Search Results (1,655)

The characterization of supercapacitors (SCs), particularly electric double-layer capacitors (EDLCs), is useful for the design of energy management systems. This article presents a five-parameter dynamic model based on electrochemical impedance spectroscopy (EIS) data. Unlike conventional fixed-parameter models, this study explores an approach that accounts for voltage dependence. The model was evaluated using four commercial 58-farad SCs over a frequency range of 10 mHz to 300 kHz and at voltages ranging from 6.25% to 93.75% of the nominal value. The results show that the parameters vary with the state of charge; for example, the effective capacitance increased by up to 24% when moving from 6.25% to 50% of the nominal voltage. The model, fitted using nonlinear optimization algorithms, has a mean square percentage error (MSPE) of less than 3%. This approach estimates the dynamic behavior of the SCs, facilitating the simulation and tuning of management and protection strategies. Full article

Lithium-ion batteries (LiBs) are fundamental to modern energy systems, particularly in electric vehicle (EV) applications, due to their high energy density, long cycle life, and low self-discharge characteristics. Accurate State-of-Charge (SoC) estimation is essential for ensuring reliable performance, efficient energy usage, and the safety of Battery Management Systems (BMSs). However, the nonlinear and time-varying characteristics of LiBs, along with the difficulty in directly measuring internal states, pose significant challenges for parameter identification and SoC estimation. This study presents an advanced approach based on the Weighted Mean of Vectors optimization algorithm to simultaneously identify the unknown parameters of an extended Thevenin Equivalent Circuit Model (ECM) and estimate the SoC. Unlike previous methods that use static parameters for specific battery modes, the proposed technique accounts for dynamic changes during both charging and discharging operations. The algorithm demonstrates superior adaptability by continuously adjusting model parameters to reflect real-time battery behavior under varying operational conditions. The algorithm also models the relationship between SoC and open-circuit voltage (Voc) using data collected from real lithium-ion cells tested under a controlled load profile in the laboratory. This experimental validation ensures the practical applicability and robustness of the proposed methodology. The simulation results confirm the effectiveness and precision of the proposed approach, showing excellent agreement between measured and estimated values, with minimal errors in both voltage and SoC prediction. The enhanced accuracy achieved through this dynamic parameter identification framework represents a significant advancement in battery state estimation technology. Full article

To address the issue of significantly reduced coupling coefficient and limited transmission efficiency in traditional flat solenoid magnetic couplers within wireless power transfer (WPT) systems under horizontal lateral offset conditions, this paper proposes a design method for a concave flat solenoid coil magnetic coupler for engineering applications, aiming to achieve high misalignment tolerance. An equivalent model of the LCC/S compensation circuit is established, its output characteristics are analyzed, and the parameter configuration method for its resonant elements is derived. Secondly, from the perspective of winding arrangement, the mechanism by which the coil winding method, turn spacing, and port concavity angle affect the uniformity of magnetic field distribution and the retention rate of the coupling coefficient is analyzed in detail, and corresponding parameter trade-off and optimization methods are proposed. Subsequently, a simulation model of multiple configuration magnetic couplers is established based on Ansys/Maxwell, comparing the magnetic field distribution and coupling coefficient variation of different structures under horizontal offset conditions. The results show that the concave structure with a non-uniform arrangement and a port concavity angle of 30° can still maintain a high coupling coefficient and stable transmission performance under a maximum horizontal offset equal to 60% of the corresponding transmitter-side characteristic dimension. To achieve lightweight and integrated design, the receiver is designed with a flexible printed circuit board (FPC) coil structure, meeting the miniaturization and high power density requirements of low-to-medium power portable devices. Finally, a 100 W experimental prototype was built. Experimental results show that within an offset range of ±15 mm on the X-axis and ±30 mm on the Y-axis at the receiver, the system output voltage fluctuation is controlled within 4%, and the maximum transmission efficiency reaches 87.3%. These results verify the feasibility and practical applicability of the proposed magnetic coupler with high misalignment tolerance. Full article

