Search Results (188)

Designing an effective electrical model for charged water bodies is of great significance in reducing the risk of electric shock in water and enhancing the safety and reliability of electrical equipment. Aiming to resolve the problems faced in using existing charged water body modeling methods, a practical circuit model of a charged water body is developed. The basic units of the model are simply constructed using fractional-order resistance–capacitance (RC) parallel circuits. The state variables of the model can be obtained by solving the circuit equations. In addition, a practical method for obtaining the circuit model parameters is also developed. This enables the estimation of the characteristics of charged water bodies under different conditions through model simulation. The effectiveness of the proposed method is verified by comparing the estimated voltage and leakage current of the model with the actual measured values. The comparison results show that the estimated value of the model is close to the actual characteristics of the charged water body. Full article

Based on a fractional-order equivalent circuit model, this paper proposes a multi-timescale collaborative State of Energy (SOE) and State of Health (SOH) estimation method (FOASTFREKF-EKF) for lithium batteries to mitigate the influence of model inaccuracies and battery aging on SOE estimation. Initially, a fractional-order equivalent circuit model is built, and its parameters are identified offline using the Starfish Optimization Algorithm (SFOA) to establish a high-fidelity battery model. An H∞ filter is then integrated to improve the algorithm’s resilience to external disturbances. Furthermore, an adaptive noise covariance adjustment mechanism is employed to reduce the effect of operational noise, and a time-varying attenuation factor is introduced to improve the algorithm’s tracking and convergence capabilities during abrupt system-state changes. A joint estimator is subsequently constructed, which uses an Extended Kalman Filter (EKF) for the online determination of battery parameters and SOH assessment. This approach minimizes the effect of varying model parameters on SOE accuracy while reducing computational load through multi-timescale methods. Experimental validation under diverse operating conditions shows that the proposed algorithm achieves root mean square errors (RMSE) of less than 0.21% for SOE and 0.31% for SOH. These findings demonstrate that the method provides high accuracy and reliability under complex operating conditions. Full article

This paper addresses the issue of rotor swings in a high-power synchronous generator during stable operation with a stiff power grid. The analysis of electromechanical swings was conducted using a circuit model incorporating fractional-order derivatives. Assuming that variations in the load angle under small disturbances from a stable equilibrium are minor, a linearized differential equation describing the electrodynamic state of the synchronous machine was derived. Based on this linearized equation of motion and the identified parameters of the equivalent circuit, calculations were performed for a 200 MW turbogenerator. The results indicate that the electromechanical swings are characterized by a constant pulsation and a low damping factor. Calculations were also carried out using a lumped-parameter equivalent circuit model. Based on the obtained results, it can be stated that the fractional-order model provides a more accurate fit of the frequency characteristics compared with the classical model with the same number of rotor equivalent circuits. The relative approximation errors for the fractional-order model are, for the d-axis (one rotor equivalent circuit), relative magnitude error δ_m = 1.53% and relative phase error δ_φ = 6.32%, and for the q-axis (two rotor equivalent circuits), δ_m = 3.2% and δ_φ = 8.3%. To achieve comparable approximation accuracy for the classical model, the rotor electrical circuit must be replaced with two equivalent circuits in the d-axis and four equivalent circuits in the q-axis, yielding relative errors of δ_m = 2.85% and δ_φ = 6.51% for the d-axis, and δ_m = 1.86% and δ_φ = 5.49% for the q-axis. Full article

To overcome the limitations of traditional integer-order models, which fail to accurately capture the dynamic behavior of lithium-ion batteries, and to improve the insufficient accuracy of state of charge (SOC) and state of health (SOH) collaborative estimation, this study proposes a cooperative estimation framework based on a fractional-order model. First, a fractional-order second-order RC equivalent circuit model is established, and the whale optimization algorithm is applied for offline parameter identification to improve model accuracy. Second, a strong tracking strategy is introduced into the improved unscented Kalman filter to address the convergence speed issue under inaccurate initial SOC conditions. Meanwhile, the extended Kalman filter is employed for SOH estimation and online parameter identification. Furthermore, a multi-time-scale collaborative estimation algorithm is proposed to enhance overall estimation accuracy. Experimental results under three dynamic operating conditions driving cycles demonstrate that the proposed method effectively solves the SOC/SOH collaborative estimation problem, achieving a mean SOC estimation error of 0.45% and maintaining the SOH estimation error within 0.25%. Full article

Fractional-order calculus (FOC) has gained significant attention in electric vehicle (EV) energy storage and management systems, as it provides enhanced modeling and analysis capabilities compared to traditional integer-order approaches. This review presents a comprehensive survey of recent advancements in the application of FOC to EV energy storage systems, including lithium-ion batteries (LIBs), supercapacitors (SCs), and fuel cells (FCs), as well as their integration within energy management systems (EMS). The review focuses on developments in electrochemical, equivalent circuit, and data-driven models formulated in the fractional-order domain, which improve the representation of nonlinear, memory-dependent, and multi-scale dynamics of energy storage devices. It also discusses the benefits and limitations of current FOC-based models, identifies open challenges such as computational feasibility and parameter identification, and outlines future research directions. Overall, the findings indicate that FOC offers a robust framework with significant potential to advance next-generation EV energy storage and management systems. Full article

