Electrical Design Research Articles

Land and sea transport options for the installation of green artificial reefs (GARs) in shallow waters: a Galician case study.

The aim of the present paper is to propose a new methodology for the production and installation of green artificial reefs (GARs) in shallow waters, with special attention to the transport stages. The process includes both onshore (manufacturing, road transport and unload at port) and offshore (load at port, sea transport, positioning, and deployment tasks) stages. Two different types of truck were analysed for the road transport. Furthermore, three different options were considered for sea transport: a workboat powered by liquefied natural gas, a barge using diesel (0.1% sulphur) as fuel, and an electric specific design barge. A simulation tool called AGARDO (Automatic Green Artificial Reef Deploy Optimisation) was developed for such a purpose. An estuary located in Galicia (North-West of Spain), where 180 GAR units must be installed, has been considered as case study. AGARDO was used to obtain results concerning process total time, equivalent CO2 emissions and costs for different scenarios. Consequently, the use of the proposed methodology allows the decision-maker to select the best option in terms of costs, emissions and time. AGARDO can be easily adapted to other case studies, with different onshore and offshore options.

A Piezoelectric Balance System With Mass Automatic Recognition Ability Based on Resonant Frequency Shift

Mass measurement in the microgravity environment is a crucial technology promoting space science experiments. Here, a piezoelectric balance (PEBL) based on resonant frequency shift is proposed to achieve mass measurement for microgravity environment. The structural and electrical designs of the PEBL are elaborated, and the theoretical modeling is accomplished to carry out parameter analysis. The finite-element method (FEM) simulation is used to analyze the vibration modes and verify the relationship between the resonant frequency shift and the measured mass, in which the working mode of the PEBL is determined; the impact resistance of the PEBL is analyzed, which shows that it can resist acceleration overload of larger than 50 times the gravity acceleration. A prototype is developed and its vibration characteristics and impedance characteristics are tested experimentally. The experiments successfully verify the effectiveness of theoretical analysis. Furthermore, an automatic mass recognition system is developed to achieve fast detection of the resonant frequency and the measured mass. The developed PEBL system achieves measurement range of 283.36 g with measurement uncertainty of about 1.22% (3.47 g). It is a suitable candidate for mass measurement in microgravity environment with merits of independence on the acceleration field, low power consumption, structure miniaturization, and configuration simplification.

Environmentally friendly electric vehicle design

Particularly for automobiles, the global automotive industry is expanding quickly. One of the most often used forms of transportation in Indonesia is the automobile. A variety of cars, including MPVs, SUVs, City Cars, and Sedans, each with the sophistication and benefits of its own type, are being supplied by producers of four-wheeled vehicles. With a focus on sustainability and minimalism, designers create designs for city cars. This essay's goal is to examine how the environmentally friendly City Car is used in cities. The writing uses analytic techniques, design sketches, and three-dimensional visual representations.

Overview of Identified Challenges in the Development Process of Superconducting Accelerator Magnets

Development challenges in the domain of superconducting magnets are concentrated on technical problems in the current literature. Organizational, domain-specific challenges are often seen as secondary but must be considered with new holistic development approaches like Model-Based Systems Engineering (MBSE) becoming more popular. This work quantifies the domain challenges and gives the foundation to derive success criteria for design support in the future. A systematic literature review has been conducted to identify the overall domain challenges, and extensive interviews in the CERN technology department have been carried out to identify the development challenges on a practical level. Problems in knowledge management have been identified as a major challenge in the development process and the general literature. The paper concludes by picking up the most important challenges from the interviews and literature and puts them into the context of the authors’ knowledge of electrical magnet design.

