Search Results (779)

Based on the photoconductive effect of photosensitive films, a designed light pattern was projected onto a hydrogenated amorphous silicon (a-Si:H) photosensitive chip to generate virtual light-induced electrodes for cellular electrical detection. To obtain high-quality cellular signals, this study aims to explore the effect of electrical excitation on a-Si:H photosensitive chip. Firstly, the electrochemical impedance spectroscopy (EIS) and volt-ampere characteristics of the a-Si:H photosensitive chip were characterized. EIS data were fitted to extract equivalent circuit models (ECMs) for both the chip and system. Then analog experiments were performed to verify the ECMs, and the results were consistent with the circuit simulation. Finally, applied alternating current (AC) or direct current (DC) signals to the chip and recorded the electrical signals of the cultured cardiomyocytes on the a-Si:H photosensitive chip. The results demonstrated that applying a high-frequency small AC signal to the chip reduced the background noise of the system by approximately 85.1%, and applying a DC bias increased the amplitude of the detection signal by approximately 142.7%. Consequently, the detection performance of the a-Si:H photosensitive chip for weak bioelectrical signals was significantly enhanced, advancing its applicability in cellular electrophysiological studies. Full article

Unmanned aerial vehicles (UAVs) are increasingly used in urban management and public services, but their potential misuse poses serious risks to public safety. Electrostatic sensors offer a promising approach for UAV detection and interception by capturing their electrostatic signatures during dynamic encounters. However, the sensor output is affected by the coupling between encounter parameters and circuit characteristics, making accurate modeling challenging. This study proposes an analytical modeling method for electrically floating electrostatic sensor signals, calibrated under actual boundary conditions. The model incorporates the effects of encounter angle, miss distance, relative velocity, and equivalent input resistance-capacitance parameters, enabling efficient prediction of sensor signals under multivariable coupling. To validate the model, the electrostatic signatures during dynamic encounters were obtained using the airborne data acquisition and storage system. Results show that the predicted signals correlate well with measured data, with a correlation coefficient above 0.9. The proposed model demonstrates high computational efficiency and supports the design and optimization of electrostatic sensing systems for low-altitude UAV detection and interception. Full article

Accurate parametric modeling of lithium-ion batteries is essential for battery management system (BMS) design in electric vehicles and broader energy storage applications, enabling reliable state estimation and effective thermal control under diverse operating conditions. This study presents a detailed characterization of lithium-ion cells to support advanced BMS in electric vehicles and stationary storage. A second-order equivalent circuit model is developed to capture instantaneous and dynamic voltage behavior, with parameters extracted through Hybrid Pulse Power Characterization over a broad range of temperatures (−10 °C to 45 °C) and state-of-charge levels. The method includes multi-duration pulse testing and separates ohmic and transient responses using two resistor–capacitor branches, with parameters tied to physical processes like charge transfer and diffusion. A weakly coupled electro-thermal model is presented to support real-time BMS applications, enabling accurate voltage, temperature, and heat generation prediction. This study also evaluates open-circuit voltage and direct current internal resistance across pulse durations, leading to power capability maps (“fish charts”) that capture discharge and regenerative performance across SOC and temperature. The analysis highlights performance asymmetries between charging and discharging and confirms model accuracy through curve fitting across test conditions. These contributions enhance model realism, thermal control, and power estimation for real-world lithium-ion battery applications. Full article

Due to their advantages, such as abundant raw material reserves, excellent thermal stability, and superior low-temperature performance, sodium-ion batteries (SIBs) exhibit significant potential for future applications in energy storage and electric vehicles. Therefore, in this study, a commercial pouch-type SIB with sodium iron sulfate cathode material was investigated. Firstly, a second-order RC equivalent circuit model was established through parameter identification using multi-rate hybrid pulse power characterization (M-HPPC) tests at various temperatures. Then, both the specific heat capacity and entropy coefficient of the sodium-ion battery were measured through experiments. Building upon this, an electro-thermal coupling model was developed by incorporating a lumped-parameter thermal model that accounts for the heat generation of the tabs. Finally, the prediction performance of this model was validated through discharge tests under different temperature conditions. The results demonstrate that the proposed electro-thermal coupling model can achieve the simultaneous prediction of both temperature and voltage, providing valuable references for the future development of thermal management systems for SIBs. Full article

