Calculation Of Voltage Research Articles

Dichalcogenides as Emerging Electrocatalysts for Efficient Ammonia Synthesis: A Focus on Mechanisms and Theoretical Potentials

AbstractDeveloping sustainable technologies for ammonia production through electrochemical reactions offers a promising alternative by leveraging renewable energy sources to produce ammonia under ambient conditions. These methods include nitrogen reduction reaction (NRR), nitric oxide reduction reaction (NORR), nitrite reduction reaction (NO2RR), and nitrate reduction reaction (NO3RR). Optimizing energy efficiency (EE) in electrochemical ammonia synthesis has become increasingly crucial as commercialization approaches. Herein, this work offers a comprehensive study of system EE improvements through the theoretical voltage calculations based on pH and the expansion of bifunctional catalysts like transition metal dichalcogenides (TMDs), which can efficiently catalyze the oxygen evolution reaction (OER) and ammonia synthesis. The review summarizes the pH‐dependent redox potential and Pourbaix diagrams for NRR, NO2RR, and NO3RR, offering insights into the potential‐pH regions where nitrogen and nitrogen oxides are reduced to NH3. Incorporating theoretical voltage calculations into system design enables researchers to minimize energy losses better and improve overall performance. Finally, the review wraps up by exploring the roles of TMD catalysts in different reaction mechanisms and identifying potential areas for improvement. The broader impact of this review lies in its potential to transform ammonia production into alignment with global efforts to reduce greenhouse gas emissions.

A novel approach using iterative g-function and chaotic cooperation search for accurate voltage calculation of double and triple diode solar cell models

The solar cells can be accurately represented via double and triple-diode models (DDM and TDM, respectively). In this paper, a novel iterative procedure based on applying the g-function is proposed for double and triple solar cell voltage calculation for the first time. The proposed iterative procedure is performed without any approximations, while its application overcomes numerical limitations when applying literature-accepted approaches based on the Lambert W function. Also, one notable advantage of the proposed procedure is its effectiveness with arbitrary starting point values. Second, in this paper, an original equation for calculating solar cells’ root mean square error (RMSE) voltage (RMSEU) in the DDM and TDM, which aids in parameter estimation, is proposed. Third, the paper introduces a new metaheuristic algorithm called the Chaotic Cooperation Search Algorithm (ChCSA) for estimating solar cell parameters. The proposed approach (iterative procedure for voltage-current representation as well as a novel algorithm) is tested on two well-known solar cells in the literature and on measured current-voltage characteristics for different weather conditions. Applying the proposed algorithm and the novel iterative procedure for DDM and TDM voltage calculations demonstrated the accuracy and efficiency of the proposed approach for solar cell parameter estimation. In order to achieve the appropriate accuracy, it was shown that only a few iterations of the proposed iterative procedure are needed for the majority of measurement points in both observed cells. Furthermore, the application of the proposed algorithm outperforms existing algorithms in solar cell parameter estimation. Moreover, with the well-known Photowatt-PWP 201 solar module, the application of the proposed algorithm enables the estimation of the parameters of the solar cell so that the RMSEU value is reduced by about 50 % compared to the results obtained for the parameters determined by numerous approaches from the literature. Therefore, the presented research offers a novel and original double and triple solar cell modeling perspective.

Numerical study of breakdown voltage calculation and discharge characteristics of millimeter-level short air gap with a single water droplet

