Search Results (53)

To address the limitations of conventional LC resonant battery equalization circuits, including slow balancing speed under small voltage differences, limited scalability in multi-cell configurations, and the risk of over-equalization, this paper proposes a dual-layer LC resonant equalization topology integrated with a Boost-assisted mechanism and a state-of-charge (SOC)-based dual closed-loop current control strategy. In the proposed topology, a Boost converter is introduced to actively enhance the effective voltage difference between cells, thereby improving the equalization current amplitude and accelerating the balancing process. A switched-inductor structure is further adopted to enable scalable inter-group energy transfer in multi-cell battery systems. To improve control accuracy, SOC is selected as the balancing variable, and a dual closed-loop control framework is designed, where the outer loop regulates SOC deviation, and the inner loop controls the equalization current via proportional–integral (PI) controllers. A MATLAB/Simulink model is established to evaluate the proposed method under multiple operating conditions, including idle, charging, and discharging states. The results show that the proposed topology significantly reduces the equalization time compared with conventional LC resonant circuits and improves balancing speed by approximately 49% under the dual closed-loop control strategy. In addition, the system maintains stable performance across different operating conditions. It should be noted that this study focuses on topology design and control strategy validation through simulation. Due to the focus on topology validation and control mechanism analysis, this study is limited to simulation-based verification. Experimental implementation will be conducted in future work. Full article

In low-voltage-input, high-voltage-output applications, the input-parallel output-series (IPOS) LLC resonant converter experiences voltage and current imbalances due to parameter mismatches in resonant tank components. To address this issue, a self-balancing IPOS LLC resonant converter based on a shared inductance–capacitance (shared L-C) network is proposed. This topology achieves passive voltage and current self-equalization with an interconnection network of resonant inductors and capacitors between modules that does not need additional active components or complex control strategies. An analytical model based on the fundamental harmonic approximation (FHA) is developed to quantitatively assess the balancing performance, and a comparison is made with traditional structures and IPOS structures with only shared inductance. A 1.25 kW two-phase LLC resonant converter prototype is built for experimental validation. The results demonstrate that the balancing errors of the traditional structure and the shared inductance structure reach up to 25.43% and 17.63%, respectively, whereas the proposed structure significantly reduces the balancing error to only 0.43%. This study confirms that this structure provides a simple and reliable solution for voltage and current equalization in high-gain DC–DC conversion systems. Full article

To address the state-of-charge (SOC) imbalance and the limited convergence speed of conventional SOC balancing strategies in cascaded power conversion systems (PCSs) under practical grid-connected conditions, this paper investigates the control of cascaded H-bridge energy storage converters under multiple operating scenarios. The three-phase cascaded H-bridge topology is first reviewed, followed by the development of a hierarchical control framework for the cascaded PCSs. The corresponding overall control block diagram is then presented. Based on this, a unified power equalization control strategy based on the third harmonic injection is proposed, which ensures the effectiveness of power control, SOC equalization control, and fault-tolerant control by increasing the injection range, and it guarantees the normal operation of the cascaded PCSs. Considering the phase relationship of the PCS output voltage after the third harmonic injection, the maximum zero-sequence voltage injection range is found, and the constraints of zero-sequence voltage injection are derived. A MATLAB/Simulink simulation model and a real-time hardware-in-the-loop (HIL) platform based on the MT6016 are established to validate the effectiveness and practical feasibility of the proposed control strategy. Full article

Supercapacitor modules for energy storage systems often require complex active balancing circuits to manage voltage imbalances between series-connected cells. This paper proposes a modified forward converter topology that passively charges and balances supercapacitor modules simultaneously. The proposed solution is modular, provides galvanic isolation, and is self-regulating, eliminating the need for dedicated sensors or complex control logic. Voltage equalization is achieved autonomously through coupled inductors, naturally directing current to the cells with the lowest voltage during the period when the converter is off. This work details the operating principle of the converter and analyzes two architectures: a non-crossover configuration and a crossover configuration. This study validated the system performance through PSIM simulations and a hardware prototype. The experimental results demonstrate that both configurations successfully charge and balance the supercapacitors. However, the crossover and non-crossover configurations achieve faster equalization under certain imbalance conditions. In contrast, the crossed configuration exhibits a smaller final voltage discrepancy between cells compared to the non-crossover architecture. The proposed converter proves to be a simple, robust, and effective solution for managing supercapacitor modules. Full article

