Problem Of Energy Loss Research Articles

Overview of Wireless Charging Technology Optimization for Electric Vehicles

In recent years, electric vehicles (EVs) have attracted wide attention for their clean, energy-saving, quiet operation and high energy efficiency. Wireless charging technology achieves complete electrical isolation between the power supply and the electrical equipment. It not only has the advantages of safety and flexibility but also avoids a series of problems such as charging cable mismatch. It is one of the trends of the future development of electric vehicle power supply technology, but it needs to be further improved in terms of energy loss and safety. This paper first introduces the concept of wireless charging and then elaborates the principle of magnetic coupling charging, which is popular in electric vehicles. Secondly, in view of the energy loss and other problems, the author combs the resonant charging mode, increasing the trunk coil, and other ways to reduce the energy loss. Changing the shape of the motor controller and using synthetic materials to promote heat dissipation and reduce human radiation. Finally, the challenges of wireless charging of electric vehicles are explained, and the future development of electric vehicles is prospected.

Application Research of Power Measurement Data Exchange Based on Uninterruptible Power Supply

With the maturity of the smart meter embedded system integration mode, the power consumption information can be fed back to the management center by the intelligent terminal through the power Internet of Things. The smart terminal adopts the narrowband data communication mode. However, the narrowband channel interval is hindered by interference signals, resulting in serious data packet loss. Therefore, a stable and efficient acquisition scheme is needed to ensure its smooth interaction. Based on the application of smart meter data communication, we analyze the power consumption optimization and carrier transmission optimization of the power Internet of Things and propose a data analysis method based on self-learning and external characteristics, which is used to calculate the offline execution strategy of smart meters when they encounter factors such as power outage or intrusion. A production task-driving rule is designed. The external characteristics of deep learning data of the power Internet of Things are collected. The accuracy of data classification is judged according to the parallel Internet of Things of a convolutional neural network and a long-term and short-term memory deep neural network. When dealing with high-dimensional original data, the data network is graded to reduce the work of feature selection and the difficulty of training. Moreover, we improve the autonomous execution ability of an embedded terminal device in an offline state. We also strengthen the ability of abnormal data detection and judgment learning to meet the requirements of efficient and stable operation of the power grid. Simulation results verify that compared with the current mainstream schemes, the performance of the proposed scheme is improved by more than 17%. Besides, the fault tolerance rate is enhanced by 29%, and the power consumption after optimization is reduced by 26.3% and 42.8%. These effects highlight the role of data processing in embedded systems. It solves the problem of abnormal data and energy loss affecting the accuracy of error estimation of electric energy meters, opens up a new way for data acquisition and processing of large-scale smart meters, and further improves the service level of information management of power systems.

Investigation into the Effect of Permeable Boundary Sealing on the Behavior of Hydrate Exploitation via Depressurization Combined with Heat Injection

Depressurization combined with heat (mainly hot water) injection is an important technique for exploiting natural gas hydrate (NGH). To overcome the problems of pore water intrusion and hot water energy loss in the technique, this paper employs a method of setting sealing boundaries in permeable overburden and underburden to exploit NGH. The influence of the presence of sealing boundaries on NGH exploitation performances was numerically investigated. The results indicate that the sealing boundaries in permeable overburden and underburden can inhibit water intrusion and reduce heat loss, significantly improving the efficiency of hydrate dissociation and gas production. Specifically, the hydrate dissociation and gas production efficiency increased by 22.0–30.1% and 63.9–85.1%, respectively. Moreover, there is an optimal sealing vertical distance within the range of 0–15 m, maximizing the mining efficiency of NGH at the end of production. On the other hand, the presence of sealing boundaries effectively limits the escape range of CH4 in the permeable overburden and underburden, resulting in an increasing gas-to-water ratio and an increasing energy efficiency. These findings provide theoretical and technical support for the mining of NGH by depressurization combined with heat injection.

