Electrically controllable spin filtering in zigzag phosphorene nanoribbon based normal–antiferromagnet–normal junctions

We investigated the electric controllable spin-filtering effect in a zigzag phosphorene nanoribbon(ZPNR) based normal–antiferromagnet–normal junction. Two ferromagnets are closely coupled to the edges of the nanoribbon and form the edge-to-edge antiferromagnetism. Under an in-plane electric field, the two degenerate edge bands of the edge-to-edge antiferromagnet split into four spin-polarized sub-bands and a 100% spin-polarized current can be easily induced with the maximal conductance 2e~2/h. The spin polarization changes with the strength of the electric field and the exchange field,and changes sign at opposite electric fields. The spin-polarized current switches from one edge to the other by reversing the direction of the electric field. The edge current can also be controlled spatially by changing the electric potential of the scattering region. The manipulation of edge current is useful in spin-transfer-torque magnetic random-access memory and provides a practical way to develop controllable spintronic devices.

Research on Electrical Automation Control Design Based on PLC Technology

As science and technology continue to progress forward,electrical automation engineering is also developing,of which programmable logic controller(PLC)technology is widely being used.Through the integration of PLC technology and traditional electrical automation technology,good development of modern science and technology is promoted while traditional automation is preserved.The development of electrical engineering can greatly improve the strength of science,technology,and economy in our country.Based on PLC technology,this paper analyzes the design of electrical automation control.

Adaptive Robust Servo Control for Vertical Electric Stabilization System of Tank and Experimental Validation

A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.

Coordinated Voltage Control of Distribution Network ConsideringMultiple Types of Electric Vehicles

The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.

Stochastic sampled-data multi-objective control of active suspension systems for in-wheel motor driven electric vehicles

This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables.The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets.For this purpose,a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities.Then,an asynchronous fuzzy sampled-data controller,featuring distinct premise variables from the active suspension system,is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership.Furthermore,novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous𝐻2 and𝐻∞performance requirements.Finally,the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.

Implementation of Fuzzy Logic Control into an Equivalent Minimization Strategy for Adaptive Energy Management of A Parallel Hybrid Electric Vehicle

As government agencies continue to tighten emissions regulations due to the continued increase in greenhouse gas production, automotive industries are seeking to produce increasingly efficient vehicle technology. Hybrid electric vehicles (HEVs) have been introduced to mitigate problems while improving fuel economy. HEVs have led to the demand of creating more advanced controls software to consider multiple components for propulsive power in a vehicle. A large section in the software development process is the implementation of an optimal energy management strategy meant to improve the overall fuel efficiency of the vehicle. Optimal strategies can be implemented when driving conditions are known a prior. The Equivalent Consumption Minimization Strategy (ECMS) is an optimal control strategy that uses an equivalence factor to equate electrical to mechanical power when performing torque split determination between the internal combustion engine and electric motor for propulsive and regenerative torque. This equivalence factor is determined from offline vehicle simulations using a sensitivity analysis to provide optimal fuel economy results while maintaining predetermined high voltage battery state of charge (SOC) constraints. When the control hierarchy is modified or different driving styles are applied, the analysis must be redone to update the equivalence factor. The goal of this work is to implement a fuzzy logic controller that dynamically updates the equivalence factor to improve fuel economy, maintain a strict charge sustaining window of operation for the high voltage battery, and reduce computational time required during algorithm development. The adaptive algorithm is validated against global optimum fuel economy and charge sustaining results from a sensitivity analysis performed for multiple drive cycles. Results show a maximum fuel economy improvement of 9.82% when using a mild driving style and a 95% success rate when maintaining an ending SOC within 5% of the desired SOC regardless of starting SOC.

