Search Results (567)

This research paper presents Volvo SmartCell, an AC battery technology that integrates modular multilevel converters and battery cells to form a unified system for electric vehicle propulsion and power supply. The research work addresses the broader challenge of reducing driveline cost and complexity by replacing traditional components such as inverters, onboard chargers, centralized DC/DC converters, vehicle control units and many more. SmartCell uses distributed Cluster Boards comprised of H-bridges which are controlled via wireless communication to generate AC voltage, deliver redundant low voltage power, and support cell level protection mechanisms. The prototype testing demonstrates that the system can supply traction power by engaging clusters according to the required voltage depending on motor speed, achieve AC grid charging by synthesizing sinusoidal voltages without a dedicated charger, and provide autonomous DC/DC operation through cluster level voltage regulation. Simulations further indicate that multilevel voltage generation can reduce switching losses and improve electric machine efficiency compared to conventional systems. Additional benefits include active cell balancing, support for mixed cell chemistries, and high redundancy through multiple independent power branches. Challenges remain in wireless bandwidth limitations and cost optimization of Cluster Boards. Ongoing development aims to enhance communication robustness and validate safety for non-isolated grid charging. Full article

Radiotherapy is essential for treating head and neck cancer but frequently leads to radiation-induced fibrosis (RIF) in salivary glands (SGs). RIF develops through a cascade of radiation-triggered events, including DNA damage, excessive oxidative stress, and epithelial cell death. Persistent injury can cause cells to become senescent and release inflammatory signals, fueling chronic inflammation. These processes activate pathways, particularly TGF-β/SMAD, resulting in fibroblast activation, myofibroblast differentiation, and extracellular matrix accumulation. Potential treatments include drugs, mesenchymal stem/stromal cell (MSC) therapy, and gene-transfer approaches. In which, MSC therapy is particularly promising as MSCs can migrate to injured tissue and support epithelial regeneration. Yet progress is limited by the difficulty of expanding human acinar cells (ACs) in vitro. To address this gap, tunable alginate–gelatin–hyaluronic acid (AGHA) bioink hydrogels have emerged as a suitable system as gelatin provides adhesion sites for AC attachment and 3D organoid formation, alginate offers tunable mechanical support through ionic crosslinking, and hyaluronic acid contributes essential cues for cell adhesion, migration, and morphogenesis. The aim of this review is to synthesize current understanding of the mechanisms driving RIF, evaluate available therapeutic strategies, and highlight the role of AGHA in generating engineered SG constructs to test MSC therapies for RIF. Full article

We developed an arbitrary Lagrangian–Eulerian (ALE)-based multiphysics model for evaporation from a contact-line-pinned sessile drop of neat water subject to a vertically oriented sinusoidal alternating current (AC) electric field applied across parallel-plate electrodes. The framework fully couples electrostatics, incompressible flow, heat transfer with evaporative cooling, and transient vapour transport in air, and includes an instantaneous, voltage-controlled electrowetting contact-angle response under constant-contact-radius conditions. Validation against published data shows that the model captures both pinned-droplet evaporation and electrically induced deformation. Because Maxwell traction scales with the squared electric-field magnitude, droplet height and contact angle exhibit a robust 2:1 frequency-doubled response, producing two peak–trough events per voltage period. The resulting periodic deformation drives oscillatory interfacial shear and internal recirculation, yielding a synchronous double-peaked evaporative-flux waveform. Gas-side analysis quantifies a time-varying diffusion-layer thickness via a characteristic diffusion length; two thinning events per period coincide with flux maxima, indicating that AC enhancement is dominated by periodic compression of the vapour boundary layer and reduced gas-side mass-transfer resistance. Increasing voltage amplitude (0–60 kV) strongly accelerates volume loss, while frequency has a secondary effect: the cycle-averaged flux rises from 1 to 10 Hz but decreases slightly at 20 Hz due to phase lag and weaker boundary-layer modulation. Full article