Virtual Synchronous Generator (VSG) has become a prominent candidate to control grid-tied power electronic inverters for its ability to provide inertial support and improve power system frequency stability. However, under disturbances, VSG exhibits significant oscillations in its output frequency and power. Meanwhile, existing oscillation suppression methods rely on somewhat complex modeling and cumbersome parameter tuning. To address this issue, this paper proposes a straightforward approach to improving the transient performance of VSG based on the equivalent circuit model of the VSG active power loop. First, it is shown that the parameters in the VSG active power loop have a one-to-one correspondence with the elements of a RLC circuit. Based on the equivalent circuit model of VSG control, it is demonstrated that under the constraints of ROCOF and power–frequency droop limitation, oscillation suppression cannot be effectively achieved only by parameter tuning. Thus, an additional damping resistance branch is introduced into the VSG equivalent circuit model. The quantitative parameter design method of this damping branch is further introduced. Finally, high-power experiments demonstrate that the proposed method effectively suppresses power oscillations and enhances the transient performance of VSGs. Full article

Proton exchange membrane fuel cells (PEMFCs) play a key role in hydrogen-based energy systems; however, accurate and practical modelling remains challenging due to system nonlinearities, parameter variability, and degradation effects. This paper presents a low-complexity parameter estimation methodology for a simplified PEMFC equivalent circuit model using current-switching techniques. The approach enables direct extraction of key parameters, including internal resistance and capacitance, from transient voltage responses without requiring complex optimization or large datasets. Experimental validation was conducted using 100 W and 1 kW PEMFC systems under current loading and interruption conditions. The results demonstrate good agreement between measured and simulated voltage responses, with a maximum error below 10% and typical error levels in the range of ~1.4–3%. Compared to conventional mechanistic and data-driven models, the proposed method significantly reduces computational complexity and measurement requirements while maintaining high predictive accuracy. Moreover, the combination of the simplified equivalent circuit model with current-switching-based parameter estimation offers an effective and practical tool for electrical engineers, enabling real-time monitoring, control-oriented modelling, and seamless integration with power electronic systems. The proposed approach is particularly suitable for applications in DC microgrids and digital twin-based monitoring of hydrogen energy systems. Full article

State-of-charge (SOC) and state-of-health (SOH) of lithium-ion batteries are critical parameters in battery management systems, directly impacting the driving range, performance stability, and safety of electric vehicles. To improve the accuracy and stability of SOC and SOH estimation simultaneously, this paper proposes a joint estimation method with constant-current bias compensation. First, based on a second-order RC equivalent circuit model, a constant-current bias compensation term is introduced into the Kalman filter framework. The estimation accuracy and robustness of SOC are validated under multiple operating conditions and noise levels. Then, a model integrating Transformer and gated recurrent unit is constructed. The fata morgana algorithm (FATA) is adopted for hyperparameter optimization. Ablation studies and multi-model comparative experiments are conducted to verify the model’s accuracy. Finally, capacity correction is performed using SOH results. By combining current bias compensation and precise temporal features extracted from aging data, joint estimation of SOC and SOH is achieved. Results show that after introducing current bias compensation and aging-based capacity correction, the accumulated SOC estimation error is reduced by more than 10%, while SOH estimation achieves a MAPE below 0.90% and an RMSPE below 1.10%. The proposed joint method is thus verified to be accurate and practical. Full article

To address the low efficiency of finite element modeling and the reliance on manual measurements in electric/magnetic field analysis of complex overhead transmission line structures, this paper develops an IronPython-based automated computational platform within ANSYS Maxwell for 3-D modeling and electric/magnetic field analysis. First, by parsing transmission line data from the Grid Information Model (GIM), a unified coordinate transformation method is proposed to convert geographical coordinates into three-dimensional (3-D) Cartesian coordinates for finite element analysis. Based on the extracted line parameters, conductor sag is calculated and catenary modeling is implemented. An equivalent radius method is also introduced to simplify multi-bundle conductor modeling, enabling fast parametric construction of complex 3-D transmission line models. Second, by combining the IronPython scripting language with the .NET Windows Forms control library, a visualized finite element modeling and computation platform is developed. Finally, a typical double-circuit transmission line on the same tower is taken as a case study to calculate the spatial distribution of electric/magnetic fields. The influence of solution domain size on electric/magnetic field computation results is investigated, and optimal solution domain parameters are determined. The finite element results generated by the developed platform are further validated through comparison with measured data. The results demonstrate good agreement between calculated and measured values, confirming the accuracy and engineering applicability of the developed platform for electric/magnetic environment analysis of overhead transmission lines. Full article