Multi-Layer QCA Reversible Full Adder-Subtractor Using Reversible Gates for Reliable Information Transfer and Minimal Power Dissipation on Universal Quantum Computer

The effects of quantum mechanics dominate nanoscale devices, where Moore’s law no longer holds true. Additionally, with the recent rapid development of quantum computers, the development of reversible gates to overcome the problems of energy and information loss and the nano-level quantum-dot cellular automata (QCA) technology to efficiently implement them are in the spotlight. In this study, a full adder-subtractor, a core operation of the arithmetic and logic unit (ALU), the most important hardware device in computer operations, is implemented as a circuit capable of reversible operation using QCA-based reversible gates. The proposed circuit consists of one reversible QCA gate and two Feynman gates and is designed as a multi-layer structure for efficient use of area and minimization of delay. The proposed circuit is tested on QCADesigner 2.0.3 and QCADesigner-E 2.2 and shows the best performance and lowest energy dissipation. In particular, it shows tremendous improvement rates of 180% and 562% in two representative standard design cost indicators compared to the best existing studies, and also shows the highest circuit average output polarization.

Enhancing Electrical Generator Efficiency through Advanced Technologies Flotation Magnets, Sealed Vacuums, and Liquid Hydrogen Cooling.

In the scientific endeavour to enhance the efficiency of modern electrical generators, three innovative technologies: flotation magnets, sealed vacuums, and liquid hydrogen-cooled electrical energy transfer wires offer electrical engineers promising solutions to the classical problems of entropic energy loss. These three technologies aim to reduce friction at moving components points of contact, reduce or negate air resistance to moving turbines, and achieve a state of near-zero electrical resistance in the wires which transfer this energy to storage devices. This paper explores how potentially these advanced electrical engineering techniques can be integrated into the current design and operation of electrical turbine generators, with the scope of potentially revolutionising their output performance and entropic energy efficiency.

Event triggering fixed time secondary control of DC microgrid considering FDI attacks

SummaryAiming at the problem that distributed secondary control is vulnerable to FDI attacks in DC microgrid, which affects the stability of the system, and the problems of communication redundancy and energy loss in traditional distributed secondary control, an event triggered fixed time distributed secondary control scheme based on high‐order differentiator is proposed. The high‐order differentiator is used to estimate the FDI attack signal of the system. Then, using the estimated attack signal, a fixed time distributed secondary controller based on event triggering is designed to eliminate the impact of the attack signal, and realize the adjustment of bus voltage and accurate power distribution. The strict stability and the absence of Zeno behavior are proved. The simulation results show that the proposed control strategy can significantly reduce the impact of attacks on the system, and the event triggered fixed time control reduces the energy consumption of the system and the update numbers of the controller, making the system have better dynamic performance.

Hyperbolic enhancement of a quantum battery

A quantum system which can store energy, and from which one can extract useful work, is known as a quantum battery. Such a device raises interesting issues surrounding how quantum physics can provide certain advantages in the charging, energy storage, or discharging of the quantum battery as compared to their classical equivalents. However, the pernicious effect of dissipation degrades the performance of any realistic battery. Here, we show how one can circumvent this problem of energy loss by proposing a quantum battery model which benefits from quantum squeezing. Namely, charging the battery quadratically with a short temporal pulse induces a hyperbolic enhancement in the stored energy, such that the dissipation present becomes essentially negligible in comparison. Furthermore, we show that when the driving is strong enough, the useful work which can be extracted from the quantum battery, that is the ergotropy, is exactly equal to the stored energy. These impressive properties imply a highly efficient quantum energetic device with abundant amounts of ergotropy. Our theoretical results suggest a possible route to realizing high-performance quantum batteries, which could be realized in a variety of platforms exploiting quantum continuous variables. Published by the American Physical Society 2024