In the context of the coordinated development of high-proportion renewable energy integration and alternating current/direct current (AC/DC) hybrid transmission, the sending-end power grid faces challenges such as decreased system strength, contracted stability boundaries, and difficulties in covering high-risk operating conditions. This paper proposes a new renewable energy scale impact analysis method that integrates “typical scenario construction-scale ladder comparison–prediction-driven time series injection” in response to the operational constraints of AC/DC transmission. In terms of method implementation, firstly, a two-layer typical scenario system is constructed under unified transmission constraints and fixed grid boundaries: A regular benchmark scenario covers the main operating range, and a set of high-risk scenarios near the boundaries is obtained through multi-objective intelligent search, which is then refined through clustering to form a computable stress-test scenario library. Here, the boundary scenarios are generated by a multi-objective search that simultaneously drives multiple key section load rates towards their limits, subject to AC power-flow feasibility and operational constraints, and the resulting Pareto candidates are reduced into a compact stress-test library by clustering. Secondly, a ladder scenario with increasing renewable energy scale is constructed, and cross-scale comparisons are carried out within the same scenario system to extract the scale effect and critical laws of key safety indicators. Finally, data resampling and Gated Recurrent Unit multi-step prediction are introduced to generate wind power output time series, enabling the temporal mapping of prediction results to scenario injection quantities, and constructing a closed-loop input interface of “prediction–scenario–grid indicators”. The results demonstrate that the proposed hierarchical framework, under unified AC/DC export constraints, can effectively construct a compact stress-test scenario library with enhanced boundary-risk coverage and can reveal how transient voltage security evolves across renewable expansion scales. By coupling boundary-oriented scenario construction, cross-scale comparable assessment, and forecasting-driven time series injection, the framework improves engineering interpretability and practical applicability compared with conventional scenario sampling/reduction workflows. For the forecasting module, the Gated Recurrent Unit (GRU) model achieves MAPE = 8.58% and RMSE = 104.32 kW on the test set, outperforming Linear Regression (LR)/Random Forest (RF)/Support Vector Regression (SVR) in multi-step ahead prediction. Full article

Background: The progression of idiopathic pulmonary fibrosis (IPF) involves distal airway remodeling and bronchiolization; however, the mechanisms driving these changes, particularly the contributions of epithelial stem cells, are not fully understood. K13⁺ hillock cells, normally quiescent in proximal airways, were examined for their potential contribution to IPF pathogenesis. Methods: Spatial immunofluorescence was used to profile K13 expression along the airway axes in IPF and control lungs. Multiplex staining complemented by ex vivo culture assays was used to test expression stability. Single-cell RNA-sequencing (scRNA-seq) data were re-analyzed to identify cell subclusters and pathway enrichments. Meanwhile, cell–cell communication was inferred by using CellChat. Results: K13 was ectopically upregulated in IPF honeycomb cysts, triggering a proximal-like pseudostratified phenotype. This shift was marked by surges in K13⁺ regionally overlapping expression patterns (K5⁺, ~9%; CC10⁺, ~53%; ACE-TUB⁺, ~44%; MUC5AC⁺, ~23%) and a decline in SOX2 expression (~95% to ~64%), with ~70% of residual SOX2^low cells exhibiting elevated K13. Accompanying the expansion of K13⁺ subclusters (basal: 1.8% to 41.5%; club: 10.7% to 31.5%), it was observed that the profibrotic markers (K17, S100A2, LGALS7, IGFBP6) and ontologies related to RNA processing, stress response, and senescence were also enriched. These subclusters also amplified pro-fibrotic signaling (e.g., TGF-β, SEMA3, and GALECTIN-9) associated with epithelial subtypes and HAS1^high fibroblasts. Conclusions: Here, we demonstrate that K13⁺ cell activation is a pivotal event, driving the dysregulated proximalization of distal airways in IPF through fate reprogramming and epithelial-mesenchymal crosstalk. Thus, elucidating these K13-mediated fate dynamics provides a critical framework for understanding IPF pathogenesis. Full article