Peripheral nerve injuries pose a significant clinical challenge due to the limited self-repair capacity and the complexity of neural tissue architecture. Tissue engineering strategies applied to the peripheral nerve system aim to restore functional nerve constructs by combining scaffolds, cells, and biochemical cues to recreate the native microenvironment. This work aimed to propose the electrical conductivity as a functional readout of structural and biological remodeling in engineered peripheral nerve scaffolds, along with functional and molecular evaluations. To this end, bioimpedance measurements were combined with equivalent circuit modeling to track state-dependent changes across different levels of tissue organization. Murine sciatic nerves were decellularized and recellularized with neural populations to generate engineered constructs, and their electrical properties were assessed using broadband bioimpedance spectroscopy. Distinct impedance profiles were observed across control, decellularized, and recellularized samples, reflecting structural and functional changes associated with cell removal and repopulation. Furthermore, a multilayer series RC circuit model was implemented to accurately reproduce the measured spectra, enabling the extraction of layer-specific electrical parameters. Analysis of these parameters revealed that decellularization reduces compartmental resistances and increases inter-layer coupling, whereas recellularization restores outer-layer resistances and reduces coupling, consistent with functional tissue organization. Overall, the results demonstrate that bioimpedance provides a readout of the scaffold biological state and cellular integration, and that equivalent circuit modeling offers a quantitative framework to link structural remodeling to electrical function in engineered peripheral nerve tissues. Full article

Accurate estimation of the State of Charge (SOC) of lithium-ion batteries is one of the core functions of a battery management system and is of great significance for ensuring the safe operation of electric vehicles and optimizing energy utilization. However, due to the strong nonlinearity, time-varying characteristics, and interference from complex operating conditions within the battery, high-precision SOC estimation faces severe challenges. To address the problems that a single data-driven method lacks physical constraints and a single model-driven method struggles to characterize complex nonlinearities, this paper proposes a series-connected LSTM-UKF fusion estimation method. This method first utilizes a Long Short-Term Memory network to learn the dynamic characteristics of the battery from historical voltage and current data, capturing the long-term dependencies of SOC changes to achieve an initial prediction. Subsequently, using this predicted value as the observation input, an Unscented Kalman Filter based on a second-order RC equivalent circuit model is introduced for optimal state correction, effectively suppressing model uncertainty and measurement noise. Simulation validation under various dynamic conditions, such as constant current discharge and FUDS, shows that compared to single LSTM or UKF algorithms, the proposed fusion method has significant advantages in estimation accuracy, convergence speed, and robustness. Its root mean square error is reduced to 0.0031, and it maintains stable estimation performance under different operating conditions. This study provides an effective data-model fusion solution for high-precision SOC estimation of lithium-ion batteries under complex operating conditions. Full article

Driven by the goal of sustainable energy transitions, the integration of Inverter-Interfaced Distributed Generation (IIDG) has led to a continuous decline in the accuracy of single-phase grounding fault line selection in neutral non-effectively grounded distribution networks. Protection methods based on characteristic signal injection currently struggle to balance the differentiated requirements of fault detection sensitivity and equipment safety in networks with high-penetration IIDG. To address this issue, a high-frequency equivalent circuit model of the IIDG is established. The distribution patterns of the high-frequency characteristic current (HFCC) in distribution networks under high-penetration IIDG are analyzed. Subsequently, an adaptive HFCC injection strategy is proposed, which accounts for IIDG low-voltage ride-through (LVRT) requirements, fault identification sensitivity, and equipment safety constraints. Based on the amplitude and phase differences in the HFCC between faulty and healthy feeders, a fault line selection criterion is established. Consequently, an adaptive injection-based protection method for single-phase grounding fault is developed, considering the impact of high-penetration IIDG. Simulation results demonstrate that the proposed method accurately identifies the faulty feeder under various fault locations, transition resistances, and quantities of integrated IIDG units. The results further confirm the high adaptability and reliability of the method, thereby providing a robust technical foundation for the safe, reliable, and sustainable operation of modern power grids. Full article

