Search Results (770)

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

Determination of single-valued BH curve and power loss curve of electric steels is an important parameter in the design of electrical machines and transformers. This paper proposes a correction procedure for the measurement of anhysteretic BH curve and power losses, based on the finite element model (FEM) and SST apparatus. A 3D finite element model (FEM) of the SST (Single Sheet Tester) was developed with respect to the IEC 60404-3 standard. The measurement results obtained with a standardized SST apparatus are fed to its FEM and used to iteratively correct initial BH and power loss curves, obtained using magnetic equivalent circuits theory. The proposed iterative correction procedure is based on the steepest descent algorithm, while the stopping criteria were based on the difference between simulated and measured global variables (power loss, induced voltage, and primary current). After correction, root mean squared errors were decreased from 1.85 A/m to 42.88 × 10⁻³ A/m for the BH curve, and from 44.5 × 10⁻⁴ W/kg to 7.28 × 10⁻⁴ W/kg for the power loss curve. Full article

Noise reduction is essential in analyzing electrochemical impedance spectroscopy (EIS) data for accurate parameter identification of models of electrochemical sources and interfaces. EIS is widely used to study the behavior of electrochemical systems as it provides information about the processes occurring at electrode surfaces. However, measurement noise can severely compromise the accuracy of parameter identification and the interpretation of EIS data. This paper presents methods for parameter identification of Randles (also known as R-RC or 2R-1C) equivalent electrical circuits and noise reduction in EIS data using recursive filtering. EIS data obtained at the estimated characteristic frequency is processed with three equations in the closed form for the parameter estimation of series resistance, charge transfer resistance, and double-layer capacitance. The proposed recursive filter enhances estimation accuracy in the presence of random noise. Filtering is embedded in the estimation procedure, while the optimal value of the recursive filter weighting factor is self-tuned based on the proposed search method. The distinguished feature is that the proposed method can process EIS data and perform estimation with filtering without any input from the user. Synthetic datasets and experimentally obtained impedance data of lithium-ion batteries were successfully processed using PC-based and microcontroller-based systems. Full article

The temperature variations of interconnected coaxial connectors in RF circuits are strongly influenced by the contact surface characteristics and the ferromagnetic properties of the electroplated materials. In this study, specially structured N-DIN connectors with either magnetic or non-magnetic plating were designed. A dedicated high-frequency, high-power RF experimental platform was set up to monitor and measure the temperature and power of the connectors. Finite element analysis (FEA) was employed to simulate the current density and temperature distribution across the samples. Furthermore, an equivalent circuit model of the central conductor was established by integrating electrical contact theory with the magnetic hysteresis effect. Based on the voltage–temperature (V–T) relation and the derived magnetic field–magnetoresistance (H–M) relation, a predictive model for the temperature rise of the central conductor was formulated. Experimental results demonstrated good agreement with simulation predictions, validating the proposed model and highlighting the critical role of plating material properties in high-power RF connectors’ thermal effect. Full article

In this paper, the concept of symmetry is utilized to optimize the structural parameters and output characteristics of the generator design—that is, the construction and solution of the equivalent magnetic circuit method for the hybrid excitation generator are symmetrical. To address the issues of high excitation loss and low power density in purely electrically excited generators, as well as the difficulty in adjusting the magnetic field in purely permanent magnet generators, a new topology for a built-in permanent magnet and salient-pole electromagnetic hybrid excitation generator is proposed. Firstly, an equivalent magnetic circuit model of the generator is established. Secondly, expressions are derived to describe the relationships between the dimensions of the salient-pole rotor and the permanent magnets and the generator’s no-load induced electromotive force, cogging torque, and air gap flux density. These expressions are then used to analyze the structural parameters that influence the generator’s performance. Thirdly, optimization targets are selected through sensitivity analysis, with the no-load induced electromotive force, cogging torque, and air gap flux density serving as the optimization objectives. A multi-objective genetic algorithm is employed to optimize these parameters and determine the optimal structural matching parameters for the generator. As a result, the optimized no-load induced electromotive force increased from 18.96 V to 20.14 V, representing a 6.22% improvement; the cogging torque decreased from 177.08 mN·m to 90.52 mN·m, a 48.88% reduction; the air gap flux density increased from 0.789 T to 0.829 T, a 5.07% improvement; and the air gap flux density waveform distortion rate decreased from 6.22% to 2.38%, a 39.3% reduction. Finally, a prototype is fabricated and experimentally tested, validating the accuracy of the simulation analysis, the feasibility of the optimization method, and the rationality of the generator design. Therefore, the proposed topology and optimization method can effectively enhance the output performance of the generator, providing a valuable theoretical reference for the design of hybrid excitation generators for vehicles. Full article