To reduce vehicular emission pollution in cold regions and maximize sustainable development of transportation, AC self-heating of electric vehicles is acknowledged as an efficient approach to mitigate the decline in Li-ion battery performance under low-temperature conditions. This paper introduces a novel battery self-heating approach based on reconfiguration of the drive circuit, which is compatible with both preheating and on-route heating. The undesired torque generated by the heating current can be inherently nullified regardless of the rotor position. The control of heating and driving currents is entirely decoupled, facilitating straightforward adaptation to a range of heating strategies. Furthermore, a battery electro-thermal model is proposed and integrated with the drive system model to estimate the battery temperature evolution. Comprehensive experiments are designed to validate the operating principle and the accuracy of battery temperature estimation under various working conditions. The results present a high fidelity between the experimental data and the simulation outcomes. The root mean square errors of the predicted battery temperature under all the constant and combined driving conditions are less than 1 °C. Full article

Traditional virtual synchronous generator (VSG) control in photovoltaic–storage systems struggles with severe dynamic deterioration under high-impedance weak grid conditions. Through small-signal modeling, this paper analytically reveals that increased grid inductance forces the system’s dominant poles to migrate significantly toward the real axis, inducing a critical “overdamped hysteresis” that degrades transient tracking speed and oscillation attenuation. To break these physical constraints, an improved exponential synergistic adaptive control strategy is proposed. By establishing a synergistic optimization mechanism between the virtual inertia and damping coefficients via a square-root coupled exponential function, the proposed method achieves precise multi-parameter coordination. During the initial phase of disturbances, it triggers an explosive parameter surge to provide “stiff” transient support, strictly limiting frequency deviations and the rate of change of frequency (RoCoF). During the recovery phase, it drives a precipitous parameter decay to actively neutralize the overdamped coupling effect, forcibly pulling the migrated poles back to the ideal underdamped region. Rigorous switching-model simulations demonstrate that, compared to conventional fixed-parameter and power function-based adaptive methods, the proposed synergistic strategy significantly improves transient performance. Quantitatively, during load steps, it restricts the frequency nadir to 49.85 Hz (compared to 49.73 Hz for fixed parameters). During extreme grid stiffness transitions (SCR drops), it completely eliminates active power tracking hysteresis by reducing the settling time to just 0.26 s and aggressively clamps AC overcurrent peaks from 38 A down to 31 A. Supported by coordinated PV–storage energy management, the proposed method offers a highly robust grid-forming framework for renewable-dominated weak power grids. Supported by coordinated PV–storage energy management, the proposed method offers a highly robust grid-forming framework for renewable-dominated weak power grids. Full article

Silicon carbide (SiC) MOSFETs are critical for next-generation power electronics, yet their reliability is challenged by alternating-current Bias Temperature Instability (AC BTI). While charge trapping and Recombination-Enhanced Defect Reaction (REDR) are known degradation pathways, the specific role of gate oxide thickness in determining the dominant mechanism remains unclear. This study investigates the degradation behaviors of SiC MOSFETs with varying oxide thicknesses under 150 kHz Dynamic Gate Stress. By maintaining a constant electric field, we decouple the effects of oxide thickness using high-frequency C-V, quasi-static gate current (I_GS) characteristics, and transconductance analysis. Results reveal that thin-oxide devices exhibit parallel C-V shifts and stable transconductance, indicating degradation driven by deep-level charge trapping. Conversely, thick-oxide devices display significant C-V stretch-out, negligible I_GS peak shifts, and severe transconductance degradation, accompanied by irreversible threshold voltage drift. We conclude that despite identical electric fields, the higher driving voltages in thick-oxide devices trigger severe interface state generation consistent with the REDR model, whereas thin-oxide devices are dominated by bulk oxide trapping. These findings highlight the necessity of thickness-dependent optimization strategies for SiC power devices. Full article

Sub-synchronous oscillation problems may be induced when direct-drive wind turbines are connected to a weak AC power grid, and then it is necessary to analyze the mechanism of sub-synchronous oscillation and study effective suppression methods. In this paper, the disturbance of direct-drive wind turbines connected to the grid is analyzed firstly. The result indicates that the regulation ability of traditional current inner-loop PI controller is limited and may even exacerbate oscillation. Then a new current inner-loop controller is designed which is based on linear active disturbance rejection control. To address the difficulty in tuning the parameters of the disturbance rejection controller, the particle swarm optimization algorithm is applied. Finally, a simulation model of a direct-drive wind turbine grid connected to the power grid is built and simulated. The results show that, compared with the bandwidth method for tuning controller parameters, the particle swarm optimization algorithm has stronger adaptability to various operating conditions; the proposed linear active disturbance rejection controller based on particle swarm optimization can block the propagation of sub-synchronous frequency disturbance components strongly compared to traditional control, and the sub-synchronous oscillations are suppressed effectively. Full article