Reducing Electrical Consumption in Stationary Long-Haul Trucks

On average, long-haul trucks in the U.S. use approximately 667 million gallons of fuel each year just for idling. This idling primarily facilitates climate control operations during driver rest periods. To mitigate this, our study explored ways to diminish the electrical consumption of climate control systems in class 8 trucks through innovative load reduction technologies. We utilized the CoolCalc software, developed by the National Renewable Energy Laboratory (NREL), which integrates heat transfer principles with extensive weather data from across the U.S. to mimic the environmental conditions trucks face year-round. The analysis of the CoolCalc simulations was performed using MATLAB. We assessed the impact of various technologies, including white paint, advanced curtains, and Thinsulate insulation on reducing electrical demand compared to standard conditions. Our findings indicate that trucks operating in the eastern U.S. could see electrical load reductions of up to 40%, while those in the western regions could achieve reductions as high as 55%. Such significant decreases in energy consumption mean that a 10 kWh battery system could sufficiently manage the HVAC needs of these trucks throughout the year without idling. Given that many long-haul trucks are equipped with battery systems of around 800 Ah (9.6 kWh), implementing these advanced technologies could substantially curtail the necessity for idling to power air conditioning systems.

Safety and effectiveness of electromyography-induced rehabilitation treatment after epidural electrical stimulation for spinal cord injury:study protocol for a prospective,randomized,controlled trial

Epidural electrical stimulation is a new treatment method for spinal cord injury(SCI).Its efficacy and safety have previously been reported.Rehabilitation treatment after epidural electrical stimulation is important to ensure and improve the postoperative efficacy of epidural electrical stimulation in patients with SCI.Considering that electromyography(EMG)-induced rehabilitation treatment can accurately match the muscle contraction of patients with SCI,we designed a study protocol for a prospective,randomized controlled trial.In this trial,on the premise of adjusting the spinal cord electrical stimulator to obtain the maximum EMG signal of the target muscle,patients with SCI receiving epidural electrical stimulation will undergo EMG-induced rehabilitation treatment.Recovery of muscle strength of key muscles,quality of life,safety and therapeutic effects will be monitored.Twenty patients with SCI who are scheduled to undergo epidural electrical stimulation in Shanghai Ruijin Rehabilitation Hospital will be randomly divided into two groups with 10 patients per group.The control group will receive conventional rehabilitation treatment.The EMG-induced rehabilitation group will receive EMG-induced rehabilitation treatment of the target muscles of the upper and lower limbs based on conventional rehabilitation treatment.After rehabilitation treatment,follow up for all patients will occur at 2 weeks and 1,3 and 6 months.The primary outcome measure of this trial will be evaluation of target muscle recovery using the Manual Muscle Testing grading scale.Secondary outcome measures will include modified Barthel Index scores,integrated EMG values,the visual analogue scale,Spinal Cord Independence Measure scores,and modified Ashworth scale scores.The safety indicator will be the incidence of adverse events.This trial will collect data regarding the therapeutic effects of EMG-induced rehabilitation in patients with SCI receiving epidural electrical stimulation for 6 months after rehabilitation treatment.Findings from this trial will help develop rehabilitation methods in patients with SCI after epidural electrical stimulation.This study protocol was approved by Ethics Committee of Shanghai Ruijin Rehabilitation Hospital(Approval No.RKIRB2022-12)on February 15,2022 and was registered with Chinese Clinical Trial Registry(registration number:ChiCTR2200061674;date:June 30,2022).Study protocol version:1.0.

An Integrated Control Framework for Torque Vectoring and Active Suspension System

Four-wheel independently driven electric vehicles(FWID-EV)endow a flexible and scalable control framework to improve vehicle performance.This paper integrates the torque vectoring and active suspension system(ASS)to enhance the vehicle’s longitudinal and vertical motion control performance.While the nonlinear characteristic of the tire model leads to a relatively heavier computational burden.To facilitate the controller design and ease the load,a half-vehicle dynamics system is built and simplified to the linear-time-varying(LTV)model.Then a model predictive controller is developed by formulating the objective function by comprehensively considering the safety,energy-saving and comfort requirements.The in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy consumption.Finally,the effectiveness of the proposed controller is verified through the rapid-control-prototype(RCP)test.The results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability.