In recent years, the expansion of network scale and the diversification of attack methods pose dual challenges to intrusion detection systems in extracting effective features and addressing class imbalance. To address these issues, the Spatial–Temporal Equilibrium Graph Convolutional Network (STEGCN) is proposed. This model integrates Graph Convolutional Network (GCN) and Gated Recurrent Unit (GRU), leveraging GCN to extract high-order spatial features from network traffic data while capturing complex topological relationships and latent patterns. Meanwhile, GRU efficiently models the dynamic evolution of network traffic over time, accurately depicting temporal trends and anomaly patterns. The synergy of these two components provides a comprehensive representation of network behavior. To mitigate class imbalance in intrusion detection, the Equalization Loss v2 (EQLv2) is introduced. By dynamically adjusting gradient contributions, this function reduces the dominance of majority classes, thereby enhancing the model’s sensitivity to minority-class attacks. Experimental results demonstrate that STEGCN achieves superior detection performance on the UNSW-NB15 and CICIDS2017 datasets. Compared with traditional deep learning models, STEGCN shows significant improvements in accuracy and recall, particularly in detecting minority-class intrusions. Full article

Accurate intracranial artery segmentation from digital subtraction angiography (DSA) is critical for neurovascular diagnosis and intervention planning. Vascular extraction, which combines preprocessing methods and deep learning models, yields a high level of results, but limited preprocessing results constrain the improvement of results. We propose a texture-based contrast enhancement preprocessing framework integrated with the nnU-Net model to improve vessel segmentation in time-sequential DSA images. The method generates a combined feature mask by fusing local contrast, local entropy, and brightness threshold maps, which is then used as input for deep learning–based segmentation. Segmentation performance was evaluated using the DIAS dataset with various standard quantitative metrics. The proposed preprocessing significantly improved segmentation across all metrics compared to both the baseline and contrast-limited adaptive histogram equalization (CLAHE). Using nnU-Net, the method achieved a Dice Similarity Coefficient (DICE) of 0.83 ± 0.20 and an Intersection over Union (IoU) of 0.72 ± 0.14, outperforming CLAHE (DICE 0.79 ± 0.41, IoU 0.70 ± 0.23) and the baseline (DICE 0.65 ± 0.15, IoU 0.47 ± 0.20). Most notably, vessel connectivity (VC) dropped by over 65% relative to unprocessed images, indicating marked improvements in VC and topological accuracy. This study demonstrates that combining texture-based preprocessing with nnU-Net delivers robust, noise-tolerant, and clinically interpretable segmentation of intracranial arteries from DSA. Full article

This paper presents the design, implementation and experimental validation of a modular battery management system (BMS) featuring active cell balancing. The proposed BMS consists of a master module and multiple slave submodules responsible for monitoring and balancing 22 cells connected in series. The master module collects voltage and temperature data from the slave submodules and measures the battery current to estimate the cells’ state of charge (SoC). Each slave module performs cell voltage and temperature measurements and controls a balancing circuit based on dc-dc converters. This work describes in detail the development and validation of the dc-dc converter based in the switched inductor topology, presenting the converter’s operational principles, a theoretical and simulation-based analysis of its performance, the implementation of the MOSFETs driver circuits based on PNP transistors and experimental results obtained from a submodule prototype. The results demonstrate the capability of the switched inductor converter to achieve effective voltage equalization by transferring energy from the cells with higher voltages to cells with lower voltages. Full article

