Search Results (2,471)

In microgrids, battery chargers/dischargers are used to manage power flow between the battery and the DC bus and to regulate the DC bus voltage, ensuring safe operating conditions for sources and loads. These actions contribute to enhancing the sustainability of the microgrid by improving energy efficiency, extending battery life, and ensuring reliable operation. The classical converter adopted to implement the battery chargers/dischargers is the boost converter, which avoids high current harmonic injection into the battery because of its continuous input current. But due to the discontinuous output current, it introduces high current harmonics into the DC bus. This also occurs in Sepic, Zeta, or other DC/DC converters with discontinuous input or output currents. One exception is the Cuk converter, which has both continuous input and output currents. However, in the Cuk converter, the intermediate capacitor voltage is higher than the input and output voltages, thus imposing high stress on the semiconductors and requiring a costly capacitor with high energy storage. Therefore, this paper proposes the design of a battery charger/discharger based on a non-electrolytic capacitor boost converter. This topology provides continuous input and output currents, which reduces harmonic component injection, extends battery life, and increases operation efficiency. Moreover, it requires a lower intermediate capacitor voltage, thereby enhancing reliability. The design of this battery charger/discharger requires an adaptive sliding-mode controller to ensure global stability and accurate bus voltage regulation. A formal stability analysis and design equations are provided. The proposed solution is validated through detailed simulations, while the adaptive sliding-mode controller is specifically tested using a detailed software-in-the-loop approach. Full article

This study explores how the integration of generative artificial intelligence, multi-objective evolutionary optimization, and reinforcement learning can enable sustainable and cost-effective decision-making in supply chain strategy. Using real-world retail demand data enriched with synthetic sustainability attributes, we trained a Variational Autoencoder (VAE) to generate plausible future demand scenarios. These were used to seed a Non-Dominated Sorting Genetic Algorithm (NSGA-II) aimed at identifying Pareto-optimal sourcing strategies that balance delivery cost and CO₂ emissions. The resulting Pareto frontier revealed favorable trade-offs, enabling up to 50% emission reductions for only a 10–15% cost increase. We further deployed a deep Q-learning (DQN) agent to dynamically manage weekly shipments under a selected balanced strategy. The reinforcement learning policy achieved an additional 10% emission reduction by adaptively switching between green and conventional transport modes in response to demand and carbon pricing. Importantly, the agent also demonstrated resilience during simulated supply disruptions by rerouting decisions in real time. This research contributes a novel AI-based decision architecture that combines generative modeling, evolutionary search, and adaptive control to support sustainability in complex and uncertain supply chains. Full article

To address the problems of insufficient trajectory tracking accuracy, pronounced jitter over undulating terrain, and limited disturbance rejection in orchard mobile robots, this paper proposes a trajectory tracking control strategy based on a double-loop adaptive sliding mode. Firstly, a kinematic model of the orchard robot is constructed and a time-varying integral terminal sliding surface is designed to achieve global fast finite-time convergence. Secondly, a sinusoidal saturation switching function with a variable boundary is employed to suppress the high-frequency chattering inherent in sliding mode control. Thirdly, an improved double-power reaching law (Improved DPRL) is introduced to enhance disturbance rejection in the inner loop while ensuring continuity of the outer-loop output. Finally, Lyapunov stability theory is used to prove the asymptotic stability of the double-loop system. The experimental results show that attitude angle error settles within 0.01 rad after 0.144 s, while the position errors in both the x-axis and y-axis directions settle within 0.01 m after 0.966 s and 0.753 s, respectively. Regarding position error convergence, the Integral of Absolute Error (IAE)/Integral of Squared Error (ISE)/Integral of Time-Weighted Absolute Error (ITAE) are 0.7629 m, 0.7698 m, and 0.2754 m, respectively; for the attitude angle error, the IAE/ISE/ITAE are 0.0484 rad, 0.0229 rad, and 0.1545 rad, respectively. These results indicate faster convergence of both position and attitude errors, smoother control inputs, and markedly reduced chattering. Overall, the findings satisfy the real-time and accuracy requirements of fast trajectory tracking for orchard mobile robots. Full article

The photonic spin Hall effect (PSHE) has emerged as a powerful metrological approach for precision measurements. Dynamic manipulation of PSHE through external stimuli could substantially expand its applications. In this work, we present a simple and active modulation scheme for PSHE in a surface plasmon resonance (SPR) structure by exploiting electric-field-tunable refractive indices of electro-optic materials. By applying an electric field, the enhancement of PSHE spin shifts is observed, and the dual-field control can further amplify these spin shifts through synergistic effects in this SPR structure. Notably, various operation modes of external electric field enable the real-time switching between two high-performance sensing functionalities (refractive index detection and angle measurement). Therefore, our designed PSHE sensor based on SPR structure with a simple structure of only three layers not only makes up for the complex structure in multi-functional sensors, but more importantly, this platform establishes a new paradigm for dynamic PSHE manipulation while paving the way for advanced multi-functional optical sensing technology. Full article