The surface of AM60 magnesium alloy was modified with Al-nanocoating ~65.62 nm, using DC magnetron sputtering to enhance its resistance to degradation under aggressive marine ambience. The sputtered Al film showed adhesion to the α-Mg matrix, covering the dispersed particles of the β-Mg₁₇Al₁₂ secondary phase. The aluminum nanofilm was composed of (111) and (200) crystal planes of metallic aluminum (Al⁰) and Al₂O₃ (Al³⁺). After 30 days of immersion in a simulated marine environment (SME, pH 7.8), the Al-AM60 maintained a lower alkaline value (pH~8.13) of SME than that of uncoated AM60, attributed to α-Mg electrochemical oxidation to Al₂O₃ and its posterior dissolution, consuming OH⁻ ions. Consequently, the concentration of the released Mg²⁺ ions from the Al-AM60 surface was reduced ~2.3 times (~15 mg L⁻¹). The Rp (polarization resistance), as inversely proportional to the corrosion current, was extracted from the EIS impedance data fitted to an equivalent electrical circuit. After 30 days in SME solution, the Rp value of the Al-AM60 modified surface was ~3.5 times higher than that of AM60 (~15.46 kΩ cm²), confirming that the sputtered aluminum nano-deposit layer can hinder the corrosion process. These reported findings indicated that sputtered Al nano-coatings can mitigate the surface degradation of Mg-Al alloys in saline aggressive marine environments. Full article

This study explores the significant effects of charge–discharge cycling on lithium iron phosphate (LiFePO₄)-based electrochemical cells, with a particular focus on the Sinopoly SP-LFP040AHA cell. As lithium-ion batteries undergo repeated charging and discharging cycles, their internal characteristics evolve, influencing performance, efficiency, and longevity. Understanding these changes is crucial for optimizing battery management strategies and ensuring reliable operation across various applications. To analyze these effects, the study utilizes equivalent electrical circuits (EEC) to model the internal behavior of the battery. The individual components of the EEC—such as its resistive, capacitive, and inductive elements—are examined through 3D waveforms, offering a comprehensive visualization of how each parameter responds to cycling. One of the key contributions of this research is the development and implementation of an EEC identification approach that enables a systematic assessment of battery parameter evolution. This technique provides insights into the general trends and variations in electrical behavior based on the state of charge (SoC) of the cell. By analyzing data across a wide range of SoC values—from 0% (fully discharged) to 100% (fully charged)—and tracking changes over 100 charge–discharge cycles, the study highlights the progressive alterations in battery performance. The findings of this investigation offer valuable implications for battery health monitoring, predictive maintenance, and the refinement of state estimation models. Full article

In the context of new power systems, the safe and accurate sensing of voltage data is crucial for the secure and stable operation of power grids. Given that existing voltage measurement devices cannot meet the development requirements for wide-area deployment and distributed monitoring, this paper designs a non-intrusive voltage measurement device based on MEMS (micro-electromechanical system) electric field sensors, which are characterized by their small size, low power consumption, ease of installation and strong anti-interference ability. Firstly, the paper introduces the voltage measurement principle and analyzes the equivalent circuit based on this analysis; secondly, the key structural design of the measurement device is completed and the prototype of the device is developed; finally, the accuracy and anti-jamming tests of the measurement device are conducted by establishing an experimental platform, followed by field applications. Experimental results demonstrate that the voltage measurement device has high measurement accuracy, and the maximum error is only 1.215%. Additionally, the device has a good shielding capability against the coupled electric field of surrounding interference conductors, with a maximum error increase of 1.313%. In a 10 kV overhead line voltage test, the device can accurately obtain the actual voltage. The voltage measuring device developed in this paper can provide data support for the condition assessment of overhead lines and effective monitoring means for the safe and stable operation of the power system. Full article

Steel fibers (SFs) can form stable conductive networks in coal gangue-cemented composites (CGCCs), endowing CGCCs with excellent mechanical, electrical and self-sensing properties. Meanwhile, electrochemical impedance spectroscopy (EIS) provides a potential approach to evaluate the damage situation of SF-reinforced CGCC. In this paper, EIS responses of CGCCs with different SF content and damage levels were determined. An equivalent circuit was then explored, and the effect of the SF content and damage levels on its parameters was investigated. It was observed that CGCC with 0.8% SFs yielded the best result in terms of mechanical and self-sensing ability. In addition, damage such as microcracks primarily affects the conductive pathways induced by pores rather than those induced by SFs. More importantly, as a non-destructive method, the EIS technique is practical and promising for monitoring damage conditions of SF-reinforced CGCC in underground engineering. Full article

LiFePO₄ batteries are widely used in hybrid electric tractors due to their high energy density, stable working voltage, low self-discharge rate, long cycle life, absence of memory effect, environmental friendliness, and flexible sizing. Accurate State of Charge (SOC) estimation is crucial for Battery Management Systems (BMSs). This study utilizes a LiFePO₄ battery dataset from the University of Maryland to improve SOC estimation accuracy. The forgetting factor recursive least squares method was employed for parameter identification, and a temperature-dependent second-order RC equivalent circuit model was developed in MATLAB R2024a/Simulink. The proposed SAO-LSTM model demonstrated superior SOC estimation performance compared to traditional ampere-hour integration, achieving a 98.23% error reduction. Evaluation results showed 0.39% and 0.31% decreases in root mean square error and mean absolute error, respectively, confirming the model’s robustness and high estimation accuracy for LiFePO₄ batteries in hybrid electric tractors. Full article