Double stator cylindrical linear oscillating generators (DSCLOGs) have been widely used in renewable energy power generation systems due to their higher power density, higher reliability, and low-noise characteristics. However, the detent force of a DSCLOG is an inevitable problem, which causes oscillations in the generator and leads to system instability. Conventionally, auxiliary teeth and skewed pole methods are employed to mitigate detent force, but these approaches often increase the overall machine size and the complexity of the manufacturing process. To solve this issue, an improved DSCLOG with curved teeth (CT-DSCLOG) is proposed to minimize the detent force. First, the structural characteristics and working principle of CT-DSCLOG are introduced. Then, to achieve a rapid and accurate analysis of the magnetic field in the irregular air gap, a 2D magnetic equivalent circuit (MEC) model is established by introducing Schwarz–Christoffel (S-C) mapping. And key structural parameters are identified through variance sensitivity analysis. Subsequently, a multi-objective optimization of the linear generator is performed using the Taguchi method combined with 3D finite element analysis (3D-FEA) to obtain the optimal structural parameters of CT-DSCLOG. Finally, the proposed structure is validated through prototype experiments. The results are provided to validate the effectiveness of the proposed structure. Full article

Vehicle recharge time is a key barrier to widespread adoption of battery electric trucks, where megawatt class charging could be used to achieve refueling times comparable to internal combustion vehicles. This work presents the design and validation of a megawatt-capable rechargeable energy storage system (144 kWh, 40P384S) together with a physics-based modeling framework for safe 1 MW operation. The pack architecture is reconfigurable, enabling nominal 750 V (80P192S) propulsion mode as well as 1125 V and 1500 V charging modes compatible with the Megawatt Charging System (MCS). An equivalent circuit model is developed to relate cell-level parameters to pack-level power, heat generation, and temperature rise, providing guidance on feasible charge profiles and thermal limits. A Simulink-based digital twin of the reconfigurable pack is then used to analyze sensitivity to current sensor mismatch and to verify protection logic for multiple bus voltage configurations. Finally, pack tests up to 1 MW confirm the model-predicted operating envelope and illustrate practical constraints imposed by charger voltage and pack resistance. The combined hardware and modeling approach provides a reusable platform for studying extreme fast charging of medium- and heavy-duty BEV packs-class charging -capable rechargeable energy storage system (144 kWh, 40P384S) together with a physics-based modeling framework for safe 1 MW operation. The pack architecture is reconfigurable, enabling nominal 750 V (80P192S) propulsion mode as well as 1125 V and 1500 V charging modes compatible with the Megawatt Charging System (MCS). An equivalent-circuit model is developed to relate cell-level parameters to pack-level power, heat generation, and temperature rise, providing guidance on feasible charge profiles and thermal limits. A Simulink-based digital twin of the reconfigurable pack is then used to analyze sensitivity to current–sensor mismatch and to verify protection logic for multiple bus-voltage configurations. Finally, pack tests up to 1 MW confirm the model-predicted operating envelope and illustrate practical constraints imposed by charger voltage and pack resistance. The combined hardware and modeling approach provides a reusable platform for studying extreme fast charging of medium- and heavy-duty BEV packs. Full article