Abstract Water droplets in the short air gap significantly affect the breakdown voltage. Currently, there is a lack of computational studies on the breakdown voltage and discharge process of short air gaps containing water droplets. In this paper, we establish a plasma dynamics-based model for the discharge in a millimeter-scale short air gap containing a single water droplet under ambient pressure and propose a breakdown voltage calculation method. We discuss typical discharge processes, calculate breakdown voltages for different gap lengths, validate the model through discharge phenomena and breakdown voltage, and analyze the impact of droplet parameters on discharge characteristics. The results show that negative streamer discharge in the cathode-side gap and positive streamer discharge in the anode-side gap occur sequentially, consistent with reported experimental results, with the positive streamer discharge being the primary process leading to gap breakdown. The average error rate between the calculated breakdown voltages for 4–8 mm gaps and reported experimental results is 4.85%, indicating good agreement. The observed streamer branching phenomenon may explain the difference between calculated and experimental breakdown voltages for the 10 mm gap. Under the influence of surface charges, low-conductivity droplets cause the discharge channel to propagate along the droplet surface. In contrast, high-conductivity droplets confine the discharge channel within the two gap sections. Increasing droplet diameter reduces breakdown voltage, with a critical value where the reduction becomes significant. Increased droplet deformation degree raises the breakdown voltage. This effect is related to the deviation of the positive streamer from the axial development and the reverse streamer generated on the droplet’s surface in different cases. The closer the droplet is to the electrode, the higher the breakdown voltage. The discharge is facilitated by the streamers generated on the droplet’s lower surface when it is close to the anode.

TPDH-Graphene as a New Anodic Material for Lithium Ion Battery: DFT-Based Investigations.

The potential of tetra-penta-deca-hexagonal graphene (TPDH-gr), a recently proposed 2D carbon allotrope as an anodic material in lithium ion batteries (LIBs), was investigated through density functional theory calculations. The results indicate that Li-atom adsorption is moderate (around 0.70 eV), allowing for easy desorption. Moreover, energy barriers (0.08-0.20 eV), diffusion coefficient (>6 × 10-6 cm2/s), and open circuit voltage (0.29 V) calculations show rapid Li atom diffusion on the TPDH-gr surface, stable intercalation of lithium atoms, and good performance during the charge and discharge cycles of the LIB. These findings, combined with the intrinsic metallic nature of TPDH-gr, indicate that this new 2D carbon allotrope is a promising candidate for use as an anodic LIB material.

An improved soft actor-critic-based energy management strategy of heavy-duty hybrid electric vehicles with dual-engine system

While deep reinforcement learning (DRL) based energy management strategies (EMSs) have shown potential for optimizing energy utilization in recent years, challenges such as convergence difficulties and suboptimal control still persist. In this research, a novel DRL algorithm, i.e. an improved soft actor-critic (ISAC) algorithm is applied to the EMS of a heavy-duty hybrid electric vehicles (HDHEV) with dual auxiliary power units (APU) in which the priority experience replay (PER), emphasizing recent experience (ERE) and Muchausen reinforcement learning (MRL) methods are adopted to improve the convergence performance and the HDHEV fuel economy. Simultaneously, a bus voltage calculation model suitable for dual-APUs is proposed and validated using real-world data to ensure the precision of the HDHEV model. Results indicate that the proposed EMS reduces HDHEV fuel consumption by 4.59 % and 2.50 % compared to deep deterministic policy gradient (DDPG) and twin delayed deep deterministic policy gradient (TD3)-based EMSs respectively, narrowing the gap to dynamic programming-based EMS to 7.94 %. The proposed EMS exhibits superior training performance, with a 91.28 % increase in convergence speed compared to other DRL-based EMSs. Furthermore, the ablation experiments also validate the effectiveness of each method in the proposed EMS for the SAC algorithm, further demonstrating its superiority.

Understanding How Porous Transport Layer Features Affect Proton Exchange Membrane Electrolyzer Performance