As the demand for second-life lithium-ion battery applications continues to grow, efficient cell equalization has become essential to mitigate parameter inconsistencies and extend system longevity. Owing to their diverse origins and varying aging paths, second-life batteries exhibit significant parameter dispersion, which poses distinct challenges. In light of these issues, this paper presents a comprehensive review of passive, active, and dynamic equalization technologies. It analyzes the circuit topologies and control strategies associated with each method, with a particular focus on their applicability to second-life battery systems. Furthermore, emerging trends toward intelligent, modular, and adaptive equalization are discussed. Full article

In this work, a battery active grouping equalization control strategy based on model predictive control (MPC) was proposed, which can promote cell consistency, equalization speed and energy loss during the battery equalization process. The dynamic group equalization topology based on reconfigurable circuits can achieve dynamic grouping. Using a battery state observation estimator and the MPC controller, multiple non-adjacent cells can realize simultaneous equalization in a single equalization process. An algorithm is designed to determine the optimal energy transfer direction and the optimal equalization current. The objective function of this algorithm incorporates weight coefficients that represent the relative importance of equalization time and energy loss. Simulation tests are conducted to evaluate the battery pack state-of-charge (SOC) root mean square, average temperature, and equalization time under various weight coefficients. Compared with two other traditional equalization control strategies, the proposed strategy reduces the equalization time by 43.93%, decreases the battery pack SOC variance by 50.18%, and improves the energy transfer efficiency by 0.59%. Full article

The lithium-ion battery equalization system is a critical component in Low-Earth Orbit (LEO) satellite power supply systems, ensuring the consistency of battery cells, maximizing the utilization of battery pack capacity, and enhancing battery reliability and cycle life. In DC bus satellite power systems, passive equalization technology is widely adopted due to its simple structure and ease of control. However, passive equalization suffers from drawbacks such as complex thermal design and limited operation primarily during battery charging. These limitations can lead to inconsistent control over the depth of discharge of individual battery cells, ultimately affecting the overall lifespan of the battery pack. In contrast, active equalization technology offers higher efficiency, faster equalization speeds, and the ability to utilize digital control methods, making it the mainstream direction for the development of lithium-ion battery equalization technology. Nevertheless, active equalization often requires a large number of switches and energy storage components, involves complex control algorithms, and faces challenges such as large size and reduced reliability. Most existing active equalization techniques are not directly applicable to DC bus satellite power systems. In this study, based on the operational characteristics of LEO satellite power storage batteries, an active–passive hybrid equalization topology utilizing a switching matrix is proposed. This topology combines the advantages of a simple structure, ease of control, and high reliability. Its feasibility has been validated through experimental results. Full article

In this study, we propose an active junction temperature control method specifically tailored for traction inverters based on active neutral point-clamped (ANPC) three-level topology. This approach not only enables real-time junction temperature equalization across switching devices, but also minimizes switching losses while preserving synchronous modulation. The methodology begins with a detailed formulation of the loss quantification model for ANPC inverters, establishing the relationship between predicted losses and switching vectors. Building on this foundation, we develop a loss equalization modulation control strategy featuring closed-loop loss control. The effectiveness and practicality of the proposed control method are rigorously validated using simulations and low-power experimental testing, demonstrating its potential to enhance both the reliability and efficiency of traction inverters. Full article

This paper introduces a model that automates the diagnosis of a patient’s condition, reducing reliance on highly trained professionals, particularly in resource-constrained settings. To ensure data consistency, the dataset was preprocessed for uniformity in size, format, and color channels. Image quality was further enhanced using histogram equalization to improve the dynamic range. Lung regions were isolated using segmentation techniques, which also eliminated extraneous areas from the images. A modified segmentation-based cropping technique was employed to define an optimal cropping rectangle. Feature extraction was performed using persistent homology, deep learning, and hybrid methodologies. Persistent homology captured topological features across multiple scales, while the deep learning model leveraged convolutional transition equivariance, input-adaptive weighting, and the global receptive field provided by Vision Transformers. By integrating features from both methods, the classification model effectively predicted severity levels (mild, moderate, severe). The segmentation-based cropping method showed a modest improvement, achieving 80% accuracy, while stand-alone persistent homology features reached 66% accuracy. Notably, the hybrid model outperformed existing approaches, including SVM, ResNet50, and VGG16, achieving an accuracy of 82%. Full article