Developing efficient, clean, and sustainable lignocellulose pretreatment technologies is essential for second-generation biofuel production. In this study, we attempted to use downstream-separated binary acetone-water, n-butanol-water, and ethanol-water solutions as the initial liquor for upstream organosolv pulping, in order to achieve the efficient and economic closed-circuit clean fractionation of the lignocelluloses for biological acetone–butanol–ethanol (ABE) production. Parameters, including concentration and temperature of the organosolv pulping, were optimized systematically. Results indicated that the 50 wt% ethanol and 30 wt% acetone aqueous solutions and pulping at 200 °C for 1 h exhibited better corn stover fractionation performances with higher fermentable sugar production. The total monosaccharide recovery (including glucose and xylose) was 50.92% and 50.89%, respectively, in subsequent enzymatic saccharification. While pulping corn stover using n-butanol solution as initial liquor showed higher delignification 86.16% (50 wt% of n-butanol and 200 °C for 1 h), the hydrolysate obtained by the organosolv pulps always exhibited good fermentability. A maximized 15.0 g/L of ABE with 0.36 g/g of yield was obtained in Ethanol-200 °C-50% group, corresponding to 112 g of ABE production from 1 kg of raw corn stover. As expected, the lignin specimens fractionated by closed-circuit organosolv pulping exhibited narrow molecule weight distribution, high purity, and high preservation of active groups, which supports further valorization. This novel strategy tightly bridges the upstream and downstream processes of second-generation ABE production, providing a new route for ‘energy-matter intensive’ and environmentally friendly lignocelluloses biorefineries. Full article

Supercapacitors (SCs) are emerging as a dependable energy storage technology in industrial applications, valued for their high power output and exceptional longevity. In high-power applications, SCs are not used as single cells but are configured in a series–parallel combination to form a bank. Accurate state-of-charge estimation is essential for effective energy management in power systems employing SC banks. This work presents a novel state estimation approach for SC banks. First, a dynamic model of an SC bank is derived by applying a fractional-order Thévenin equivalent circuit to a single-cell SC. Then, an observability analysis is conducted, which reveals that the system is empirically weakly observable. This is the fundamental challenge for state-of-the-art observers to robustly perform state estimation. To address this challenge, an implicitly regularized observer is developed based on generalized parameter estimation techniques. The performance of the proposed observer is benchmarked against a fractional-order extended Kalman filter using experimental data. The results demonstrate that incorporating a regularization law into the observer dynamics effectively mitigates observability limitations, offering a robust solution for the SC bank state estimation. Full article

This paper presents a novel four-dimensional autonomous conservative model characterized by an infinite set of equilibrium points and an unusual algebraic structure in which all eigenvalues of the Jacobian matrix are zero. The linearization of the proposed model implies that classical stability analysis is inadequate, as only the center manifolds are obtained. Consequently, the stability of the system is investigated through both analytical and numerical methods using Lyapunov functions and numerical simulations. The proposed model exhibits rich dynamics, including hyperchaotic behavior, which is characterized using the Lyapunov exponents, bifurcation diagrams, sensitivity analysis, attractor projections, and Poincaré map. Moreover, in this paper, we explore the model with fractional-order derivatives, demonstrating that the fractional dynamics fundamentally change the geometrical structure of the attractors and significantly change the system stability. The Grünwald–Letnikov formulation is used for modeling, while numerical integration is performed using the Caputo operator to capture the memory effects inherent in fractional models. Finally, an analog electronic circuit realization is provided to experimentally validate the theoretical and numerical findings. Full article

This paper presents three novel sufficient and necessary conditions for the admissibility of singular fractional-order systems (FOSs), a stabilization criterion, and a solution algorithm. The strict linear matrix inequality (LMI) stability criterion for integer-order systems is generalized to singular FOSs by using column-full rank matrices. This admissibility criterion does not involve complex variables and is different from all previous results, filling a gap in this area. Based on the LMIs in the generalized condition, the improved criterion utilizes a variable substitution technique to reduce the number of matrix variables to be solved from one pair to one, reflecting the admissibility more essentially. This improved result simplifies the programming process compared to the traditional approach that requires two matrix variables. To complete the state feedback controller design, the system matrices in the generalized admissibility criterion are decoupled, but bilinear constraints still occur in the stabilization criterion. For this case, where a feasible solution cannot be found using the MATLAB LMI toolbox, a branch-and-bound algorithm (BBA) is designed to solve it. Finally, the validity of these criteria and the BBA is verified by three examples, including a real circuit model. Full article