HAN基ECSP凝胶模型的构建与分子动力学模拟

目的从微观分子的角度对硝酸羟胺(HAN)基电控固体推进剂(Electrically Controlled Solid Propellants,ECSP)的性能参数进行模拟与计算。方法利用分子表面静电势(ESP)对HAN分子2种可能的构型进行优化和稳定性分析。通过真空非周期性分子动力学模拟得到聚乙烯醇(PVA)分子稳定构型,并以HAN基ECSP的主要成分按一定比例构建凝胶模型。基于RESP(Restrained Electrostatic Potential)电荷生成更准确的凝胶模型拓扑文件,并进行凝胶模型的分子动力学模拟、模型稳定分析以及模型参数计算。结果凝胶模型总能量相对平均值的周期性波动不超过7%。由于三维PVA链的包裹,H_(2)O分子的扩散系数被大幅削弱。氢键分析和径向分布函数表明氢键键长主要分布在0.2826 nm附近,PVA与H_(2)O间的氢键较少,H_(2)O与HAN、H_(2)O与H_(2)O之间的氢键较多。模型密度为1.405 g/cm^(3),与实验值吻合度高。在283、293、303 K下,HAN基ECSP凝胶模型的拉伸模量依次降低,剪切模量先增后减。在15 K/600 ps冷却速率下,HAN基ECSP凝胶模型的拉伸模量和剪切模量均增大。结论ECSP制备结束后,冷却过程中的环境温度不宜过高,否则容易造成ECSP力学性能的快速下降,快速冷却可以提高ECSP的力学性能。

Oscillation of Dzyaloshinskii–Moriya interaction driven by weak electric fields

Dzyaloshinskii–Moriya interaction(DMI) is under extensive investigation considering its crucial status in chiral magnetic orders, such as Néel-type domain wall(DW) and skyrmions. It has been reported that the interfacial DMI originating from Rashba spin–orbit coupling(SOC) can be linearly tuned with strong external electric fields. In this work, we experimentally demonstrate that the strength of DMI exhibits rapid fluctuations, ranging from 10% to 30% of its original value, as a function of applied electric fields in Pt/Co/MgO heterostructures within the small field regime(< 10-2V/nm). Brillouin light scattering(BLS) experiments have been performed to measure DMI, and first-principles calculations show agreement with this observation, which can be explained by the variation in orbital hybridization at the Co/MgO interface in response to the weak electric fields. Our results on voltage control of DMI(VCDMI) suggest that research related to the voltage control of magnetic anisotropy for spin–orbit torque or the motion control of skyrmions might also have to consider the role of the external electric field on DMI as small voltages are generally used for the magnetoresistance detection.

An ultrasound-guided percutaneous electrical nerve stimulation regimen devised using finite element modeling promotes functional recovery after median nerve transection

Percutaneous electrical nerve stimulation of an injured nerve can promote and accelerate peripheral nerve regeneration and improve function.When performing acupuncture and moxibustion,locating the injured nerve using ultrasound before percutaneous nerve stimulation can help prevent further injury to an already injured nerve.However,stimulation parameters have not been standardized.In this study,we constructed a multi-layer human forearm model using finite element modeling.Taking current density and activated function as optimization indicators,the optimal percutaneous nerve stimulation parameters were established.The optimal parameters were parallel placement located 3 cm apart with the injury site at the midpoint between the needles.To validate the efficacy of this regimen,we performed a randomized controlled trial in 23 patients with median nerve transection who underwent neurorrhaphy.Patients who received conventional rehabilitation combined with percutaneous electrical nerve stimulation experienced greater improvement in sensory function,motor function,and grip strength than those who received conventional rehabilitation combined with transcutaneous electrical nerve stimulation.These findings suggest that the percutaneous electrical nerve stimulation regimen established in this study can improve global median nerve function in patients with median nerve transection.