Water is essential to human civilization and development, yet its quality is increasingly threatened by climate change, pollution, and resource mismanagement. This work introduces an empirical, non-invasive framework for assessing water potability using electrical impedance spectroscopy (EIS) combined with a novel equivalent circuit model. A customized sensor holder was designed to reduce impedance magnitude and enhance phase sensitivity, improving detection accuracy. Various water samples, including seawater, groundwater, and commercially bottled water, were analyzed. The proposed method achieved a 100% classification accuracy in distinguishing among water types, as validated by extracted circuit parameters and verified by inductively coupled plasma (ICP) measurements. Sensitivity analysis demonstrated the ability to detect compositional changes as small as 10%, highlighting a strong potential for fine discrimination of ionic contents. The extracted parameters, such as resistance, capacitance, and inductance, showed clear correlations with ionic composition, enabling reliable potability classification in accordance with WHO guidelines. The approach is rapid, label-free, and suitable for field applications, offering a promising tool for real-time water quality monitoring and supporting sustainable water resource management. Full article

This study aims to develop a method for analyzing real-world battery degradation in electric vehicles in order to identify the optimal battery management system (BMS) during the early digital phase of vehicle development. Battery management of lithium-ion batteries (LiBs) in electric vehicles is important to ensure a stable output and to counteract degradation and thermal runaway. To design the optimal system, it is most effective to use a 1D (one-dimensional) vehicle system simulation model, which connects each unit model inside the vehicle, due to the system’s complexity. In order to create a long-term degradation simulation in a vehicle system model, it is important to reduce computational load. Therefore, in this paper, we studied a suitable battery degradation calculation for the vehicle system model based on an equivalent circuit model (ECM) and degradation approximation formulas. After implementing these models, we analyzed long-term degradation behavior through the real-world operation of an electric vehicle driver. We first implemented a high-accuracy ECM using transient charge–discharge tests and Bayesian Optimization. Next, we formulated approximation formulas for degradation prediction based on calendar and cycle degradation tests. Finally, we simulated real-world degradation behavior using these models. The simulation results revealed that even for users who frequently use electric vehicles, degradation under storage conditions is the dominant factor in overall degradation. Full article

Pyrochlore Bi_1.8Mn_0.5Ni_0.5Ta₂O_9-Δ (sp.gr. Fd-3m, a = 10.5038(9) Å) was synthesized by the solid-phase reaction method and characterized by vibrational and X-ray spectroscopy. According to scanning electron microscopy, the ceramics are characterized by a porous microstructure formed by randomly oriented oblong grains. The average crystallite size determined by X-ray diffraction is 65 nm. The charge state of transition element cations in the pyrochlore was analyzed by soft X-ray spectroscopy using synchrotron radiation. For mixed pyrochlore, a characteristic shift of Bi4f and Ta4f and Ta5p spectra to the region of lower energies by 0.25 and 0.90 eV is observed compared to the binding energy in Bi₂O₃ and Ta₂O₅ oxides. XPS Mn2p spectrum of pyrochlore has an intermediate energy position compared to the binding energy in MnO and Mn₂O₃, which indicates a mixed charge state of manganese (II, III) cations. Judging by the nature of the Ni2p spectrum of the complex oxide, nickel ions are in the charge state of +(2+ζ). The relative permittivity of the sample in a wide temperature (up to 350 °C) and frequency range (25–10⁶ Hz) does not depend on the frequency and exhibits a constant low value of 25. The minimum value of 4 × 10⁻³ dielectric loss tangent is exhibited by the sample at a frequency of 10⁶ Hz. The activation energy of conductivity is 0.7 eV. The electrical behavior of the sample is modeled by an equivalent circuit containing a Warburg diffusion element. Full article

This study presents a comprehensive evaluation and an equivalent circuit modeling of the skin–electrode impedance characteristics of three types of ultra-thin tattoo electrodes, all based on Parylene C nanofilms but with different active materials: Gold, Silver, and PEDOT:PSS. Their performance was compared to standard disposable Ag/AgCl electrodes. Impedance measurements were carried out on six human subjects under controlled conditions, assessing the frequency response in the range of 20 Hz to 1 kHz. For each subject, the impedance was recorded six times over one hour to investigate the stability and the temporal performance. The collected data were subsequently analyzed to model the electrical properties and interface behavior of each electrode type. The findings demonstrate that the tattoo electrodes offer impedance levels comparable to those of Ag/AgCl electrodes (in the order of tens of kΩ at 20 Hz), while providing additional benefits such as enhanced conformability, improved skin adhesion, and reduced skin irritation during use. Furthermore, the modeling of the skin–electrode interface through a more detailed equivalent circuit than the single time constant model enables a more detailed interface analysis and description, with fitting algorithm R² scores of about 0.999 and 0.979 for the impedance magnitude and impedance phase, respectively. The proposed equivalent circuit offers valuable insights for optimizing electrode design, supporting the potential of Parylene C-based tattoo electrodes as promising alternatives for next-generation wearable bioelectronic applications. Full article