Unveiling the mechanism of attaining high fill factor in silicon solar cells

AbstractA world record conversion efficiency of 26.81% has been achieved recently by LONGi team on a solar cell with industry‐grade silicon wafer (274 cm2, M6 size). An unparalleled high fill factor (FF) of up to 86.59% has also been certified in a separated device. The theoretical FF limit has been predicted to be 89.26%, while the practical FF is far below this limit for a prolonged interval due to the constraints of recombination (i.e., SRH recombination) and series resistance. The ideality factor (m) in the equivalent circuit of silicon solar cells is consistently ranging from 1 to 2 and rarely falls below 1, resulting in a relatively lower FF than 85%. Here, this work complements a systematic simulation study to demonstrate how to approach the FF limit in design of silicon solar cells. Firstly, a diode component with an ideality factor equal to 2/3 corresponding to Auger recombination is incorporated in the equivalent circuit for LONGi ultra‐high FF solar cell; Secondly, an advanced equivalent circuit is put forward for comprehensive analysis of bulk recombination and surface recombination on the performance, in which specific ideality factors are directly correlated with various recombination mechanisms exhibiting explicit reverse saturation current density (J0). Finally, we evaluate precisely the route for approaching theoretical FF in practical solar cell fabrication based on electrical design parameters using the developed model.

CAPACITANCE EVALUATION ON PARALLEL-PLATE CAPACITORS BY MEANS OF FINITE ELEMENT ANALYSIS

The electric field distribution produced by any disposition of insulating and conducting materials is a key aspect in electrical design, but exact values can only be obtained in simple geometries. In this work, using commercially available F.E.M. software we show the influence of the edge-effect on the electric field distribution of a two parallel-plane conducting plates system surrounded by an insulating medium taking into account the thickness of the conducting plates. We compare our results with previous published works. Finally, we obtain the relationship between capacitance and insulation characteristics, insulation gap, plate dimensions and plate thickness.

Application of finite element method in industrial design, example of an electric motorcycle design project

Abstract This study presents the use of finite element method (FEM) in solving the real engineering problems, e.g., an electric motorcycle design project. A simplified scheme of industrial design is presented, followed by an indication of how to use the capabilities of the selected CAD/CAM/ CAE software in the industrial design of industrial form. Using concurrent design based on the CAD system with the simultaneous use of CAE modules, the interdisciplinary of industrial design engineering was shown, which cannot exist without access to numerical methods. In the electric motorcycle project discussed in this article, the close relation between CAD and CAE modules was used, looking for the best solution in the construction of the motorcycle frame. By conducting a series of numerical simulations based on the FEM and topological optimization, the final shape of the frame and the rear control arm mounting was presented. The designed structure was optimized in terms of mass and effective stress distributions determined from the Huber-Mises-Hencky hypothesis. The resulting model of the frame was adapted to the design project, briefly discussed in the summary of the article. This study indicates the need to use the FEM and CAD/CAM/CAE applications at almost every stage of engineering design.

Electric vehicle charging design: The factored action based reinforcement learning approach

Charging optimization design for Electric Vehicles (EV) is challenging because it must account for various uncertainties and design aspects such as random EVs’ arrivals and departures, battery degradation, and transformer Loss of Life (LoL). Model-free reinforcement learning (RL) can be employed to tackle such the EV charging design where it does not require to explicitly model the environment dynamics and accurately predict relevant system parameters. However, the high complexity involved in conventional RL-based approaches usually limits its application to only small-scale EV charging settings, which is impractical. To overcome this limitation, we employ the factored action based RL method to transform the formulated Markov Decision Process (MDP). Then, we propose novel reward shaping and hybrid learning methods combining the Convolutional Neural Network (CNN) and Proximal Policy Optimization (PPO) algorithm to extract relevant features from high-dimension state space and efficiently solve the transformed MDP problem. Extensive numerical studies demonstrate that the proposed design can be used to control a charging station (CS) supporting a large number of EVs. Moreover, we show that the proposed framework greatly outperforms other baselines including single-agent and multi-agent RL based strategies and a heuristic power scheduling algorithm in terms of the achieved reward.