PEM Water electrolysis has emerged as a promising technology for the production of green hydrogen. A key component of PEM electrolyzer is the porous transport layer (PTL). The porous transport layer has numerous important roles in water electrolysis. In addition to enabling electrical conduction and water and gas transport, the PTL is necessary for maintaining excellent contact with the cell components. Cell performance is anticipated to be affected by PTL properties such as structure, composition, and thickness.This study delves into the critical contribution of porous transport layer properties to mass transport resistance, activation losses, catalyst layer resistance, and ohmic losses. I will present our experimental framework to deconvolute the impact of PTL properties such as thickness, porosity, and microporous layer on various overpotentials. Voltage loss breakdown analysis was conducted to determine kinetic, ohmic, mass transport, and catalyst layer losses. Theoretical calculations of thermodynamic voltage typically rely on standard reaction potentials adjusted for reactant and product concentrations, operating temperature, and pressure via Nernst corrections. Ohmic voltage, which accounts for contact resistances, bulk resistances, and ohmic losses from the membrane, was determined using high-frequency impedance spectroscopy measurements. To calculate losses from OER kinetics, a Tafel fit is subsequently implemented on the HFR-free voltage. Typically, this process tends to result in residual voltage at elevated current densities, including losses arising from mass transport of water and oxygen, resistance within the catalyst layer, and impacts stemming from ionic impurities. Ionic contamination is omitted from our analysis as a result of the short duration of the experiment.Our detailed analysis reveals that the properties of PTL can have a substantial impact on the performance of the water electrolyzer, which is crucial for enhancing the performance and durability of PEMWE. This study presents a novel framework for forecasting the performance of diverse PTL materials, which may be effectively used to drive the development and optimization of PTL for water electrolyzers. Figure 1

Important insights into steady-state calculations of voltages and currents in complex sheath bonding configurations of single-core cables

Ensuring effective sheath bonding holds paramount importance within underground single-core cable systems, as a misjudged selection can precipitate cable failures or jeopardize human safety. The foundation of a sound bonding design rests upon a meticulous examination of induced voltages and currents on the cable sheaths. To address this, guidelines and numerical techniques have been introduced, applicable to both handheld calculators and sophisticated software tools. However, their precision hinges on specific features and solving techniques, aspects that remain unclarified in current literature. This paper delves into a comprehensive exploration of sheath current and voltage calculations at steady-state in single-core cable systems. A rigorous benchmarking exercise is undertaken, comparing bonding-design simulation results derived from various computation methods. Moreover, the study scrutinizes the impact of several parameters, shedding light on crucial insights. Building upon this, the paper proposes modelling recommendations for the design and assessment of sheath bonding configurations in complex power cable installations.

Simulation of voltage characteristics of vapor-gas shell during electrolyte-plasma treatment

Electrolytic plasma processing (EPT) is a method of surface treatment of materials based on the use of plasma and an electrolytic solution. This abstract discusses the principle of action, main applications and potential benefits of EPТ. The EPТ technique involves immersing the object being treated in an electrolytic solution, after which an electric current is applied, causing decomposition of the solution and the formation of a plasma cloud at the surface of the material being processed. Exposure to plasma and chemically active components of the solution makes it possible to modify the surface of the material, improving its properties, such as adhesion, strength and corrosion resistance. EPТ is widely used in a variety of industries, including metalworking, electronics, medical equipment and food processing. The advantages of the method include high efficiency, the ability to process complex shapes and materials, as well as environmental safety due to the absence of the use of chemically aggressive substances. Electrolytic plasma processing is a promising direction in the field of surface modification of materials with a wide range of potential applications. In this paper, theoretical studies of vapor-gas shell formation in the near-surface region of structural steels in the cathodic heating mode of electrolyte-plasma treatment were considered. The technology of electrolyte-plasma hardening, providing the required mechanical properties of products, which are often subjected to wear, temperature and force effects, was investigated. Based on the results of theoretical studies, mathematical calculations of voltage, current density, and dependence graphs were made to obtain a model of vapor-gas shell formation in the process of cathodic heating. Modeling of calculations of vapor-gas shell formation in the process of cathodic heating was carried out with the help of Maple program.