High-pressure water injection (HPWI) can rapidly replenish the formation energy of low-permeability reservoirs, but it may trigger multi-scale fractures, leading to premature water breakthrough between injection and production wells. To identify the main causes and regulate the mainstream line (i.e., the preferential flow path with the highest streamline density/flow rate), a two-zone and five-point numerical model was developed. This model couples the static damage zone (dominated by micro-fractures) and the fracture development zone (dominated by macro-fractures). Through sensitivity analysis, the ways in which micro-fracture damage and macro-fracture geometry control the evolution of seepage patterns and the risk of water breakthrough were quantified. The results show that in the representative scenarios of this paper, micro-fracture damage is mainly associated with an increased risk of water breakthrough by forming equivalent weakening zones and enhancing the directional extension trend of main fractures. The scale of macro-fractures has the strongest correlation with the water breakthrough response. When the fracture scale increases to a certain proportion close to the well spacing, the seepage mode changes from “fracture + matrix cooperation” to “main-fracture-dominated short-circuit channel”. Based on this, a design and verification of a combined control scheme of “chemical profile control + cyclic water injection” was proposed and carried out in well groups with high water cut and strong channeling. Simulations show that this combination helps to weaken the flow conductivity of preferential channels and improve the uniformity of the flow field. This paper can provide technical support for the prevention, control, and early warning of water breakthrough and the regulation of main flow lines in the high-pressure water injection development of similar low-permeability reservoirs. Full article

This paper proposes a small size meander-line patch antenna which is designed to have biomedical telemetry applications using the Industrial, Scientific and Medical (ISM) band from 2.40 to 2.48 GHz supported by the equivalent circuit model (ECM). Antenna miniaturization is realized by the effective use of several slot structures placed in the rectangular microstrip patch structure, in order to realize electrical length extension and reduce the physical size. The antenna has overall dimensions of 12 × 22 × 0.787 mm³ and is made on a low-loss Arlon AD 450 (ε_r = 4.50 and tanδ = 0.0035) dielectric substrate, which has the desired stable electrical behavior and, importantly, can be used in implantable environments. Experimental validation is done by implanting the fabricated prototype into a laboratory-manufactured tissue-mimicking phantom, and it showed good agreement with simulated results. The designed antenna has a peak gain of 1.29 dBi in free space and −24.99 dBi at a frequency of 2.45 GHz and a fractional impedance bandwidth of about 250 MHz, which will guarantee reliable operation in the face of diversity and fluctuation in the surrounding environment (biological tissues). Furthermore, specific absorption rate (SAR) analysis is carried out in order to comply with international safety standards with peak SAR values kept within the permissible level of 2 W/kg for 10 g averaging tissue. The results show that the proposed antenna provides a good trade-off between the reduction in size, radiation performance and safety to the patient, making it a good candidate for short-range in-body wireless communication, implantable medical devices, and biomedical monitoring systems. Full article

High concentrations of ionized ammonia (${\mathrm{NH}}_4^{+}$) have been increasingly reported in municipal drinking water systems, posing a severe public health risk as excessive ingestion can lead to life-threatening conditions. Despite its importance, there is a significant lack of sensing technologies designed for continuous-flow monitoring outside laboratory settings, particularly those providing a robust, low-cost methodology suitable for resource-limited environments. To address these challenges, in this work, we report the development of an impedance sensor featuring a 3D-printed housing (3D-IS) for monitoring aqueous ionized ammonia (${\mathrm{NH}}_4^{+}$). The sensing electrodes, composed of zinc oxide and graphite, allow for the detection of concentrations 10 times lower and 60 times higher than current environmental limits. Its innovative, optimized design, analogous to that of industrial pressure gauges, highlights its potential for use in continuous water flow conditions outside the laboratory, such as water treatment plants. The level of ${\mathrm{NH}}_4^{+}$ in water is monitored by changes in impedance magnitude, with optimal performance observed at a frequency of 100 kHz. At this frequency, the impedance magnitude decreased by nearly two orders of magnitude as the ${\mathrm{NH}}_4^{+}$ concentration increased from 0 to 1 μM. Under these optimized conditions, the sensor exhibited a sensitivity of 2 kΩ/log(μM) and a linearity exceeding 90%. Furthermore, we propose an equivalent circuit model that accurately describes the experimental data, explaining the transduction process. We also describe, from an electrical perspective, the phenomenon of adsorption on the sensor’s transducer surface, thereby ensuring the device’s selectivity. The sensor was evaluated using dilutions of a standard ammonium solution for IC in distilled water, as well as with real groundwater samples, obtaining ∼99.7% of correlation with ion chromatography and a limit of detection of 2 μM. Finally, our device can provide information relatively quickly, with the added advantage of stable response under continuous-flow and real conditions, making it an attractive option for integration into a field sensor node. Full article