Networking Strategies of Triboelectric Nanogenerators for Harvesting Ocean Blue Energy

The utilization of abundant blue energy in the ocean could greatly contribute to achieving carbon neutrality. However, the unsolved economic and technical challenges of traditional technologies for harvesting blue energy have resulted in slow progress. Triboelectric nanogenerators (TENGs), as a new approach for converting mechanical energy into electricity, have great potential for blue energy harvesting, which can be connected as networks with different numbers of units for varying scales of energy harvesting. Here, recent advances of networking strategies of TENGs for harvesting blue energy are reviewed, mainly concerning mechanical and electrical connection designs. Anchoring strategies of devices and networks are also discussed. The development of TENG networks could provide an effective solution for large-scale ocean blue energy harvesting, which can also serve as an in-situ energy station or power source for self-powered systems, supporting various marine equipment and activities.

Heat transfer simulation of electric heating fabric system and parametric design: Towards human thermal comfort and energy efficiency

A 3D heat transfer model was developed to optimize the design of electric heating garments (EHGs) towards human thermal comfort and energy efficiency. The model deals with the thermal interaction between human skin, a three-layer electrical heating fabric system, and cold environments, allowing analysis of the heating process and resultant skin temperature. Three heat transfer mechanisms, namely conduction, convection and radiation, were considered. The real-time and final skin temperatures from simulation and measurement exhibited a difference below 4%, demonstrating the efficiency of the model. A steady-state parametric study was conducted using the validated numerical model. Five parameters, such as heating temperature, thermal resistance of the inner and outer fabrics, wind speed, and environmental air temperature, were involved. The results indicate that the heating temperature and thermal resistance of the inner fabric have a more noticeable effect on the temperature of the skin surface below the heated area compared to the other three factors. Apart from the heating temperature, the other four factors have a greater impact on the skin temperature of non-heated regions than that of the heated region. Multiple linear regression analysis was performed to establish a relationship between skin temperature and the five factors. Based on this analysis, a prediction model for skin temperature was developed and subsequently used to determine relevant parameters for EHGs. A method for optimizing the design of electrically heated clothing is proposed, which can achieve the dual goals of human thermal comfort and energy efficiency.

Volatile and Nonvolatile Resistive Switching Coexistence in Conductive Point Hexagonal Boron Nitride Monolayer.

Recently, we demonstrated the nonvolatile resistive switching effects of metal-insulator-metal (MIM) atomristor structures based on two-dimensional (2D) monolayers. However, there are many remaining combinations between 2D monolayers and metal electrodes; hence, there is a need to further explore 2D resistance switching devices from material selections to future perspectives. This study investigated the volatile and nonvolatile switching coexistence of monolayer hexagonal boron nitride (h-BN) atomristors using top and bottom silver (Ag) metal electrodes. Utilizing an h-BN monolayer and Ag electrodes, we found that the transition between volatile and nonvolatile switching is attributed to the thickness/stiffness of chain-like conductive bridges between h-BN and Ag surfaces based on the current compliance and atomristor area. Computations indicate a "weak" bridge is responsible for volatile switching, while a "strong" bridge is formed for nonvolatile switching. The current compliance determines the number of Ag atoms that undergo dissociation at the electrode, while the atomristor area determines the degree of electric field localization that forms more stable conductive bridges. The findings of this study suggest that the h-BN atomristor using Ag electrodes shows promise as a potential solution to integrate both volatile neurons and nonvolatile synapses in a single neuromorphic crossbar array structure through electrical and dimensional designs.

Ecological network analysis and optimization of resilience and efficiency for electric power systems design

The simultaneous increase in natural disasters and human dependence on critical infrastructures for essential services such as water, electricity, etc., places ever-increasing demands on the reliable, safe, resilient design and operation of these infrastructures, with a trade-off between continuity of supply (safety and resilience) and quality of supply (reliability and efficiency) at limited cost. With this in mind, a new methodology for the analysis of electric power systems inspired by natural ecosystems is proposed here and applied to representative systems from literature. Information theory is used to quantify the results of the ecological network analysis (ENA) performed. The analysis shows that electric power systems are more efficient than reliable and vulnerable to disasters. A flow matrix is constructed from the available IEEE systems data, quantified and analyzed using information theory, and finally validated by contingency analysis and SCOPF analysis. The original network configurations are compared to random generated topologies. Comparisons are also made with ENA-inspired configurations. The latter show significantly fewer violations in each contingency scenario compared to the original configurations, further supporting the use of ENA to balance power system efficiency and resilience. Thus, ENA can be used to develop power systems with balanced efficiency and resilience.

