Stable Output Voltage Research Articles

In-situ synthesis AgO/AgNPs composite as binder-free cathode for high-performance aqueous AgO-Al batteries

Aqueous AgO-Al batteries are promising systems due to their ultrahigh specific capacity, energy density, and stable output voltage. However, they still suffer from the low utilization and sluggish kinetics of the cathode. In this study, the binder-free AgO/AgNPs composites were synthesized in-situ using a simple electrodeposition method. Due to the excellent conductivity and rich mesoporous structure of AgO/AgNPs materials, the electron and ion transfer kinetics were enhanced, thereby improving the charge storage performance of the electrode. As expected, the AgO-Al battery with the optimized AgO/AgNPs composite cathode demonstrated excellent rate performance, achieving a high discharge capacity of 325.1 mAh g−1, and a stable operating voltage platform of 1.55 V at the current density of 1000 mA cm−2. The maximum energy and power density were 687 Wh kg−1 and 6.2 kW kg−1, respectively. This work presents an effective strategy for designing high-performance AgO electrode materials for AgO-Al batteries.

Electricity production and nutrient recovery from waste activated sludge via microbial fuel cell and subsequent struvite crystallization: Effect of low temperature thermo-alkaline pretreatment

Microbial fuel cell (MFC) and subsequent struvite crystallization are available low-carbon environmental- friendly techniques for resource utilization of waste activated sludge (WAS). In this study, low temperature thermo-alkaline pretreatment (LTTAP) was innovatively proposed for enhancing MFC electricity generation and subsequent struvite crystallization from WAS. The results indicated that LTTAP at 75 °C and pH 10 not only substantially shortened the start-up time of MFC to 3–4 days, but also significantly increased maximum power density to 5.38 W/m3. Moreover, thermo-alkaline pretreated WAS effectively exhibited stable and high output voltage over long period, compared to unpretreated WAS. Furthermore, pretreated WAS can provide an effective pH buffering function for MFC operation. In addition, about 90 % of phosphate in the pretreated WAS supernatant was recovered by struvite crystallization. The findings herein provided a new route for enhancing electricity production and nutrient recovery from WAS, which can realize the full-scale applicationof WAS resource utilization.

Implementation Joule Thief Buck-Boost Converter in A Neodymium Wind Power Plant

Wind power generation is gaining popularity as an environmentally friendly renewable energy source. However, the output voltage of a wind generator usually varies according to the wind speed, requiring a power converter to produce a stable DC voltage. The author of this research aims to implement a Joule Thief Buck-Boost Converter on a neodymium wind power generation system. Joule Thief is a DC-DC converter that has the ability to convert a low input voltage into a higher output voltage, and can maintain a relatively stable output voltage despite changes in the input voltage. In this study, a Joule Thief buck-boost converter is used to regulate the output DC voltage of the neodymium wind generator to remain stable despite the changing wind speed. System testing is done by measuring the output voltage of the neodymium wind power plant. The test results show that the Joule Thief Buck-Boost Converter can maintain the output DC voltage at a stable value of 14V at input voltages above 3V, so the implementation of this converter in neodymium wind power plants is proven effective in producing a stable DC voltage. This research is expected to contribute to the development of a more efficient and reliable wind power generation system.

An integrated textile of electrical signal sensing with visual indicators and energy supply for perspiration management

Recent advances in wearable electronics have enabled the development of sweat sensors providing valuable information for healthcare monitoring. However, the limitations of sweat sensors are excessive dependence on external detection systems, the impossible to real-time visual signal transmission, and inadequate perspiration management. Herein, a single- and double-layer interwoven fabric (SDIF) is designed to achieve indicators of color visualization with an output of electrical signal and energy supply. After absorption of electrolyte, the SDIF can be rapidly activated, connected with the concentration, infiltrated volume, and environmental parameters, and the variational color of SDIF can provide visual indicators. The one tissue cycle of SDIF with three-weft intervals maintains a stable output voltage of ≈1.0 V, conducted by twisting, folding, dynamic bending, and reusing. Moreover, serial tissue cycles can be woven into large fabrics by connecting in series and parallel configurations for energy supply. The developed SDIF with an interweaving structural design using industrial-producible weaving technology provides the functionality of sweat adsorption and transportation, monitoring by recognition of color, and electrical signals to improve perspiration management.