This work presents a high-common-mode-rejection-ratio (CMRR) and high-gain FinFET-based bio-potential amplifier with a novel CMRR reduction technique. In this paper, a feedback buffer is used alongside a capacitively coupled chopper-stabilized circuit to reduce the common-mode signal gain, thus boosting the overall CMRR of the circuit. The conventional pseudoresistor in the feedback circuit is replaced with a tunable parallel-cell configuration of pseudoresistors to achieve high linearity. A chopper spike filter is used to mitigate spikes generated by switching activity. The mid-band gain of the chopper-stabilized amplifier is 42.6 dB, with a bandwidth in the range of 6.96 Hz to 621 Hz. The noise efficiency factor (NEF) of the chopper-stabilized amplifier is 6.1, and its power dissipation is 0.92 µW. The linearity of the parallel pseudoresistor cell is tested for different tuning voltages (V_tune) and various numbers of parallel pseudoresistor cells. The simulation results also demonstrate the pseudoresistor cell performance for different process corners and temperature changes. The low cut-off frequency is adjusted by varying the parameters of the parallel pseudoresistor cell. The CMRR of the chopper-stabilized amplifier, with and without the feedback buffer, is 106.9 dB and 100.3 dB, respectively. The feedback buffer also reduces the low cut-off frequency, demonstrating its multi-utility. The proposed circuit is compatible with bio-signal acquisition and processing. Additionally, a machine learning-based arrhythmia diagnosis model is presented using a convolutional neural network (CNN) + Long Short-Term Memory (LSTM) algorithm. For arrhythmia diagnosis using the CNN+LSTM algorithm, an accuracy of 99.12% and a mean square error (MSE) of 0.0273 were achieved. Full article

A fast terminal sliding mode control based on a fixed-time sliding surface is proposed for a permanent magnet arc motor (PMAM), effectively improving speed response, control accuracy, and disturbance rejection capability. Due to its piecewise structure and advanced logarithmic characteristics, a PMAM is subject to high-frequency disturbances. Additionally, it is also influenced by external disturbances. To address this, a sliding mode reaching law that combines terminal terms, linear terms, and switching terms is designed to reduce chattering and enhance robustness. Furthermore, to improve the convergence speed of the sliding mode and disturbance rejection ability, a novel fixed-time converging sliding surface based on a variable exponent terminal term is introduced. Numerical simulations verify the convergence and disturbance rejection capabilities of the proposed sliding surface. Stability based on the Lyapunov theorem is strictly proven. Experimental results validate the effectiveness and superiority of the proposed algorithm. Full article

With the proliferation of wind power generation, the receiving end grids exhibit unprecedented dynamic characteristics, imposing critical stability challenges on grid-connected wind turbine’s converter. To address this, wind turbine converter control strategies have evolved beyond traditional grid-following (GFL) methods to include grid-forming (GFM), mode-switching, and hybrid GFL-GFM controls. This paper establishes a small-signal model for hybrid GFL-GFM-controlled wind turbines to analyze stability at varying grid strengths, guiding the selection of coefficients in hybrid mode. Simulation tests validate the theoretical framework. Full article

The Dynamic Voltage Restorer (DVR), which is connected in series between the power grid and the load, can rapidly compensate for voltage disturbances to maintain stable voltage at the load end. To enhance the energy supply capacity of the DVR and utilize its shared circuit topology with photovoltaic (PV) inverters—which enables the dual functions of voltage compensation and PV-storage power generation—this study integrates PV and energy storage as a coordinated energy unit into the DVR, forming a PV-storage-integrated DVR system. The core innovation of this system lies in extending the voltage disturbance detection capability of the DVR to include harmonics. By incorporating a Butterworth filtering module and voltage fluctuation tracking technology, high-precision disturbance identification is achieved, thereby supporting power balance control and functional coordination. Furthermore, a multi-mode-power coordinated regulation method is proposed, enabling dynamic switching between operating modes based on PV output. Simulation and experimental results demonstrate that the proposed system and strategy enable smooth mode transitions. This approach not only ensures reliable voltage compensation for sensitive loads but also enhances the grid-support capability of PV systems, offering an innovative technical solution for the integration of renewable energy and power quality management. Full article

This paper presents a small-signal model of a series resonant converter under continuous conduction mode, based on asymmetric pulse-width modulation, which is commonly used under light-load conditions. When controlled using conventional pulse-frequency modulation, the series resonant converter (SRC) suffers from insufficient resonant current under light loads, leading to degraded soft-switching performance, increased switching losses, and reduced efficiency due to the need for higher switching frequencies to maintain output regulation. To address these issues, the asymmetric pulse-width modulation with a fixed switching frequency is required to improve efficiency. In this study, a small-signal model is derived using the Extended Describing Function method. Based on this model, transfer functions are obtained and verified through MATLAB(R2024a), switching model-based PLECS(4.7.5) simulations, and experimental results. Full article