Variable magnification beam expander system based on semiconductor laser

Due to the different divergence angles in two perpendicular directions and the presence of astigmatism in edge-emitting semiconductor lasers, the communication distance and efficiency of underwater communication are seriously affected. Therefore, based on the fact that the semiconductor laser beam belongs to Gaussian beam, satisfying Gaussian characteristics and collimating and expanding characteristics, a system composed of fast-axis collimation mirror and variable magnification beam expander is designed. Simulation is performed, and the final divergence angle is calculated. Experimental results show that the divergence angles of the fast axis and the slow axis have been compressed from 49 and 9, respectively, to 0.315 mrad and 0.180 mrad. Simulation demonstrates that the system can achieve propagation over a distance of 100m underwater and solve the alignment difficulty of APT. The designed structure is compact, easy for processing and adjustment, with high practical value, which helps to solve the problems of optical energy loss and low coupling efficiency in underwater long-distance communication.

Computational Analysis Of Pipe Bend Angle Effect On Pressure Drop

The air conditioning system is a significant energy source inskyscrapersfor supplying cool air to all rooms. However, the process has energy losses due to the ducting used. If the problem of energy loss can be solved, the air conditioning system will bring advantages in terms of energy efficiency and financial savings. A pressure drop in air duct pipe installations, such as pipe bends, is one type of energy loss. This research intends to use Computational Fluid Dynamics (CFD) to investigate the effect of pipe bend angles and velocity relationships on pressure drop in air duct pipe installations, which has previously been validated by experimental research with a 0.17% error percentage. This study focuses on square pipe bends with varying 45o, 60o, and 90o bend angles. The research showed that when testing the highest fluid velocity of 19.68 m/s, the highest pressure drop was 275.69 Pa on the pipe bend angle of 90o, while the lowest pressure drop was 256.41 Pa on the pipe bend angle of 45o. When testing the lowest fluid velocity of 9.77 m/s the highest pressure drop was 67.73 Pa on the pipe bending angle of 90owhile the lowest pressure drop was 62.98 Pa on thepipe bending angle of 45o. The simulation results indicate that the larger pipe bend angle result in a higherpressure drop, and vice versa.

Buck-Boost Converter with Fractional Control for Electric Vehicles

In this paper, non-integer order control is applied to improve the performance of a buck-boost dc-dc power converter with ultracapacitor based on state feedback techniques. The approach is based on stabilization in the Lyapunov's sense for linear rational-order systems. The ultracapacitor can overcome the classical problems of energy losses due to the use of batteries, giving more accuracy, autonomy and efficiency to the electrical vehicles.

SOC 밸런싱 기능을 갖춘 새로운 배터리 스위칭 시스템

The conventional dual-voltage automotive system has a large size and high cost due to its magnetic components. To eliminate the magnetic components, previous research adopted switched-capacitor converters. However, to provide the proper output voltage with small capacitance, high switching frequency should be employed, which leads to high energy loss and EMI problems. To mitigate the drawbacks, the battery switching system using some switches was considered. This system has charging and discharging modes through series or parallel battery connections. However, the batteries can be under-utilized and unbalanced due to the state of charge (SOC) problem. Therefore, this paper proposes a new battery switching system with SOC balancing capability. The proposed system only adds a few switches, in which switching in the order of battery connection can be applied. Through this structure, all batteries can be utilized and balanced. In addition, battery switching can be controlled simply. To confirm the validity of the proposed system, a 160 W prototype was implemented and experimented.

A novel two-stage thermophotovoltaic-thermoelectric system based on micro combustion

Aiming at solving the problem of low energy conversion efficiency due to high energy loss in micro-combustion power system, this work innovatively proposed a two-stage thermophotovoltaic-thermoelectric energy conversion system. The effects of the inlet velocity and the equivalence ratio on the energy conversion efficiency of the two-stage thermophotovoltaic-thermoelectric energy conversion system are investigated. The results indicate that two-stage thermophotovoltaic-thermoelectric energy conversion system significantly alleviates the problem of large energy loss in the micro-combustion power system and improves the energy output and energy conversion efficiency of the micro-combustion power system. As the inlet velocity increases, the total output efficiency of the micro-photovoltaic module, thermoelectric module and the overall system decreases. Under the H2/air flow condition with an inlet velocity of 6 m/s and an equivalence ratio of 1.0, the total system reaches its a maximum energy conversion efficiency of 5.05% and generates an output power of 6.17 W.