Switch Capacitor–Based High Step‐Up Three‐Port DC–DC Converter for Fuel Cell/Battery Integration

ABSTRACTAddressing issues of low input voltage in new energy generation systems such as fuel cells, a high step‐up three‐port DC–DC converter for fuel cell/battery hybrid power supply system is proposed. The proposed converter is evolved from Boost three‐port converter, and switch capacitor structure and diode capacitor voltage doubling unit are employed to achieve high voltage gain and low voltage stress. The three ports are connected to fuel cell, battery and load respectively, among which the flow of energy is realized. The steady state performance of this converter in various operating states and design of parameter are presented. Primary competitive advantages compared to similar converters include high voltage gain, continuous input current and its feature of common ground. Moreover, control strategy and compensators under three operating modes are designed to achieve stable output voltage and battery protection. Finally, a 100 W experimental prototype with 15 V input voltage and 24 V battery voltage is established to verify the stable and dynamic performance of the proposed converter.

Design of a PID Controller for Microbial Fuel Cells Using Improved Particle Swarm Optimization

The microbial fuel cell (MFC) is a renewable energy technology that utilizes the oxidative decomposition processes of anaerobic microorganisms to convert the chemical energy in organic matter, such as wastewater, sediments, or other biomass, into electrical power. This technology is not only applicable to wastewater treatment but can also be used for resource recovery from various organic wastes. The MFC usually requires an external controller that allows it to operate under controlled conditions to obtain a stable output voltage. Therefore, the application of a PID controller to the MFC is proposed in this paper. The design phase for this controller involves the identification of three parameters. Although the particle swarm optimization (PSO) algorithm is an advanced optimization algorithm based on swarm intelligence, it suffers from issues such as unreasonable population initialization and slow convergence speed. Therefore, this paper proposes an improved particle swarm algorithm based on the Golden Sine Strategy (GSCPSO). Using Circle chaotic mapping to make the distribution of the initial population more uniform, and then using the Golden Sine Strategy to improve the position update formula, not only improves the convergence speed of the population but also enhances convergence precision. The GSCPSO algorithm is applied to execute the described design process. The results of the simulation show that the designed control method exhibits smaller steady-state error, overshoot, and chattering compared with sliding-mode control (SMC), backstepping control, fuzzy SMC (FSMC), PSO-PID, and CPSO-PID.

A Study on Dual-Gate Dielectric Face Tunnel Field-Effect Transistor for Ternary Inverter.

In this article, we propose a dual-gate dielectric face tunnel field-effect transistor (DGDFTFET) that can exhibit three different output voltage states. Meanwhile, according to the requirements of the ternary operation in the ternary inverter, four related indicators representing the performance of the DGDFTFET are proposed, and we explain the impact of these indicators on the inverter and confirm that better indicators can be obtained by choosing appropriate design parameters for the device. Then, the ternary inverter implemented with this device can exhibit voltage transfer characteristics (VTCs) with three stable output voltage levels and bigger static noise margins (SNMs). In addition, by comparing the indicators of the DGDFTFET and a face tunnel field-effect transistor (FTFET), as well as the SNM of inverters, it is demonstrated that the performance of the DGDFTFET far surpasses the FTFET.

Effects of Co3O4 modified with MoS2 on microbial fuel cells performance

In this study, Co3O4@MoS2 is prepared as anodic catalytic material for microbial fuel cells (MFCs). As the mass fraction of MoS2 is 20%, the best performance of Co3O4@MoS2 composite catalytic material is achieved, and the addition of MoS2 enhances both the electrical conductivity and catalytic performance of the composite catalyst. Through the structural characterization of Co3O4@MoS2 composite catalytic material, nanorod-like Co3O4 and lamellar MoS2 interweaved and stacked each other, and the agglomeration of Co3O4 is weakened. Among the four groups of single-chamber MFCs constructed, the Co3O4@MoS2-MFC shows the best power production performance with a maximum stable output voltage of to 539 mV and a maximum power density of up to 2221 mW/m2. Additionally, the ammonia nitrogen removal rate of the MFCs loaded with catalysts is enhanced by about 10% compared with the blank carbon cloth MFC. Overall, the findings suggest that Co3O4@MoS2 composite catalysts can significantly improve the performance of MFCs, making them more effective for both energy production and wastewater treatment.