This paper presents the design of a high-efficiency apple harvesting robot based on a hybrid pneumatic-electric drive system, capable of operating around the clock. The robotic system comprises a mobile platform with two degrees of freedom (DOF) and a five-DOF PRRRP manipulator for fruit picking. To meet the harvesting requirements, a spoon-shaped end-effector with pneumatic control was developed, enabling precise manipulator control and flexible grasping. The robot’s vision system integrates machine vision and deep neural network approaches. Additionally, an industrial computer and AC servo drivers were employed to control the manipulator and end-effector. An integrated nighttime illumination system allowed for all-weather operation. Initial experiments were conducted in a controlled laboratory. Subsequently, comprehensive identification and harvesting tests were performed in both laboratory and field environments to validate system robustness. Experimental results validated the effectiveness of the proposed system, demonstrating an apple harvesting success rate of 81% and an average harvesting time of 7.81 s per apple. The system achieved a fruit damage rate of less than 5% during field experiments, demonstrating its potential for gentle handling. The primary innovation of this work lies in its hybrid drive architecture and adaptive vision strategy, which together offer a cost-effective and robust solution for all-weather automated harvesting, addressing key limitations of high cost and environmental sensitivity in existing robotic harvesters. Full article

Façade-integrated solar cooling technologies enable the utilisation of façade surface potential and the provision of resilient cooling. This work compares three solar cooling scenarios, positioning a solar cooling element in the west and east façades. The 2ACE scenario is based on a compact adsorption cooling concept, while the 2PV scenario directly drives a compression chiller with photovoltaic elements, and 2PVB incorporates an additional battery. All Modelica system models are implemented in Modelon Impact and operated using dynamic optimisation for the hottest day of the year. Results indicate that the 2ACE scenario, utilising the adsorbent Silica Gel SG123, achieves near to double the self-sufficiency compared to Zeolite 13X. No clear optimal area balance between west and east elements is apparent. The 2PV scenario only surpasses the 2ACE scenario’s self-sufficiency with increased total element area, whereas 2PVB enables a drastic increase and complete self-sufficiency. This highlights the limitation of the adsorption cooling scenario due to its inability to compensate for ventilation’s electrical energy consumption. However, photovoltaic scenarios are heavily reliant on the assumed energy efficiency ratio. Additionally, slender buildings with a low AV ratio require less façade area to achieve the same self-sufficiency level as wider buildings. Full article

The global shift toward decarbonized power systems is driving unprecedented penetration of variable renewable energy sources, especially wind and solar PV. Legacy grid architectures, built around centralized, dispatchable synchronous generation, are ill-suited to manage the bidirectional power flows, reduced inertia, and new stability constraints introduced by inverter-based resources. Existing research offers deep but fragmented insights into individual elements of this transition, such as advanced power electronics, microgrids, or market design, but rarely integrates them into a coherent architectural vision for resilient, high-renewable grids. This review closes that gap by synthesizing technical, architectural, and institutional perspectives into a unified framework for resilient grid design toward 2030 and beyond. First, it traces the evolution from traditional hierarchical grids to smart, prosumer-centric, and modular multi-layer architectures, highlighting the implications for reliability and resilience. Second, it critically examines the core technical challenges of high VRES penetration, including stability, power quality, protection, and operational planning in converter-dominated systems. Third, it reviews the enabling roles of advanced power electronics, hierarchical control and wide-area monitoring, microgrids, and hybrid AC/DC networks. Case studies from Germany, China, and Egypt are used to distil context-dependent pathways and common design principles. Building on these insights, the paper proposes a scalable multi-layer framework spanning physical, data, control, and regulatory/market layers. The framework is intended to guide researchers, planners, and policymakers in designing resilient, converter-dominated grids that are not only technically robust but also economically viable and socially sustainable. Full article