ECSP制备及电控燃烧技术研究进展

电控固体推进剂(Electrically controlled solid propellant,ECSP)具有点火、燃速及熄火可由馈入电能进行调控的良好性能,而成为一种备受关注的新型推进剂。针对ECSP制备及电控燃烧技术的研究现状,以主氧化剂为分类依据介绍了已公开报道的三类ECSP配方及性能;概述了熔融浇注法和凝胶固化法两种ECSP制备技术路线并分析了其各自的优缺点;从导电机理、电化学分解、热分解三方面分析了ECSP电控燃烧机理;总结了ECSP电控燃烧性能表征试验及ECSP电控燃烧特点;分析了当前公开报道的ECSP电控点火装置的优缺点;最后总结和展望了ECSP在制备技术和电控燃烧机理研究方面的不足和可以深入开展的研究方向。

Design and Analysis of Power and Transmission System of Downhole Pure Electric Command Vehicle

Electric vehicles use electric motors, which turn electrical energy into mechanical energy. As electric motors are conventionally used in all the industry, it is an established development site. It’s a mature technology with ideal power and torque curves for vehicular operation. Conventional vehicles use oil and gas as fuel or energy storage. Although they also have an excellent economic impact, the continuous use of oil and gas threatened the world’s reservation of total oil and gas. Also, they emit carbon dioxide and some toxic ingredients through the vehicle’s tailpipe, which causes the greenhouse effect and seriously impacts the environment. So, as an alternative, electric car refers to a green technology of decarbonization with zero emission of greenhouse gases through the tailpipe. So, they can remove the problem of greenhouse gas emissions and solve the world’s remaining non-renewable energy storage problem. Pure electric vehicles (PEV) can be applied in all spheres, but their special implementation can only be seen in downhole operations. They are used for low noise and less pollution in the downhole process. In this study, the basic structure of the pure electric command vehicle is studied, the main components of the command vehicle power system, namely the selection of the drive motor and the power battery, are analyzed, and the main parameters of the drive motor and the power battery are designed and calculated. The checking calculation results show that the power and transmission system developed in this paper meets the design requirements, and the design scheme is feasible and reasonable.

An Energy Efficient Control Strategy for Electric Vehicle Driven by In-Wheel-Motors Based on Discrete Adaptive Sliding Mode Control

This paper presents an energy-efficient control strategy for electric vehicles(EVs)driven by in-wheel-motors(IWMs)based on discrete adaptive sliding mode control(DASMC).The nonlinear vehicle model,tire model and IWM model are established at first to represent the operation mechanism of the whole system.Based on the modeling,two virtual control variables are used to represent the longitudinal and yaw control efforts to coordinate the vehicle motion control.Then DASMC method is applied to calculate the required total driving torque and yaw moment,which can improve the tracking performance as well as the system robustness.According to the vehicle nonlinear model,the additional yaw moment can be expressed as a function of longitudinal and lateral tire forces.For further control scheme development,a tire force estimator using an unscented Kalman filter is designed to estimate real-time tire forces.On these bases,energy efficient torque allocation method is developed to distribute the total driving torque and differential torque to each IWM,considering the motor energy consumption,the tire slip energy consumption,and the brake energy~?recovery.Simulation results of the proposed control strategy using the co-platform of Matlab/Simulink and CarSim way.

Flexible predictive power-split control for battery-supercapacitor systems of electric vehicles using IVHS

The utilization of traffic information received from intelligent vehicle highway systems(IVHS) to plan velocity and split output power for multi-source vehicles is currently a research hotspot. However, it is an open issue to plan vehicle velocity and distribute output power between different supply units simultaneously due to the strongly coupling characteristic of the velocity planning and the power distribution. To address this issue, a flexible predictive power-split control strategy based on IVHS is proposed for electric vehicles(EVs) equipped with battery-supercapacitor system(BSS). Unlike hierarchical strategies to plan vehicle velocity and distribute output power separately, a monolayer model predictive control(MPC) method is employed to optimize them online at the same time. Firstly, a flexible velocity planning strategy is designed based on the signal phase and time(SPAT) information received from IVHS and then the Pontryagin’s minimum principle(PMP) is adopted to formulate the optimal control problem of the BSS. Then, the flexible velocity planning strategy and the optimal control problem of BSS are embedded into an MPC framework, which is online solved using the shooting method in a fashion of receding horizon. Simulation results verify that the proposed strategy achieves a superior performance compared with the hierarchical strategy in terms of transportation efficiency, battery capacity loss, energy consumption and computation time.