β-enhanced humidity robust high performance triboelectric nanogenerator for energy harvesting and sensors

Limited output current and harsh environmental conditions are big challenges to harvesting electrical energy from triboelectric nanogenerators (TENG) in sensing applications. One contributing factor to this issue is matching the density of state between two layers of TENG for maximum charge transfer. To ensure a stable output performance, a superhydrophobic interface between the TENG's two layers has been achieved by applying a novel fluorescence enhanced hexamethyldisiloxane (HMDSO) dielectric barrier discharge (DBD) plasma. The plasma coating not only improve the hydrophobicity but also the interface contacts between the two layers of TENG and therefore a maximum charge transfer and ultra-high current density are obtained. The plasma treatment increases the surface roughness and introduces functional groups such as amino (-NH2), hydroxyl (-OH), and siloxane (-Si-O-Si) on the PMMA film, which increases the electron affinity difference between the two layers, increases humidity resistance. The modified TENG generates a maximum stable output voltage of 1400 V and a maximum current of 125 µA with a power density of 55 W/m2, which is significantly higher than those reported in previous studies. Therefore, the TENG has been used as a self-powered droplet detector with an ultra-fast response time of 1.8 ms and has the potential to be used as a self-powered humidity sensor.

Whole-process analysis and implementation of a self-powered wireless health monitoring system for railway bridges: Theory, simulation and experiment

In this work, a self-powered wireless health monitoring system (SP-WHMS) combined with the Internet-of-Things (IoT) is proposed and implemented for a long-term and long-distance health monitoring of railway bridges. This system frees the wireless sensor nodes (WSNs) from their dependence on chemical batteries by using the piezoelectric energy harvester (PEH) to harvest the vibration energy from bridges to power the WSNs. The whole-process of the SP-WHMS including energy conversion, energy storage, energy management and application is analyzed at the first time through theory, simulation and experiment. For the energy conversion, a reported PEH model with high energy conversion efficiency (called D-M PEH) is refabricated, which can achieve a maximum average output power of 0.9 W under unit harmonic acceleration excitation. For the energy storage, a high-precision iteration analysis procedure (IAP) is proposed to predict the charging process of the strong-coupled PEHs and the charging process under non-harmonic excitations. The comparison results show that the IAP’s prediction deviates less than 3% from the experiment result and even less than 1% from the simulation result. For the energy management, an AP64500 chip with two adjustable input voltage thresholds and a stable output voltage ensures the normal operation of the SP-WHMS and makes the SP-WHMS suitable for different types of WSNs. For the application, the synergies between energy conversion, storage and management are considered, and the effectiveness of the SP-WHMS used on railway bridges is tested through an activation experiment. This work provides a technical guidance and framework for the implementation of the self-powered wireless monitoring on railway bridges.

High‐Performance Azo Cathodes Enabled by N‐Heteroatomic Substitution for Zinc Batteries with a Self‐Charging Capability

AbstractRedox‐active azo compounds are emerging as promising cathode materials due to their multi‐electron redox capacity and fast redox response. However, their practical application is often limited by low output voltage and poor thermal stability. Herein, we use a heteroatomic substitution strategy to develop 4,4′‐azopyridine. This modification results in a 350 mV increase in reduction potential compared to traditional azobenzene, increasing the energy density at the material level from 187 to 291 Wh kg−1. The introduced heteroatoms not only raise the melting point of azo compounds from 68 °C to 112 °C by forming an intermolecular hydrogen‐bond network but also improves electrode kinetics by reducing energy band gaps. Moreover, 4,4′‐azopyridine forms metal‐ligand complexes with Zn2+ ions, which further self‐assemble into a robust superstructure, acting as a molecular conductor to facilitate charge transfer. Consequently, the batteries display a good rate performance (192 mAh g−1 at 20 C) and an ultra‐long lifespan of 60,000 cycles. Notably, we disclose that the depleted batteries spontaneously self‐charge when exposed to air, marking a significant advancement in the development of self‐powered aqueous systems.