First-principles study of lithium behavior in the ABA-stacking trilayer graphene with defects

To investigate the effect of defects on the Li embedding in graphene, we have studied the embedding and migration of Li in graphene with single-vacancy (SV), double-vacancy (DV), and Stone-Wales (SW) defects using the first-principles calculations. The results show that Li atom prefers to embed in regions with defect, and the presence of defect enhances the Li embedding in graphene. From the perspective of solution energy, Li embedded in the defect region of SV is the most stable, followed by the defect region of DV and SW. Migration results reveal that defects lead to an increase in the energy barrier for Li atom migration between layers and that Li is likely to be trapped in the defect region during migration. Open-circuit voltage and theoretical capacity calculations demonstrate that the lithium capacity of the ABA-stacking trilayer perfect graphene is 248 mAh/g. The lithium capacity diminishes to 165 mAh/g when a SW defect is present in the ABA-stacking trilayer graphene. In contrast, the lithium capacity increases to 270 mAh/g and 292 mAh/g when SV or DV defect is present in the ABA-stacking trilayer graphene, respectively. It is sufficient to show that graphene with low-density SW defect is unsuitable for application as electrode materials. Conversely, the low density of SV and DV defects can increase the lithium capacity of the ABA-stacking trilayer graphene at the same time, which will also lead to lithium deposition to some extent.

Calculation algorithm for electromagnetic wave processes in multi-wire intersystem ETL

The nature of the transient process and the magnitude of the overvoltages are determined by a large number of factors in the HV/EHV AC transmission networks. The paper presents the study of mathematical modelling of electromagnetic wave processes in long-distance electric transmission line (ETL). The mathematical model is based on electromagnetic processes occurring on distributed parameter lines that are characterized by specific derivatives of the system of differential equations. The application of a spline-interpolation technique enables the calculation of currents and voltages at the nodes of the scheme, which obtains the unknown coordinates of the overhead line mode at the beginning of the ETL to solve the transmission line equation. The following results are derived from computer simulations of transients during switching on. With a simulation model, the importance of intelligent control of shunt reactor (SR) and ungrounded reactor (UR) was demonstrated and considered for a 500 kV power networks.

Breakdown Voltage Estimation in Transformer Oils with Low-Cost Humidity Sensor

The relative humidity and temperature of the oil used for insulation purposes in transformers directly affect the breakdown voltage of the oil and accordingly the life of the transformer. Continuous monitoring of the moisture content and breakdown voltage of the transformer oil provides the basis for predictive maintenance practices. This study aims to develop a sensor to continuously monitor the moisture content of the insulating oil and to calculate the breakdown voltage approximately. In this context, firstly, measurements were taken with an industrial oil monitoring sensor which calculates the breakdown voltage in transformer oils with high accuracy and was verified with laboratory measurements. At the same time, EE364 by E+E™ and SHT10 by Sensirion™ also used for temperature and humidity measurements. By comparing the measured data with each other, a relationship was formulated between the humidity and temperature values and the breakdown voltage. As a result, an approximate breakdown voltage calculation method that can be used considering the characteristic parameters of transformer oil has been introduced. Thus, a cost-effective function has been developed that can be widely used for transformer monitoring systems.

The Influence of the Design of Antenna and Chip Coupling Circuits on the Performance of Textronic RFID UHF Transponders

The objectives of this study were to design, investigate, and compare different designs of coupling circuits for textronic RFID transponders, particularly focusing on magnetic coupling between an antenna and a chip. The configuration of the inductively coupled antenna module and the microelectronic module housing the chip can be varied in several ways. This article explores various geometries of coupling circuits and assesses the effects of altering their dimensions on mutual inductance, chip voltage, and the transponder’s read range. The investigation comprised an analytical description of inductive coupling, calculations of mutual inductance and chip voltage based on simulation models of transponders, and laboratory measurements of the read range for selected configurations. The results obtained from this study demonstrate that various designs of textile transponders are capable of achieving satisfactory read ranges, with some configurations extending beyond 10 m. This significant range provides clothing designers with the flexibility to select transponder designs that best meet their specific aesthetic and functional requirements.