Next-generation smart sensing devices necessitate on-chip integration of power-efficient reference circuits. The latters are required to provide other circuit blocks with highly reliable bias signals, even in the presence of temperature shifts and supply voltage disturbances, while draining a small fraction of the overall power budget. In particular, it is especially challenging to design current references with enhanced robustness and efficiency; hence, thorough exploration of novel architectures and design approaches is needed for this type of circuits. In this work, we propose a novel CMOS-only current reference, achieving temperature compensation by exploiting geometry dependences of the threshold voltage (specifically, the reverse short-channel effect and the narrow-channel effect). This allows reaching first-order temperature compensation within a single current reference core. Implemented in 0.18 µm CMOS, a version of the proposed current reference designed to deliver 141 nA (with 377 nW of total power consumption) achieved an average temperature coefficient equal to 194 ppm/°C (from −20 °C to 80 °C) and an average line sensitivity of −0.017%/V across post-layout statistical Monte Carlo simulations. Based on such findings, the newly proposed design methodology stands out as a noteworthy solution to design robust current references for power-constrained mixed-signal systems-on-chip. 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

Fractional-order four-wing (FO 4-wing) systems are of significant importance due to their complex dynamics and wide-ranging applications in secure communications, encryption, and nonlinear circuit design, making their control and stabilization a critical area of study. In this research, a novel model-free finite-time flexible sliding mode control (FTF-SMC) strategy is developed for the stabilization of a particular category of hyperchaotic FO 4-wing systems, which are subject to unknown uncertainties and input saturation constraints. The proposed approach leverages fractional-order Lyapunov stability theory to design a flexible sliding mode controller capable of effectively addressing the chaotic dynamics of FO 4-wing systems and ensuring finite-time convergence. Initially, a dynamic sliding surface is formulated to accommodate system variations. Following this, a robust model-free control law is designed to counteract uncertainties and input saturation effects. The finite-time stability of both the sliding surface and the control scheme is rigorously proven. The control strategy eliminates the need for explicit system models by exploiting the norm-bounded characteristics of chaotic system states. To optimize the parameters of the model-free FTF-SMC, a deep reinforcement learning framework based on the adaptive dynamic programming (ADP) algorithm is employed. The ADP agent utilizes two neural networks (NNs)—action NN and critic NN—aiming to obtain the optimal policy by maximizing a predefined reward function. This ensures that the sliding motion satisfies the reachability condition within a finite time frame. The effectiveness of the proposed methodology is validated through comprehensive simulations, numerical case studies, and comparative analyses. 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

Imaging applications involving outdoor scenes and fast motion require sensing and processing of high-dynamic-range images at video rates. In turn, image signal processing pipelines that serve low-dynamic-range displays require tone mapping operators (TMOs). For high-speed and low-power applications with low-cost field-programmable gate arrays (FPGAs), global TMOs that employ contrast-limited histogram equalization prove ideal. To develop such TMOs, this work proposes a MATLAB–Simulink–Vivado design flow. A realized design capable of megapixel video rates using milliwatts of power requires only a fraction of the resources available in the lowest-cost Artix-7 device from Xilinx (now Advanced Micro Devices). Unlike histogram-based TMO approaches for nonlinear sensors in the literature, this work exploits Simulink modeling to reduce the total required FPGA memory by orders of magnitude with minimal impact on video output. After refactoring an approach from the literature that incorporates two subsystems (Base Histograms and Tone Mapping) to one incorporating four subsystems (Scene Histogram, Perceived Histogram, Tone Function, and Global Mapping), memory is exponentially reduced by introducing a fifth subsystem (Interpolation). As a crucial stepping stone between MATLAB algorithm abstraction and Vivado circuit realization, the Simulink modeling facilitated a bit-true design flow. Full article

The present work proposes a novel fractional-order multifunction filter topology in current-mode (CM), which is designed based on the Modified Current Feedback Operational Amplifier (MCFOA). The proposed design simultaneously generates fractional-order low-pass (FO-LPF), high-pass (FO-HPF), and band-pass (FO-BPF) outputs while utilizing an optimized set of essential active and passive elements, thereby ensuring simplicity, cost efficiency, and compatibility with integrated circuits (ICs). The fractional-order feature allows precise control over the transition slope between the passband and the stopband, enhancing design flexibility. PSpice simulations validated the filter’s theoretical performance, confirming a 1 kHz cut-off frequency, making it suitable for VLF applications such as military communication and submarine navigation. Monte Carlo analyses demonstrate robustness against parameter variations, while a low THD, a wide dynamic range, and low power consumption highlight its efficiency for high-precision, low-power applications. This work offers a practical and adaptable approach to fractional-order circuit design, with significant potential in communication, control, and biomedical systems. Full article