Electrical connectors play a vital role in ensuring reliable signal transmission in high-frequency microsystems. This study explores the impact of microscale scratch-induced surface roughness on the alternating current (AC) contact impedance of RF coaxial connectors. Unlike traditional approaches that assume idealized surface conditions, controlled micro-defects were introduced at the central contact interface to establish a quantitative relationship between surface morphology and signal degradation. An equivalent circuit model was constructed to account for local impedance variations and the cumulative effects of cascaded connector interfaces. The model was validated using S-parameter measurements obtained from vector network analyzer (VNA) testing, showing strong agreement with simulation results. Experimental results reveal that the low-roughness (0.4 μm) contact surfaces lead to degraded signal integrity due to insufficient micro-contact formation. In contrast, scratch-induced moderate roughness (0.8–4.8 μm) improves transmission performance, although signal quality declines as roughness increases within this range. These effects are further amplified in multi-connector configurations due to accumulated impedance mismatches. This work provides new insight into the coupling between microscale surface features and frequency-domain transmission characteristics, offering practical guidance for surface engineering, contact design, and the development of miniaturized, high-reliability radio frequency interconnects for next-generation communication systems. Full article

This study demonstrates that the ripeness of avocado fruits can be analyzed using frequency-dependent electrical conductivity and permittivity through a non-invasive Magnetic Induction Spectroscopy (MIS) method. Utilizing an MIS system for conductivity and permittivity measurements of a large sample set ($N=60$) of avocado fruits across multiple frequencies from 100 kHz to 3 MHz enables clear observation of their dispersion behavior and the evolution of their spectra over ripening time in a completely non-contact manner. For the entire sample batch, the conductivity spectrum exhibits a general upward shift and spectral flattening over ripening time. To further quantify these features, normalized gradient analysis and equivalent circuit modeling were employed, and statistical analysis confirmed the correlations between electrical parameters and ripening stages. The trend characteristics of the normalized gradient parameter $P_y$ provide a basis for defining the three ripening stages within the 22-day period: early pre-ripe stage (0–5 days), ripe stage (5–15 days), and overripe stage (after 15 days). The equivalent circuit model, which is both physically interpretable and fitted to experimental data, revealed that the ripening process of avocado fruits is characterized by a weakening of capacitive structures and an increase in extracellular solution conductivity, suggesting changes in cellular integrity and extracellular composition, respectively. The results also highlight significant inter-sample variability, which is inherent to biological samples. To further investigate individual conductivity variation trends, Gaussian Mixture Model (GMM) clustering and Principal Component Analysis (PCA) was conducted for exploratory sample classification and visualization. Through this approach, the sample set was classified into three categories, each corresponding to distinct conductivity variation patterns. Full article

The high-fidelity lithium-ion battery (LIB) models are crucial for realizing an accurate state estimation in battery management systems (BMSs). Recently, the fractional-order equivalent circuit models (FOMs), as a frequency-domain modeling approach, offer distinct advantages for constructing high-precision battery models in field of electric vehicles. However, the quantitative evaluations and adaptability of these models under different driving cycle datasets are still lacking and challenging. For this reason, comparative evaluations of different FOMs using a novel drive cycle dataset of a battery was carried out in this paper. First, three typical FOMs were initially established and the particle swarm optimization algorithm was then employed to identify model parameters. Complementarily, the efficiency and accuracy of the offline identification for three typical FOMs are also discussed. Subsequently, the terminal voltages of these different FOMs were investigated and evaluated under dynamic operating conditions. Results demonstrate that the FOM-W model exhibits the highest superiority in simulation accuracy, achieving a mean absolute error (MAE) of 9.2 mV and root mean square error (RMSE) of 19.1 mV under Highway Fuel Economy Test conditions. Finally, the accuracy verification of the FOM-W model under two other different dynamic operating conditions has also been thoroughly investigated, and it could still maintain a RMSE and MAE below 21 mV, which indicates its strong adaptability and generalization compared with other FOMs. Conclusions drawn from this paper can further guide the selection of battery models to achieve reliable state estimations of BMS. Full article