High Voltage Calculations for a 380 kV Superconducting Fault Current Limiter

High Voltage Calculations for a 380 kV Superconducting Fault Current Limiter

Machine learning-based method for predicting C–V-T characteristics and electrical parameters of GaAs/AlGaAs multi-quantum wells Schottky diodes

In this work, two models of artificial neural networks are developed to predict the electrical parameters and capacitance-voltage characteristics of GaAs/AlGaAs multi-quantum wells Schottky diodes at different temperatures. Capacitance-Voltage-Temperature (C–V-T) characteristics for voltages and temperatures in the ranges (-4 V–0 V) and (20 K–400 K), respectively, were used to assess the effectiveness of the proposed approach. The first model (Model 1) is used to evaluate how well the neural network predicts the C–V-T characteristics. The second simulation, known as Model 2, was constructed to simultaneously overcome the problems of determining the electrical parameters and predicting C–V-T characteristics. Model 2 allows the calculation of the built-in voltage, effective density, and capacitance. Three-fold cross-validation and mean square error are used to assess the effectiveness of the developed models. The results clearly demonstrate the high prediction accuracy of the electrical parameters and C–V characteristics at all temperatures. After training, Model 1 Mean Square Error performance is 1.5033×10−6 at 1450 epochs, whereas Model 2 MSE is 4.9951×10−6 at 642 epochs. According to the error distribution frequency histogram, about 95 % of errors for Model 1 and Model 2 lie between [0.00535 and 0.005608] and [0.00328 and 0.00333], respectively. The R-values that correspond to the training and validation datasets for both models are close to one (0.9999). Parameters determination results have been compared against those obtained using ant lion optimizer based method. It was found that the results obtained from the neural networks models strongly agree with the experimental data.

Model-Free Predictive Current Control of SPMSM Based on Enhanced Extended State Observer

Conventional model-free predictive current control (MFPCC) using an extended state observer (ESO) based on ultra-local model significantly decreased the sensitivity to partial motor parameters. However, the performance and stability of ESO will be degraded in the face of amplified high-frequency (HF) perturbation caused by inductance parameter mismatch. To solve the above problem, an enhanced ESO-based MFPCC method is proposed in this article. On the basis of constructing the discrete equation of ESO, an accurate and fast calculation of inductance parameter is proposed, which is real-time convergence to the actual value by deadbeat control principle, and fed back to the lumped disturbance and current observation calculation. It effectively eliminates the effects of HF perturbation on ESO. Simultaneously, the inductance and compensated lumped disturbance obtained from ESO are provided to the MFPCC command voltage calculation module, further improving the parameter robustness of MFPCC. The stability of the proposed ESO is ensured by the design of observer gain. Experiments are carried out on 1kW surfaced permanent magnet synchronous machines (SPMSM) test bench. Compared with the conventional ESO-based MFPCC method, the proposed method is superior in dynamic response, steady-state performance, and parameter robustness.

Rational designing of phenothiazine dioxide based hole transporting materials for efficient perovskite solar cells

In this study, we design five novel non-fullerene end capped acceptor based efficient hole transporting materials (HTMs) from phenothiazine dioxide-based core. MPW1PW91 functional with a 6-31G basis set was employed for all DFT calculations and simulation analysis. By substituting acceptor groups in PDO2, numbers of parameters like band gaps, the frontier molecular orbitals (FMOs), higher absorption parameters, and electronic properties like ionization potential, electron affinity, binding energy, and light harvesting efficiency (LHE) were well tuned. In addition, significant variations in other geometrical parameters such as dipole moment, and reorganizational energy parameters were also noticed for the derived molecules compared to the reference molecule (R). Device performance was analyzed by performing calculations of open circuit voltage (VOC) and fill factor (FF). Consequently, all the designed derivatives demonstrated an improved VOC of 0.84 V for an optimized designed structure. In comparison, it was limited to a VOC of 0.57 V for the reference (R) PDO2, displaying an increment in efficiency which is essential to use these molecules as highly efficient HTMs for perovskite solar cell devices in the future.