Thermodynamic analysis of a typical compressed air energy storage system coupled with a fully automatic ejector under slip pressure conditions

To solve the problem of energy loss caused by the use of conventional ejector with fixed geometry parameters when releasing energy under sliding pressure conditions in compressed air energy storage (CAES) system, a fully automatic ejector capable of adjusting key geometric parameters to maintain the maximum ejection coefficient by an automatic control device according to the running parameters is proposed in this paper. By establishing a thermodynamic model of a typical CAES system coupled with a fully automatic ejector, the effect of the fully automatic ejector on the system performance is studied under sliding pressure conditions. The results show that the fully automatic ejector has the most sensitive ejection coefficient with the variation of high-pressure gas pressure. The cycle efficiency and exergy efficiency of the proposed system were 56.91% and 52.64%, respectively. Compared with the coupled conventional ejector, the cycle efficiency, exergy efficiency, and output power of the system were increased by 0.93%, 0.81%, and 4.59%, respectively. The exergy loss of the combustion chamber is the largest among the components within the system, accounting for 65.2% of the total exergy loss, followed by the heat exchanger, which accounts for 13.8% of the exergy loss, while the fully automatic ejector has the smallest exergy loss, accounting for only 0.8% of the total exergy loss. When the extraction point is at the first stage of the turbine, the system cycle efficiency and external energy efficiency vary parabolically with the extraction pressure, but the system performance will change abruptly when the pressure at the extraction point approaches 1.5 MPa. The system performance index is more sensitive to the change of turbine inlet temperature than other variables. Reducing the heat exchanger heat transfer temperature difference and increasing the fully automatic ejector outlet pressure are the effective ways to improve system performance.

Research on the Intelligent Energy Governance of Parallel Hybrid Vehicle Based on Deep Learning

To realize the intelligent energy governance of hybrid vehicles, a Deep-Q-Network energy controller based on the construction of parallel hybrid vehicle model is proposed, which aiming at energy loss problem of parallel hybrid vehicles and combining deep learning with reinforcement learning, and it is simulated through the ADVISOR software platform and compared with the traditional fuzzy logic strategy. The experimental results indicate that the DQN-based control strategy proposed in this paper reduces both the energy consumption and exhaust emissions of parallel hybrid vehicles. Compared with the traditional fuzzy control strategy, fuel consumption is reduced by 0.43L while the fuel economy increases by 10.9%. and exhaust gas such as CO44, CO, NOxx the emission were reduced by 28.9%, 0.2%, and 7.4%, respectively. It shows the feasibility and effectiveness of the proposed methods.

A multimodal fusion method for Alzheimer's disease based on DCT convolutional sparse representation.

The medical information contained in magnetic resonance imaging (MRI) and positron emission tomography (PET) has driven the development of intelligent diagnosis of Alzheimer's disease (AD) and multimodal medical imaging. To solve the problems of severe energy loss, low contrast of fused images and spatial inconsistency in the traditional multimodal medical image fusion methods based on sparse representation. A multimodal fusion algorithm for Alzheimer' s disease based on the discrete cosine transform (DCT) convolutional sparse representation is proposed. The algorithm first performs a multi-scale DCT decomposition of the source medical images and uses the sub-images of different scales as training images, respectively. Different sparse coefficients are obtained by optimally solving the sub-dictionaries at different scales using alternating directional multiplication method (ADMM). Secondly, the coefficients of high-frequency and low-frequency subimages are inverse DCTed using an improved L1 parametric rule combined with improved spatial frequency novel sum-modified SF (NMSF) to obtain the final fused images. Through extensive experimental results, we show that our proposed method has good performance in contrast enhancement, texture and contour information retention.

