 oligomerization-dependent apoptosis. Using purified proteins, we found that p53 directly binds VDAC1, as revealed by microscale thermophoresis and by experiments using bilayer-reconstituted VDAC1, in which p53 reduced VDAC1 channel conductance. Furthermore, overexpression of p53 in p53-null cells or in cells expressing wild-type p53 increased VDAC1 expression and induced VDAC1 oligomerization even in the absence of apoptotic stimuli. Together, these findings identify VDAC1 as a direct p53 target whose expression, oligomerization, and pro-apoptotic activity are regulated by p53. They also reinforce the central role of VDAC1 oligomerization in apoptosis. Full article

This paper proposes a fixed frequency pulse width modulation (PWM) for a dual active half-bridge resonant converter. The wide voltage range can be achieved without adding any additional components, and the voltage gain characteristic is independent of the load. Meanwhile, all switches can achieve full range zero voltage switching (ZVS). The driving logic is unified between the primary and secondary sides, allowing for the implementation of both boost and buck modes. Hence, the control logic is simple. In addition, the multiple-order harmonic analysis of the resonant tank is proposed without complex time-domain calculations. Hence, the expression of voltage gain, current characteristics, and soft switching conditions can be conveniently analyzed. Finally, a 500 W experimental prototype was built. The experimental results prove the effectiveness and superiority of the proposed solution. Full article

The imperative for EMC-optimized gate drivers in Gallium Nitride (GaN)-based automotive DC-DC converters stems from the stringent CISPR 25 standards and GaN’s intrinsic high-speed switching characteristics, which paradoxically exacerbate electromagnetic interference (EMI). This review distinguishes itself by proposing a novel frequency-domain classification framework (Zone I: <50 MHz for conducted harmonics; Zone II: >50 MHz for switching noise and ringing), which systematically organizes and assesses gate driving techniques against the triad of fundamental GaN EMC challenges: pronounced capacitance nonlinearity, low threshold voltage, and extreme parasitic sensitivity. Unlike prior surveys that primarily catalog techniques, the analysis elevates the gate driver from a simple switch interface to the central “electromagnetic actuator” of the power stage, explicitly elucidating its pivotal role in mediating the critical trade-offs among switching speed, loss, and EMC performance. A comprehensive evaluation and comparison of advanced techniques—from spread-spectrum modulation for Zone I to adaptive current shaping and resonant topologies for Zone II—are provided, alongside an analysis of their design trade-offs. Furthermore, this review presents a first-of-its-kind, phased implementation roadmap towards holistic EMC compliance, integrating intelligent hybrid control, heterogeneous integration, and system-level co-design. This review bridges the gap between device physics and system engineering, offering structured design methodologies and a clear future direction for achieving electromagnetic integrity in next-generation automotive power electronics. Full article