This paper presents an algorithm for the implementation of a model that calculates shunt currents in redox flow batteries. The formation patterns of the equivalent electrical circuit that models shunt currents in redox flow batteries are analyzed in such a way that the proposed algorithm is applicable for batteries with any number of cell stacks and any number of cells per stack. Linear algebra is applied to solve the equation system related to the equivalent electric circuit. The solution of such a system of equations is obtained by performing the inverse of a matrix and premultiplying that matrix on both sides of the equation system. This being rather trivial, the real problem lies in automating the generation of the matrices relative to the system of equations. For this reason, it is analyzed how to generate the matrixes in order to facilitate the implementation of their generation. Finally, the most important parts of the implementation of the resolution algorithm are shown. Full article

This study investigates the low-signal behavior of electric motors in automotive applications, emphasizing impedance measurement, evaluation, and the definition of a simplified dummy load. A comprehensive experimental analysis was conducted on two induction motors with different power ratings (300 W and 45 kW), exploring the influence of winding topology, rotor position, and excitation amplitude on the impedance response. A simplified equivalent circuit model (ECM), derived solely from terminal impedance measurements, was developed and validated to construct a practical dummy load. This model facilitates realistic simulations without requiring detailed internal motor specifications. Experimental results confirm that the dummy load accurately replicates the measured impedance characteristics in the low-to-mid frequency range, demonstrating its effectiveness for electromagnetic interference (EMI) prediction and system-level simulations in automotive electric drive system. Full article

This study presents the successful fabrication of lead zirconate titanate (PZT) thin films on silicon (Si) substrates using a hybrid deposition method combining spin-coating and RF sputtering techniques. Initially, a PZT layer was deposited through four successive spin-coating cycles, followed by an additional layer formed via RF sputtering. The resulting multilayer structure was annealed at ${700 }^{°}$C for 2 h to improve crystallinity. Comprehensive material characterization was conducted using XRD, SEM, cross-sectional SEM, EDX, and UV–VIS absorbance spectroscopy. The analyses confirmed the formation of a well-crystallized perovskite phase, a uniform surface morphology, and an optical band gap of approximately 3.55 eV, supporting its suitability for sensing applications. Building upon these findings, a multilayer PZT-based touch sensor was fabricated and electrically characterized. Low-frequency I–V measurements demonstrated consistent and repeatable polarization behavior under cyclic loading conditions. In addition, $\left|Z\right|$–f measurements were performed to assess the sensor’s dynamic electrical behavior. Although expected dielectric responses were observed, the absence of distinct anti-resonance peaks suggested non-idealities linked to ${\mathrm{Ag}}^{+}$ ion diffusion from the electrode layers. To account for these effects, the classical Butterworth–Van Dyke (BVD) equivalent circuit model was extended with additional inductive and resistive components representing parasitic pathways. This modified model provided excellent agreement with the measured impedance and phase data, offering deeper insight into the interplay between material degradation and electrical performance. Overall, the developed sensor structure exhibits strong potential for use in piezoelectric sensing applications, particularly for tactile and pressure-based interfaces. Full article

The dielectric relaxation behavior of polymeric materials is critical to their performance in electronic, insulating, and energy storage applications. This study presents an electrical fractional model (EFM) based on fractional calculus and the complex electric modulus ($M^{*}\mathit{=}{M}^{\prime }\mathit{+}i{M}^{″}$) formalism to simultaneously describe two key relaxation phenomena: $\alpha$-relaxation and interfacial polarization (Maxwell–Wagner–Sillars effect). The model incorporates fractional elements (cap-resistors) into a modified Debye equivalent circuit to capture polymer dynamics and energy dissipation. Fractional differential equations are derived, with fractional orders taking values between 0 and 1; the frequency and temperature responses are analyzed using Fourier transform. Two temperature-dependent behaviors are considered: the Matsuoka model, applied to $\alpha$-relaxation near the glass transition, and an Arrhenius-type equation, used to describe interfacial polarization associated with thermally activated charge transport. The proposed model is validated using literature data for amorphous polymers, polyetherimide (PEI), polyvinyl chloride (PVC), and polyvinyl butyral (PVB), successfully fitting dielectric spectra and extracting meaningful physical parameters. The results demonstrate that the EFM is a robust and versatile tool for modeling complex dielectric relaxation in polymeric systems, offering improved interpretability over classical integer-order models. This approach enhances understanding of coupled relaxation mechanisms and may support the design of advanced polymer-based materials with tailored dielectric properties. Full article