High-Performance Azo Cathodes Enabled by N-Heteroatomic Substitution for Zinc Batteries with a Self-Charging Capability.

Redox-active azo compounds are emerging as promising cathode materials due to their multi-electron redox capacity and fast redox response. However, their practical application is often limited by low output voltage and poor thermal stability. Herein, we use a heteroatomic substitution strategy to develop 4,4'-azopyridine. This modification results in a 350 mV increase in reduction potential compared to traditional azobenzene, increasing the energy density at the material level from 187 to 291 Wh kg-1. The introduced heteroatoms not only raise the melting point of azo compounds from 68 °C to 112 °C by forming an intermolecular hydrogen-bond network but also improves electrode kinetics by reducing energy band gaps. Moreover, 4,4'-azopyridine forms metal-ligand complexes with Zn2+ ions, which further self-assemble into a robust superstructure, acting as a molecular conductor to facilitate charge transfer. Consequently, the batteries display a good rate performance (192 mAh g-1 at 20 C) and an ultra-long lifespan of 60,000 cycles. Notably, we disclose that the depleted batteries spontaneously self-charge when exposed to air, marking a significant advancement in the development of self-powered aqueous systems.

Efficient voltage regulation: An RW-ARO optimized cascaded controller approach

This work introduces novel advancements in automatic voltage regulator (AVR) control, addressing key challenges and delivering innovative contributions. The primary motivation lies in enhancing AVR performance to ensure stable and reliable voltage output. A crucial innovation in this work is the introduction of the random walk aided artificial rabbits optimizer (RW-ARO). This novel optimization strategy incorporates a random walk approach, enhancing the efficiency of AVR control schemes. The proposed cascaded RPIDD2-PI controller, fine-tuned using the RW-ARO, stands out as a pioneering approach in the AVR domain. It demonstrates superior stability, faster response times, enhanced robustness, and improved efficiency compared to existing methods. Comparative analyses with established controller approaches reaffirm the exceptional performance of the proposed method. The new approach results in shorter rise times, quicker settling times, and minimal overshoot, highlighting its effectiveness and speed in achieving desired system responses. Moreover, the novel approach attains higher phase and gain margins, showcasing its superior performance in the frequency domain. The disturbance rejection and harmonic analysis are performed in order to demonstrate the efficacy of the proposed approach for potential real-world applications. The latter analyses further cement the superior capability of the proposed approach for the automatic voltage regulation.

Deep Learning-Based State-of-Health Estimation of Proton-Exchange Membrane Fuel Cells under Dynamic Operation Conditions.

Proton-exchange membrane fuel cells (PEMFCs) play a crucial role in the transition to sustainable energy systems. Accurately estimating the state of health (SOH) of PEMFCs under dynamic operating conditions is essential for ensuring their reliability and longevity. This study designed dynamic operating conditions for fuel cells and conducted durability tests using both crack-free fuel cells and fuel cells with uniform cracks. Utilizing deep learning methods, we estimated the SOH of PEMFCs under dynamic operating conditions and investigated the performance of long short-term memory networks (LSTM), gated recurrent units (GRU), temporal convolutional networks (TCN), and transformer models for SOH estimation tasks. We also explored the impact of different sampling intervals and training set proportions on the predictive performance of these models. The results indicated that shorter sampling intervals and higher training set proportions significantly improve prediction accuracy. The study also highlighted the challenges posed by the presence of cracks. Cracks cause more frequent and intense voltage fluctuations, making it more difficult for the models to accurately capture the dynamic behavior of PEMFCs, thereby increasing prediction errors. However, under crack-free conditions, due to more stable voltage output, all models showed improved predictive performance. Finally, this study underscores the effectiveness of deep learning models in estimating the SOH of PEMFCs and provides insights into optimizing sampling and training strategies to enhance prediction accuracy. The findings make a significant contribution to the development of more reliable and efficient PEMFC systems for sustainable energy applications.