A stochastic programming approach for EOL electric vehicle batteries recovery network design under uncertain conditions

With the development of the electric vehicle industry, the number of power batteries has increased dramatically. Establishing a recycling EOL (end-of-life) battery network for secondary use is an effective way to solve resource shortage and environmental pollution. However, existing networks are challenging due to the high uncertainty of EOL batteries, e.g., quantity and quality, resulting in a low recycling rate of the recovery network. To fill this gap, this paper proposes a stochastic programming approach for recovery network design under uncertain conditions of EOL batteries. Firstly, a multi-objective model for battery recovery network is established, considering carbon emissions and economic benefits. Secondly, a stochastic programming approach is proposed to clarify the model. Subsequently, the genetic algorithm is employed to solve the proposed model. Finally, a recovery network case of Region T is given to verify the credibility and superiority of the proposed method. The results demonstrate that the proposed model reduces carbon emissions by 20 metric tons and increases overall economic benefits by 10 million yuan in Region T compared to the deterministic model. Furthermore, the two portions affecting the optimization results are also discussed to provide a reference for reducing carbon emissions and improving economic efficiency in recycling networks.

And SQP-Based Optimisation Algorithm for the Derivative Design of Generator.

This paper briefly reviews methods of optimisation applicable to electrical machine design with emphasis on deterministic techniques, then focusing on synchronous generator design optimisation. The case selected to demonstrate the validity of the approach is that of derivative generator design, based on an existing stator lamination. A single criterion deterministic optimisation algorithm, developed using sequential quadratic programming (SQP) technique, has been employed to obtain an optimum efficiency permanent magnet synchronous generator.

Electrical modelling, design, and implementation of a hardware PEM electrolyzer emulator for smart grid testing

Abstract The high cost and complexity of Proton Exchange Membrane (PEM) electrolyzers pose substantial challenges for their integration and testing within smart grid emulators. Addressing this, our research offers two pivotal contributions. First, we introduce an innovative Equivalent Electrical Circuit (EEC) for PEM electrolyzers. This electrical model serves as an essential tool for evaluating the performance of PEM electrolyzers, especially within the framework of renewable energy systems in smart grids. Our second major contribution is the design and implementation of a hardware PEM electrolyzer emulator based on a DC/DC boost converter. Unlike conventional approaches, our emulator accurately reproduces the nonlinear polarization curve and dynamic behavior of PEM electrolyzers under a large range of operating conditions. By seamlessly integrating into a smart grid emulator, it provides an environment for efficient and cost-effective testing of PEM electrolyzers. Experimental results offer strong validation of the emulator’s ability to replicate the characteristics of the PEM electrolyzer, establishing it as a practical alternative for evaluating and improving smart grid emulators and their management strategies.

Electric power steering system controller design using induction machine

Electric power steering system controller design using induction machine

Electrical system design of teaching building

With the continuous improvement of our country’s education level, the electrical design of teaching buildings has been paid more and more attention. If the safety measures of building facilities are not perfect, once there is a safety problem, it will inevitably bring irreparable huge losses to the personal safety of students and teachers and the property safety of the school. At the same time, taking into account school expenses, economy, energy saving is also a part that cannot be ignored, which requires full consideration of safety, environmental protection and other factors in the process of electrical system design.This paper mainly studies the electrical design of the teaching building, on the basis of strict compliance with national standards and norms, taking into account safety, economy, energy saving and other design factors, independently designed the power supply and distribution system, lighting system, lightning protection system, to ensure the safe operation of building electrical facilities and energy saving operation.