System optimization of steam generation in the dual-flash compound circulation system

Concentrating on the problem of massive energy loss in the compressor, expansion valve, and the other components present in the high-temperature heat pump system under extensive temperature lift, the dual-flash compound circulation system is proposed and the thermodynamic model of the dual-flash compound circulation system was established. The article combines the multivariate simulated annealing algorithm, utilizes the system COP as the optimization goal, and completes the calculation of the thermodynamic parameters in the steady-state of the system that is based on satisfying the conditions of the system process. Using R245fa as the refrigerant, the condensation temperature is set within the range of 110°C–140°C for the model calculation. The results show that, compared to the traditional two-stage compression system under the same environment, the COP of the dual-flash compound circulation system can be increased up to 5.71%–12.13%, and the exergy efficiency can be increased by 5.11%–10.71%, respectively. Besides, steam production per unit refrigerant is also increased by 3.79%–5.14%. Finally, the feasibility of the theoretical model is verified by simulation, and it is concluded that the dual-flash compound circulation system has better steam production performance at the extensive temperature lift and the elevated condensation temperature.

Recent advances of two-dimensional lubricating materials: from tunable tribological properties to applications

2D nanomaterial lubricants have received increasing attention as mild and environmentally friendly friction and wear moderators. They can act as promising industrial antiwear agents to alleviate problems of energy loss and resource waste caused by wear of mechanical parts.

에너지자립을 위한 PV+ESS+UPS 일체형 전력변환장치 설계 및 실험

In this paper, aims to develop an integrated power conversion system to compensate for the problem of energy loss due to a number of power conversion processes when installing existing solar power facilities, energy storage system(ESS), and uninterruptible power supplies(UPS), which are applied to improve energy consumption and power quality of the temperature-controlled distribution center.BR The proposed integrated power conversion system has a PV+ESS+UPS function and could supply power to a load in the event of a power failure without installing a separate UPS. In addition, the purpose is to develop the optimal capacity of an integrated power air conditioning system and a solar power generation and energy storage system for the energy independence of the constant temperature distribution center.

A novel offloading approach of IoT user perception task based on quantum behavior particle swarm optimization

To solve the problem of high time consumption and energy loss of edge computing perceptual task offloading in the mobile IoT (Internet of things), it is necessary to increase the particle population diversity and the performance of escaping the local optimum solution in the intelligent optimization algorithm. For the offloading scenario of multi edge center servers and smart devices of multi IoT users, the NQPSOOM method (A new method of user perceptual task offloading in the IoT based on optimizing strategy of quantum behavior particle population) was proposed. The adaptability variance of the quantum behavior particle population was designed to measure the convergence of the particle population. The logistic chaos perturbation strategy was used to improve the performance of the intelligent optimization algorithm of escaping the local optimum solution. The exchange and mutation operations of fast elite non-dominated sorting genetic algorithm based on crowding coefficient were designed to select the particle population with a high diversity of quantum behavior particle population. Compared with the other five perceptual task computing offloading methods in recent three years, considering the convergence of the perceptual offloading model, the impact of the number of smart devices of IoT users, the number of edge center servers and the perceptual task data size on the optimal offloading method, the NQPSOOM method improves the performance of the perceptual task offloading model, including reducing the adaptability of the intelligent optimization algorithm by 4.89% on average, that is, facilitating the convergence speed of the intelligent optimization algorithm by 4.89%, and lowering the time consumption of the algorithm by 4.08% and energy loss by 3.91% on average.

Simulation of energy recovery system of high speed transmission shaft dynamic torque test bench

A hydraulic energy recovery and control system is proposed to solve the energy loss problem of the current vehicle transmission shaft torque test bench. On the basis of the original system, power recovery is realized by parallel hydraulic compensation. PID module is used to control the displacement of piston variable pump and motor respectively to adjust the speed and torque to achieve the established working conditions. The feasibility of the hydraulic system and control scheme is verified by AMEsim-MATLAB software and experiments. The results show that the proposed system can not only adjust the set speed and torque dynamically, but also achieve high power recovery.