Design of low‐stress ultrahigh‐gain dc–dc converter with coupled inductor

AbstractThe dc–dc converter plays a vital role in renewable energy power generation systems. To enhance the boost range and supply stable output voltage for the power grid, This paper propose an improved low‐stress ultrahigh‐gain dc–dc converter. First, a voltage multiplier cell is designed stemming from a three‐winding coupled inductor and a switched capacitor (SC), which can obtain ultrahigh voltage gain. In the improved voltage multiplier cell, the number of semiconductor devices is reduced, resulting in a decrease in capacitor voltage stress. Moreover, a passive clamp circuit uses the new SC, which can suppress oscillation peak voltage and absorb the leakage energy of the coupled winding. Furthermore, we deduce the operating mode of the proposed converter . Compared with other advanced topologies, the proposed topology outperforms boosting capacity, component stress, and efficiency. To stabilize the output voltage, the converter is closed‐loop controlled. Finally, experiments on the 180 W prototype have demonstrated the reliability and effectiveness of the proposed topology.

Eco-friendly triboelectric nanogenerator for self-powering stacked In2O3 nanosheets/PPy nanoparticles-based NO2 gas sensor

As atmospheric issues and energy crises worsen, developing environmentally friendly, low-cost, high-performance self-powered gas sensing systems for gas pollutant monitoring is crucial for the development of ecological civilization. In this work, an eco-friendly self-powered nitrogen dioxide (NO2) sensor (EFNS) system based on an eco-friendly triboelectric nanogenerator (EF-TENG) is reported. The system comprises a power supply unit (EF-TENG) and a sensing unit (In2O3/PPy sensor), connected through a signal stabilization circuit. EF-TENG utilizes eco-friendly and biodegradable gelatin and PLA/PBAT as the friction layer. By introducing leaf structures on the gelatin surface using a template method, the output voltage and current of EF-TENG were increased by 1.44 and 1.67 times, respectively. The peak power density and root mean square power density of EF-TENG reached 1386 mW m−2 and 185.35 mW m−2, respectively. Additionally, EF-TENG exhibited excellent long-term stability, maintaining a stable output voltage (∼24 V) after rectification and voltage stabilization treatment under conditions of 15–55°C and 40–80 % RH. Additionally, an In2O3/PPy heterostructure sensor was prepared, and the EFNS system was constructed through impedance matching effects, revealing the NO2 response mechanism of the In2O3/PPy heterostructure. This achieved a wide detection range and highly sensitive (Vg/Va = 355 %@30 ppm) detection of NO2. This work provides insights into eco-friendly self-powered gas sensors and sensing mechanisms, offering ideas for the development of environmental monitoring sensors and clean energy harvesting devices.

Insight into electricity production performance from dried waste activated sludge in dual chamber microbial fuel cells: Influencing factors, neural network modelling and microbial community analysis

Directly deriving electrical energy from waste activated sludge (WAS) by using microbial fuel cell (MFC) is one of the most promising alternatives to resource utilization of WAS. However, obtaining high MFC performance is still a great challenge for the full-scale implementation of MFC. Therefore, this study aimed to quantify and model the effect of different operating parameters on the performance of MFC fed with dried WAS as anode substrate. The results indicated that MFC exhibited a fast start-up time of 3 days at the inoculated anaerobic sludge: dry WAS mass ratio of 1:5. Moreover, the output voltage and power density of MFC were highly dependent of anolyte pH and temperature, WAS concentration, which was well simulated and predicted by the BPANN model. It was revealed that MFC fed with dry WAS exhibited good performance at 55ºC, pH 9.0 and WAS concentration of 16 g/L, while the stable output voltage and power density were 0.705 V and 5.248 W/m3, respectively. The anolyte temperature significantly affected microbial communities of the anode biofilm. At the phylum level, Synergistota and Proteobacteria dominated the anode biofilm at 35ºC, while Firmicutes was absolutely enriched in the anode biofilm at 55ºC. At the genus level, the predominant Advenella is detected in the anode biofilm at 35ºC, whereas the preponderant MBA03 is identified in the anode biofilm at 35ºC. The findings herein may provide a route for efficiently driving power energy from WAS, which can facilitate the fulfillment of full-scale MFC for the resource utilization of WAS.