Composite Materials in Advancing Electric Aircraft Technologies

The transition towards electric aviation represents a significant stride in addressing the environmental impact of transportation, particularly concerning gas emissions. With the aviation sector identified as a substantial contributor to carbon emissions, the development of electric aircraft emerges as a crucial innovation towards achieving sustainable air travel. This paper explores the role of composite materials in the advancement of electric aircraft, focusing on their application in airframe construction, electrical systems integration, and the enhancement of propulsion systems. Composite materials, including carbon fiber-reinforced polymer (CFRP), glass fiber-reinforced polymer (GFRP), aramid fiber composite, and hybrid composites, offer superior strength, reduced weight, and high durability, making them ideal for electric aircraft design. Despite their advantages, challenges such as high manufacturing costs and recycling complexities persist. Through a comprehensive analysis, this study examines the potential of advanced manufacturing techniques and sustainable organic materials in overcoming these hurdles, paving the way for the widespread adoption of electric aircraft. The paper highlights the transformative impact of composite materials on electric aviation, addressing both the performance enhancements they facilitate and the obstacles to their broader application.

Deep Retrofitting Study of Government Buildings in the UAE

This report summarizes the findings of a deep retrofitting modelling study of four government buildings across the UAE. Buildings envelope assessment, HVAC, and electrical systems design, installed conditions, maintenance practices and operation methods, and rigorous engineering analysis has been performed for the four buildings to produce calibrated energy models that confirm a good correlation between actual annual energy consumption and advanced simulated energy modeling results. IES-VE software, ASHRAE Guideline 14, and IPMVP were the basis of the energy model calibration based on actual data. Energy retrofitting options were applied to the calibrated energy models of the four government buildings where advanced computational modeling studies have been utilized to analyze different thermal envelope components and external fabric energy efficiency measures in conjunction with the actual HVAC systems. The results have shown that it may be financially challenging to implement a single envelope retrofitting measure on any of the four buildings due to high payback periods. Nevertheless, when conducting an optimization through a holistic building approach targeting the overall envelope enhancements, the financial modeling results provide significantly improved and provide reduced payback periods of the solutions, making them more attractive to investors. Based on the energy modeling results and the cost of the various proposed building envelope solutions provided by Saint-Gobain, the payback period in all cases varies between 15 to 20 years. However, huge savings in terms of carbon emissions are achieved by implementing the deep retrofitting measures, crucial to achieving carbon neutrality within the UAE built environment. Deep retrofitting is a promising segment of the execution roadmap as part of the UAE's decarbonization journey; even though it is capital-intensive upfront, it has a major impact on long-term operational savings. Moreover, it is often more cost-effective than building new and energy-efficient structures from scratch. The findings indicate that deep retrofitting can be a techno-financially viable solution if it is well-planned during major refurbishment or as part of building maintenance. It has significant potential to reduce carbon emissions while also providing a range of benefits such as operational cost savings, improved thermal comfort a feature which has a direct impact on perceived efficiency and productivity at work, indoor air quality, improved asset value, reputational enhancement, and better choice for environmentally-cautious tenants or buyers.

Visualization and analysis of electrical parameter design based on digital sensors

Abstract This paper provides an in-depth study on the application of digital sensor technology in electrical fire detection. It firstly focuses on the design of electrical parameters to improve the accuracy of fire detection. Based on the research results of recurrent neural networks, the article combines the Long Short-Term Memory (LSTM) network and the Gated Recurrent Unit (GRU) neural network. It innovatively proposes an electrical fire feature recognition method based on the LSTMGRU network. The study also incorporates fuzzy inference techniques to optimize the fire alarm decision-making process, which achieves a hierarchical output for electrical fire detection recognition and alarm decision-making. The experimental results show that the LSTM-GRU network achieves an accuracy of 98.83% in electrical fire classification and recognition, significantly better than the results of using LSTM network or GRU network alone. Regarding electrical fire distance recognition, the relative error of the method only ranges from 0.32% to 2.10%, and its output of fire alarm decision is entirely correct. The study not only verifies the high accuracy and reasonableness of the electrical fire feature recognition method based on digital sensing technology, but also provides a brand new idea for recognizing electrical fire detection and alarm decision-making.