To enhance equalization efficiency and address the issue of traditional equalization methods overlooking temperature factors, this paper proposes a multilayer equalization circuit for both intra-group and inter-group balancing. The traditional Buck-Boost equalization topology between groups is improved by incorporating a two-way interleaved inductor structure, which helps reduce equalization idle time. An adaptive fuzzy control equalization strategy for multiple objectives is applied to the topology. The state of charge (SOC) and temperature of the battery are used as key variables for equalization, with the equalization current dynamically adjusted based on changes in the SOC and temperature. This approach improves the balance between equalization speed and temperature control, reducing equalization time while limiting battery temperature rise. A simulation model is developed using MATLAB/Simulink. The simulation results demonstrate that, compared to the traditional Buck-Boost equalization topology, the proposed topology reduces equalization time by 15.1%. Additionally, under three different operating conditions, the equalization cotnrol strategy designed in this paper improves time efficiency by over 14% compared to traditional methods, while also reducing both the maximum temperature and temperature difference. Full article

As one of the important components of a ship, the ship’s integrated power system is an important safeguard for ships. In order to improve the service life of the ship’s power grid, the power system should be able to realize rapid reconstruction to ensure continuous power supply of important loads when the ship is attacked or fails suddenly. Therefore, it is of vital importance to study the reconfiguration technology of the ship’s integrated power system to ensure that it can quickly and stably cope with all kinds of emergencies in order to guarantee the safe and reliable navigation of the ship. This paper takes the ship’s ring power system as the research object and sets up the maximum recovery load and the minimum number of switching operations. The load is divided uniformly and the generator efficiency is balanced for the reconstruction of comprehensive function. It also sets up the system capacity, topology, and branch current limitations of the constraints to establish a mathematical model. The load branch correlation matrix method is used for branch capacity calculation and generator efficiency equalization calculation, and the load backup power supply path matrix is added on the basis of the matrix to judge the connectivity of some loads before reconfiguration. In this paper, for the network reconfiguration of the ship circular power system, which is a discrete nonlinear problem with multiple objectives, multiple time periods, and multiple constraints, we choose to use the particle swarm algorithm, which is suitable for global optimization, with a simple structure and fewer parameters; improve the particle swarm algorithm using the swarm exchange strategy by setting up two main and auxiliary swarms for global and local search; and exchange some of the particles with the golden ratio in order to keep the diversity of the populations. The simulation results of the network reconfiguration of the ship power system show that the improved algorithm can solve the power system network reconfiguration problem more effectively and provide a feasible reconfiguration scheme in a shorter time compared with the chaotic genetic algorithm under the same fault case test, and it also proves that the use of the swarm exchange particle swarm algorithm greatly improves the performance of reconfiguring the power grid of the ship. Full article

An AC (alternative current) power integration of distributed energies faces multi-fold challenges such as synchronization and weak grid-induced instability. In this study, a multi-terminal DC transformer is proposed for renewable energy clusters grid connection. The DC transformer provides multiple DC input ports for renewable energy collection, while the load port is connected to the medium-voltage DC grid via a modular multilevel converter (MMC). The multi-port topology enables flexible power transfer between multiple input sources to the load without additional components. The carrier layer modulation strategy is implemented to balance the MMC module voltage; bidirectional power transmission between multiple input sources is achieved through the phase shift modulation (PSM) method. First, we provided a detailed introduction of the proposed topology and working principle. A simulation model was built using the SIMULINK, and the simulation results verified the effectiveness of the proposed converter modulation strategy and phase shift modulation method. A corresponding hardware experimental platform was designed and built, and the modulation and voltage equalization functions of modular multilevel rectifiers were presented as well as the measured results of power transmission modulation of the converter under single-input and multi-input conditions. The results indicate that the proposed transformer can achieve multiple DC inputs and has multi-channel power transmission capabilities, making it suitable for renewable energy clusters grid connection. Full article