基于ECS-700系统宽融合多支持智能控制应用研究

通过分析ECS-700系统优势,得出ECS-700系统是能满足监控与管理、提高仪表控制系统可靠性,保障生产工艺安全的大型高端集散控制系统;针对兰州某公司水性科技产业园项目水性树脂标段中的电气自控工程实际情况,提出基于ECS-700系统的宽融合多支持智能控制应用方案,设计预处理车间和关键设备智能控制流程。结果表明该应用方案满足了生产和实际工程要求,系统安全可靠,极大地提高了维修效率和控制处理效率。

Machine Learning-based Electric Load Forecasting for Peak Demand Control in Smart Grid

Increasing energy demands due to factors such as population,globalization,and industrialization has led to increased challenges for existing energy infrastructure.Efficient ways of energy generation and energy consumption like smart grids and smart homes are implemented to face these challenges with reliable,cheap,and easily available sources of energy.Grid integration of renewable energy and other clean distributed generation is increasing continuously to reduce carbon and other air pollutants emissions.But the integration of distributed energy sources and increase in electric demand enhance instability in the grid.Short-term electrical load forecasting reduces the grid fluctuation and enhances the robustness and power quality of the grid.Electrical load forecasting in advance on the basic historical data modelling plays a crucial role in peak electrical demand control,reinforcement of the grid demand,and generation balancing with cost reduction.But accurate forecasting of electrical data is a very challenging task due to the nonstationary and nonlinearly nature of the data.Machine learning and artificial intelligence have recognized more accurate and reliable load forecastingmethods based on historical load data.The purpose of this study is to model the electrical load of Jajpur,Orissa Grid for forecasting of load using regression type machine learning algorithms Gaussian process regression(GPR).The historical electrical data and whether data of Jajpur is taken for modelling and simulation and the data is decided in such a way that the model will be considered to learn the connection among past,current,and future dependent variables,factors,and the relationship among data.Based on this modelling of data the network will be able to forecast the peak load of the electric grid one day ahead.The study is very helpful in grid stability and peak load control management.

Simulation of optical and electrical synaptic functions in MoS_(2)/α-In_(2)Se_(3) heterojunction memtransistors

Memtransistors combine memristors and field-effect transistors, which can introduce multi-port control and have significant applications for enriching storage methods. In this paper, multilayer α-In2Se3and MoS2were transferred to the substrate by the mechanical exfoliation method, then a heterojunction MoS_(2)/α-In_(2)Se_(3) memtransistor was prepared. Neural synaptic simulations were performed using electrical and optical pulses as input signals. Through measurements, such as excitatory/inhibitory post-synaptic current(EPSC/IPSC), long-term potentiation/depression(LTP/LTD), and paired-pulse facilitation/depression(PPF/PPD), it can be found that the fabricated device could simulate various functions of neural synapses well, and could work as an electronic synapse in artificial neural networks, proposing a possible solution for neuromorphic storage and computation.

Modeling and Control of Parallel Hybrid Electric Vehicle Using Sea-Lion Optimization

This paper develops a parallel hybrid electric vehicle(PHEV)propor-tional integral controller with driving cycle.To improve fuel efficiency and reduce hazardous emissions in hybrid electric vehicles(HEVs)combine an electric motor(EM),a battery and an internal combustion engine(ICE).The electric motor assists the engine when accelerating,driving longer highways or climbing hills.This enables the use of a smaller,more efficient engine.It also makes use of the concept of regenerative braking to maximize energy efficiency.In a Hybrid Electric Vehicle(HEV),energy dissipated while braking is utilized to charge the battery.The proportional integral controller was used in this paper to analyze engine,motor performance and the New European Driving Cycle(NEDC)was used in the vehicle driving test using Matlab/Simulink.The proportional integral controllers were designed to track the desired vehicle speed and manage the vehi-cle’s energyflow.The Sea Lion Optimization(SLnO)methods were created to reduce fuel consumption in a parallel hybrid electric vehicle and the results were obtained for the New European Driving Cycle.