A New Energy Optimal Control Scheme for a Separately Excited DC Motor Based Incremental Motion Drive

This paper considers minimization of resistive and frictional power dissipation in a separately excited DC motor based incremental motion drive （IMD）. The drive is required to displace a given, fixed load through a definite angle in specified time, with minimum energy dissipation in the motor windings and minimum frictional losses. Accordingly, an energy optimal （EO） control strategy is proposed in which the motor is first accelerated to track a specific speed profile for a pre-determined optimal time period. Thereafter, both armature and field power supplies are disconnected, and the motor decelerates and comes to a halt at the desired displacement point in the desired total displacement time. The optimal time period for the initial acceleration phase is computed so that the motor stores just enough energy to decelerate to the final position at the specified displacement time. The parameters, such as the moment of inertia and coefficient of friction, which depend on the load and other external conditions, have been obtained using system identification method. Comparison with earlier control techniques is included. The results show that the proposed EO control strategy results in significant reduction of energy losses compared to the existing ones.

Design and Application of Third-order Denitration Online Control Technology

In order to alleviate the pressure of environmental protection and further strengthen the monitoring and control of NOx emission of thermal power units, combining with the transformation of boiler low-nitrogen burner, combustion optimization, static and dynamic ratio of air and coal, and SCR denitration system process, third-order NOx online control technology was designed and applied, which takes the combustion security, boiler efficiency and environmental evaluation into account and provide reference for thermal power units to deepen energy conservation and emission reduction.

Energy Optimization of the Fin/Rudder Roll Stabilization System Based on the Multi-objective Genetic Algorithm （MOGA）

Energy optimization is one of the key problems for ship roll reduction systems in the last decade. According to the nonlinear characteristics of ship motion, the four degrees of freedom nonlinear model of Fin/Rudder roll stabilization can be established. This paper analyzes energy consumption caused by overcoming the resistance and the yaw, which is added to the fin/rudder roll stabilization system as new performance index. In order to achieve the purpose of the roll reduction, ship course keeping and energy optimization, the self-tuning PID controller based on the multi-objective genetic algorithm （MOGA） method is used to optimize performance index. In addition, random weight coefficient is adopted to build a multi-objective genetic algorithm optimization model. The objective function is improved so that the objective function can be normalized to a constant level. Simulation results showed that the control method based on MOGA, compared with the traditional control method, not only improves the efficiency of roll stabilization and yaw control precision, but also optimizes the energy of the system. The proposed methodology can get a better performance at different sea states.

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.

球形电动机及其研究发展综述

球形电动机是一种具有球体结构的新型电动机,可单机实现在三维空间内的多自由度运动,且适合应用于人工智能及姿态控制系统动量球等相关领域,得到了各国学者的广泛关注与研究。球形电动机拓展了转子运动范围,是电动机行业未来的一个重要发展方向。与传统单自由度电动机相比,球形电动机结构较为复杂,且运动模式较为特殊,因此,对球形电动机的分析研究有别于传统单自由度电动机。该文整理各国学者对球形电动机的研究工作,总结归纳球形电动机的概念及发展历程,对比研究球形电动机不同的工作原理、拓扑结构及设计优化方法,探讨球形电动机的性能、转子位置检测方法、控制方法、转子支撑方式、应用场合及关键技术,最后总结球形电动机的未来发展趋势。

电气自动化技术在工业照明系统中的应用探讨

电气自动化技术能够通过控制系统实现节能降耗,而照明作为电气工程领域的一部分,能耗影响不容忽视。据统计,目前照明能耗在工厂电能消耗中占比将近18%,存在大量可优化的空间。常用的照明方式主要是借助自然光或人工照明,以满足特定环境下的照明需求。应用电气自动化技术后,不仅能够提高工业照明的智能化水平,还能全面提升照明设施的使用性能、降低照明能耗、提高使用寿命。

基于航班信息确定旅客数模型联动空调节能技术研究

针对机场航站楼内空调系统能耗高且节能潜力巨大的特点,提出一种基于航班信息动态预测分时段分区旅客数,进而联动优化空调节能控制的新方法。新方法研究重点在于航站楼空调调控分区的划分、航班信息有效数据的提取、分时段分区旅客数模型的构建、节能档位控制的实现策略与步骤。结合华南地区某支线机场航站楼冷源及空调末端控制的实际测试数据进行模拟分析,结果表明,在保障旅客舒适度的基础上,通过分区旅客数精准调控空调系统运行模式,实现了能耗较大幅度的降低,节能成效显著,为航站楼空调节能技术提供了新的思路,为同类型其他机场提供了参考。