Medium-voltage energy storage converter equipment is an important component of the new generation of ship power and power systems. Virtual space vector pulse width modulation, as a modulation optimization method to improve the neutral-point voltage imbalance in medium- and high-voltage multilevel energy storage converters, has become a research hotspot for T-type three-level energy storage inverter modulation methods due to its significant balancing effect and simple implementation. However, the current research method of constructing virtual vectors through redundant small vectors has limitations in regulating the neutral-point potential under full (especially high) modulation ratios. This paper proposes a modulation method that uses hybrid variable virtual small vectors and virtual medium vectors through optimization selection and reconstruction of basic vectors. This method ensures that the neutral-point charge change of the vector is zero and the common-mode voltage is minimized within the switching period under the full modulation ratio, achieving the purpose of controlling the neutral-point voltage balance and suppressing the common-mode voltage. Finally, simulation and experimental results show that the proposed method has good neutral-point voltage regulation and common-mode voltage suppression capabilities within the full modulation ratio range, and the system also has strong robustness and adaptability under different load conditions. Full article

With the increasing switching frequencies and power densities in modern power converters, the prediction and mitigation of common-mode (CM) noise are becoming increasingly essential. Even though powerful, simulation methods are hindered by the difficulties in modeling power semiconductors and the long simulation time. As an alternative, the measurement-based substitution model is demonstrated in the paper, which simplifies the non-linear converter with a linear circuit network with multiple independent sources. Transfer functions are then defined and characterized to evaluate the conversion ratio from different sources to the CM noise produced on the attached cables. Good agreements are observed between the predicted and measured CM noise under several test conditions. Additionally, the proposed method facilitates dominant noise source identification and the corresponding noise suppression. The proposed method offers advantages over the existing approach, including simplicity in the characterization of transfer functions and the least disturbance to the test setup. Full article

This study investigates how rereading and different annotation styles affect the reading experience, proposing a system called Echo Read. It compares traditional literary annotations with SNS-style ones and enables mode switching among plain text, traditional, and SNS annotations. A theoretical framework views reading as a multidimensional process across temporal and spatial axes. An experiment with participants reading under three annotation modes collects data via surveys, logs, and interviews. This study aims to show how annotations enhance comprehension, reflection, and social engagement, contributing to new understandings of digital reading and practical applications in education and culture. Full article

Three-level non-inverting buck–boost converters are promising for electric vehicle charging stations due to their wide voltage regulation capability and bidirectional power flow. However, the number of three-level operating states is four times that of two-level operating states, and the lack of a unified switching state selection mechanism leads to serious challenges in its application. To address these issues, a finite control set model predictive control (FCS-MPC) strategy is proposed, which can determine the optimal set and select the best switching state from the excessive number of states. Not only does the proposed method achieve fast regulation over a wide voltage range, but it also maintains the input- and output-side capacitor voltage balance simultaneously. A further key advantage is that the number of switching actions in adjacent cycles is minimized. Finally, a hardware-in-the-loop experimental platform is built, and the proposed control method can realize smooth transitions between multiple operation modes without the need for detecting modes. In addition, the state polling range and the number of switching actions are superior to conventional predictive control, which provides an effective solution for high-performance multilevel converter control in energy systems. Full article

Hybrid electric vehicles (HEVs) have gained significant attention for their superior energy efficiency and are becoming a predominant mode of urban transportation. The DC/DC converter plays a critical role in HEV energy management systems, especially in matching the voltage levels between the battery and DC bus. This paper proposes a novel high-gain DC/DC converter with a wide input voltage range based on coupled inductors. The innovation lies in the integration of a resonant cavity and the simultaneous realization of zero-voltage switching (ZVS) and zero-current switching (ZCS), effectively reducing both voltage/current stresses on the power switches and switching losses. Compared with conventional topologies, the proposed design achieves higher voltage gain without extreme duty cycles, improved conversion efficiency, and enhanced reliability. Detailed operating principles are analyzed, and design conditions for voltage stress reduction, gain extension, and soft switching are derived. The simulation model has been conducted in a PSIM environment, and a 300 W experimental prototype, implemented using a dsPIC33FJ64GS606 digital controller, has been established and demonstrates 93% peak efficiency at a 10 times voltage gain. The performance and practical feasibility of the proposed topology have been evaluated by both simulation and experiments. Full article

In this paper, we address the problem of jerk and disturbance suppression during mode transitions in power-split hybrid electric vehicles. First, a transient switching model of the PS-HEV is developed. Next, the mechanisms underlying shock generation and the influence of disturbances on transition smoothness are analyzed. Based on this, a fixed-time dynamic coordinated control strategy is proposed, comprising a novel sliding mode control law and a fixed-time extended state observer. The proposed fixed-time sliding mode control law is independent of initial state values and ensures superior convergence performance. Meanwhile, the fixed-time extended state observer enables real-time estimation of external disturbances, thereby reducing the conservatism of the control law. Finally, simulation and hardware-in-the-loop results demonstrate that the proposed strategy markedly improves mode transition performance under various disturbance scenarios. This work provides a new perspective on hybrid mode transition control and effectively enhances transition smoothness. Full article