To address the challenges of ambient light interference and slow overload recovery in transimpedance amplifiers (TIAs) for automotive Light Detection and Ranging (LiDAR) systems, this paper proposes a high-performance TIA with integrated ambient light cancellation and fast recovery capabilities. The core design includes an adaptive ambient light cancellation (ALC) loop that eliminates background currents up to 3 mA without relying on AC coupling capacitors, achieving a low-frequency cutoff frequency of 321 kHz to ensure the signal-to-noise ratio (SNR) of weak target signals. A multi-stage clamping and current transfer mechanism is employed to realize rapid overload recovery: under 100 mA heavy overload conditions, the recovery time is controlled around 8.7 ns, and the pulse broadening is limited to 2.7 ns, avoiding measurement blind zones. Implemented in a 0.18-μm SiGe BiCMOS process, the proposed TIA occupies a compact area of 0.15 mm², with a transimpedance gain of 80 dBΩ (10 kΩ) and a −3 dB bandwidth of 421 MHz. The input-referred noise current spectral density is 4.7 $\mathrm{pA}/\sqrt{\mathrm{Hz}}$, and the integrated equivalent input noise current from 1 Hz to 250 MHz is 73.6 nA_rms. Operating over a temperature range of −40 ℃ to 125 ℃, the TIA meets the rigorous requirements of automotive-grade applications. Performance comparisons with commercial products and state-of-the-art designs demonstrate its competitive ambient light rejection and fast recovery capabilities, validating its potential for use in direct time-of-flight (dToF) LiDAR systems for autonomous driving. Full article

Conventional multi-channel ultrasonic motor (USM) drive systems commonly adopt a one-motor–one-driver architecture, in which each drive channel requires an independent isolated power supply and inverter stage. As the number of motors increases, the system volume and structural complexity grow significantly. To address this issue, this paper proposes a shared DC-bus multi-channel drive architecture for traveling-wave USM. In the proposed scheme, multiple half-bridge power stages are connected in parallel to a common high-voltage DC-bus to achieve centralized energy supply and distributed driving. A DC-side midpoint reference network is introduced to establish an AC voltage reference under a unipolar DC supply, while an independent series matching inductor is employed in each channel to shape the half-bridge output into a quasi-sinusoidal motor-terminal voltage through resonant filtering. Based on the equivalent electrical model of the USM, a unified analytical model is established to analyze the voltage formation mechanism under shared DC-bus conditions. Time-domain simulations and experimental tests are carried out on a two-channel prototype operating at a 150 V DC-bus and a 40 kHz switching frequency. The results demonstrate stable quasi-sinusoidal output voltages, preserved phase consistency, and limited inter-channel coupling during parallel operation. Compared with conventional independent-supply solutions, the proposed architecture achieves an approximately 27% reduction in overall system volume for a three-motor configuration, demonstrating good scalability for compact multi-channel USM drive systems. Full article

Electric Water Pumps (EWPs) are being adopted more widely to improve thermal management in internal combustion engines and electrified powertrain systems. In this context, the drive motor must deliver high efficiency and reliability despite a strict volume constraint. This paper addresses a key drawback of coreless printed circuit board (PCB) stator axial-flux permanent-magnet machines for EWP use: the PCB traces are directly exposed to the magnet flux, which increases AC loss, while the required phase resistance also leads to non-negligible DC copper loss. To mitigate both loss components within the same conductor design space, a pyramid trace concept is introduced. A magnetic equivalent circuit (MEC) based model is first used to estimate the baseline performance as the number of PCB stator modules changes, and the resulting scalability is examined in terms of module commonality. The final design then applies the pyramid trace layout with a layer-dependent trace width that is narrower on the layers closer to the magnets and wider on the layers farther away—the trade-off between AC loss and DC loss is optimized using 3D finite element analysis. Torque predictions from the simplified MEC model are cross-checked against 3D finite element analysis (FEA), and finally, a prototype is built to validate the analysis with experimental measurements; for the final selected model, the torque prediction error is 2.37% compared with the validation result. Full article