Dynamic microgrid formation for resilient distribution systems considering large-scale deployment of mobile energy resources

Microgrids (MGs) are promising solutions to improve power distribution system (PDS) resilience against natural disasters. However, the existing MG formation approaches based on the linearized Distflow (LinDistflow) model always demand MG roots and their corresponding topologies. This can result in an increased number of variables and constraints in the optimization problem, and deteriorate their computational performance. To this end, an adaptive LinDistflow model is proposed based on the single commodity flow model in graph theory in this paper. Specifically, we show that active and reactive powers can be represented as commodities, which are sent from one node to each of its adjacent nodes in the graph. Then, the power flow and nodal voltage calculation based on the commodity flow only requires adjacent node information of the original topology rather than various MG topologies caused by the dynamic deployment of mobile energy resources (MERs). Furthermore, by incorporating the adaptive LinDistflow model as constraints, a dynamic MG formation approach is proposed for resilient load restoration considering large-scale MER deployment. The problem is formulated as a mixed-integer nonlinear programming problem (MINLP). A linearization technique is proposed based on the propositional logic constraints. It employs the propositional logic that partitions the solution space into two separated regions. Accordingly, the region that the solution lies in can be selected linearly. The effectiveness of the proposed approach is demonstrated based on the IEEE 37-Node, 123-Node and 8500-Node Test Feeders.

Dynamic Voltage and Frequency Scaling as a Method for Reducing Energy Consumption in Ultra-Low-Power Embedded Systems

Dynamic voltage and frequency scaling (DVFS) is a technique used to optimize energy consumption in ultra-low-power embedded systems. To ensure sufficient computational capacity, the system must scale up its performance settings. The objective is to conserve energy in times of reduced computational demand and/or when battery power is used. Fast Fourier Transform (FFT), Cyclic Redundancy Check 32 (CRC32), Secure Hash Algorithm 256 (SHA256), and Message-Digest Algorithm 5 (MD5) are focused functions that demand computational power to achieve energy-efficient performance. Selected operations are analyzed from the energy consumption perspective. In this manner, the energy required to perform a specific function is observed, thereby mitigating the influence of the instruction set or system architecture. For stable operating voltage scaling, an exponential model for voltage calculation is presented. Statistical significance tests are conducted to validate and support the findings. Results show that the proposed optimization technique reduces energy consumption for ultra-low-power applications from 27.74% to up to 47.74%.

Voltage prediction of vanadium redox flow batteries from first principles*

Global energy demand has been increasing for decades, which has created a necessity for large scale energy storage solutions for renewable energy sources. We studied the voltage of vanadium redox flow batteries (VRFBs) with density functional theory (DFT) and a newly developed technique using ab initio molecular dynamics (AIMD). DFT was used to create cluster models to calculate the voltage of VRFBs. However, DFT is not suited for capturing the dynamics and interactions in a liquid electrolyte, leading to the need for AIMD, which is capable of accurately modeling such things. The molarities and densities of all systems were carefully considered to match experimental conditions. With the use of AIMD, we calculated a voltage of 1.23 V, which compares well with the experimental value of 1.26 V. The techniques developed using AIMD for voltage calculations will be useful for the investigation of potential future battery technologies or as a screening process for additives to make improvements to currently available batteries.

Analysis, Calculation and Reduction of Shaft Voltage in Induction Generators

This paper presents analysis of shaft voltage in different configurations of a Doubly Fed Induction Generator (DFIG) and an Induction Generator (IG) with a back-to-back inverter in wind turbine applications. Detailed high frequency model of the proposed systems have been developed based on existing capacitive couplings in IG & DFIG structures and common mode voltage sources. In this research work, several arrangements of DFIG based wind energy conversion systems are investigated on shaft voltage calculation and its mitigation techniques. Placements of an LC line filter in different locations and its effects on shaft voltage elimination are studied with mathematical analysis and simulations.