Effect of rotation on achieving constant voltage in three-phase self-excited induction generator for small scale wind turbines application

Three-phase Self-Excited Induction Generators (SEIGs) are commonly employed for electricity generation in remote or isolated areas. SEIGs are preferred in such regions due to their ability to create a magnetic field by adding a capacitor to one of their terminals. Nevertheless, a significant challenge in utilizing SEIGs is maintaining a consistent output voltage in the presence of load fluctuations. This study aims to investigate the impact of generator rotation on the SEIG's output voltage and determine the optimal rotation speed required for achieving a stable output voltage. Ensuring stable voltage regulation is crucial to guarantee the proper functioning of all loads connected to the SEIG. Furthermore, operating the SEIG in parallel with other generators is advantageous. The methodology employed in this study involves varying the load supplied by the SEIG at different capacitor values. Unwanted voltage variations occur due to load fluctuations within a generating system or SEIG. Adjustments to the generator's rotation speed are made to uphold a uniform voltage level. The variables considered in this study include the generator's rotation speed, capacitor size, and load fluctuations. Simulation results demonstrate that the SEIG's output voltage is affected by the generator's rotation speed, and maintaining a consistent voltage necessitates appropriate adjustments to capacitor values and generator speed. This research enhances understanding of SEIG characteristics and offers guidance on effective settings for maintaining a stable output voltage at various generator rotation speeds. Future research can focus on practically implementing these findings to enhance the performance of SEIGs in real-world applications

Enhanced Adaptive Dynamic Surface Sliding Mode Control for Optimal Performance of Grid-Connected Photovoltaic Systems

This study presents an enhanced, adaptive, and dynamic surface sliding mode control (SMC), a cutting-edge method for improving grid-connected photovoltaic (PV) system performance. The suggested control approach uses dynamic SMC and adaptive approaches to enhance the robustness and efficiency of a system. Proportional–integral (PI) and SMC, two control systems for maximum power point tracking (MPPT) in PV systems, are compared in this paper. This study finds that the SMC system is a more effective and efficient MPPT approach for PV systems compared to the conventional PI control system. The SMC system’s unique feature is the capacity to stabilize grid voltage and attain a modulation index of less than one. An important component of power electronic system control is the index, which acts as a parameter representing the relationship between the output signal’s amplitude and the reference signal’s amplitude. The SMC method demonstrates improved robustness, efficiency, and stability, especially in dynamic operating settings with load and solar radiation changes. Compared to the PI control, the SMC exhibits a noteworthy 75% reduction in voltage fluctuations and an improvement in the power output of 5% to 10%. Regarding output power optimization, voltage stability, and accurate current tracking, the SMC system performs better than the PI control system. Furthermore, the SMC technique maintains a modulation index below one and guarantees grid voltage stability, both of which are essential for the efficiency and stability of power electrical systems.

Off-Grid Electric Vehicle Charging Station with Integrated Local Server OCPP Protocol as a Management System

Abstract Electric vehicles are widely regarded as pivotal in driving the sustainability of transportation networks forward, thanks to their capacity to diminish carbon emissions, enhance air quality, and bolster the robustness of electricity grids. The accessibility of charging infrastructure and the subjective norms that endorse electric mobility actively shape the electric vehicles acceptance. In this study, Our main goal is to provide off-grid electric vehicle charging infrastructures and the data communication protocols that connect to servers. We analyze the specifications of the OCPP (Open Charge Point Protocol) with an emphasis on its applicabillity for electric charging stations for vehicles. Our research concludes that off-grid electric vehicle charging systems can be effectively applied to small electric vehicles such as electric motorcycles, scooters, and bicycles. The OCPP data communication protocol can also support interactions between small electric vehicle charging stations and central server management systems (CSMS). Furthermore, we tested the electric vehicle charging process for a duration of two hours, and the charging station consistently produced stable voltage, current, and power output, matching the inverter outputs and fulfilling the specifications required by electric vehicle charging adapters. Analysis of throughput data indicates a positive correlation between the number of operational ports at a charging station and the volume of data processed by the server. However, beyond a certain threshold a decline in data transactions was observed, attributable to data loss.