绿色发展理念下新能源汽车电机控制技术及其性能优化策略

新能源汽车的出现与快速发展,改善了交通系统运行而产生的环境污染问题,同时也使人们对不可再生能源的依赖性不断降低。目前,新能源汽车的发展前景较为广阔,但总体上面临着续航里程短的问题,因此,这对新能源汽车的电机及其控制系统提出了较高要求。新能源汽车开发过程中,相关人员亟须应用高性能的电机控制手段,通过有效控制,优化新能源汽车及电机系统的整体性能。本文立足绿色发展的视角,围绕新能源汽车电机控制技术及其性能优化进行分析,提出适当策略,以供参考。

基于自动控制技术下农业机械能效优化

随着现代农业的发展,农业机械在提升生产效率和减少劳动强度方面发挥了重要作用。然而,传统农业机械的能效优化仍面临较多问题与挑战。该文通过引入智能控制系统,实现对农业机械各项参数的实时监控与调节,阐述了利用可编程逻辑控制器(PLC)和预测模糊控制(PFC)技术,在温度、土壤湿度和光照强度等方面优化农业生产过程,以提高生产效率,降低能耗,确保作物的质量和产量。研究结果可为实现农业生产智能化、可持续性发展提供技术支持。

Review of the development of power system out-of-step splitting control and some thoughts on the impact of large-scale access of renewable energy

Out-of-step oscillation is a very destructive physical phenomenon in power system, which could directly cause big blackout accompanied by serious sociology-economic impacts. Out-of-step splitting control is an indispensable means, which could protect the system from major shocks of out-of-step oscillation. After years of development, it has achieved certain amount of research results. Have the existing methods been able to meet the requirements of out-of-step splitting? What improvements are needed? Under this background, this review is written. It combs the development of out-of-step splitting control technologies and analyzes the technical routes and characteristics of different methods. It points out the contradiction between rapidity and optimality is the biggest technical problem, existing in both the traditional local measurement based out-of-step splitting protection and the wide-area information based out-of-step splitting protection. It further points out that the advantages of the two types of protections can be combined with the unique physical characteristics of the out-of-step center to form a more advantageous splitting strategy. Besides, facing the fact of large-scale renewable energy access to power grid in recent years, this review also analyzes the challenges brought by it and provides some corresponding suggestions. It is hoped to provide some guidance for the subsequent research work.

智能电子控制系统在低温电池管理中的应用与优化

低温电池针对化学电源低温缺陷而研发,广泛应用于极地科考、医疗电子、电力通信、公共安全等领域,正日益成为锂电池行业的重要组成部分。智能电子控制技术使系统有更高的自主分析和决策能力,在低温电池制造管理中具有应用前景。本文研究总结了低温电池研发现状和发展方向,把握各类低温电池特性,基于此分析电池智能化管理技术及方案,保障极端情况下电池管理系统性能,旨在提升新兴电池技术的管理水平。

电气控制技术在风力发电系统中的应用

风能作为一种取之不尽、用之不竭的自然资源,逐渐成为人类重要的能源之一。但风速、风向等因素的变化会对风力发电系统的发电效率和稳定性产生影响。如何提高风力发电系统的效率和稳定性,是风能利用面临的重要挑战。而电气控制技术可以通过对设备的精确控制和实时监测,实现对风力发电设备的有效监测和控制,保证发电的稳定和连续性。基于此,深入探讨了电气控制技术在风力发电系统中的应用及其重要性。

基于AI技术的机房节能优化方案探讨

存量机房由于投产时间较早,没有进行系统化的规划布局,导致制冷设备不能有效的解决机房的冷量需求,为解决部分存量通信机房气流组织混乱,能耗管理粗放等问题,需要引进智能化的技术分析手段对机房进行节能焕新优化。本文依托于AI大数据技术去探查分析机房能耗管理方面存在的问题,为机房节能降耗提供诊断结果,从而输出合理有效的节能优化方案。

煤矿通风系统中自动化控制技术的应用策略

煤矿通风系统在煤矿生产中起着至关重要的作用,而自动化控制技术的应用对提高通风系统效率、降低能耗和提升安全性具有重要意义。旨在探讨煤矿通风系统中自动化控制技术的应用策略,通过系统的文献综述和理论分析,为煤矿通风系统的优化提供参考。

污水处理厂污水处理节能技术与改进分析

基于可持续发展的实际需求,水资源利用上推出了诸多不同的技术手段,污水处理技术手段作为其中之一,在实际应用过程中,不仅降低了生态污染,也提高了资源利用率。但一些污水处理技术需要耗费较大能源,因此在后续的技术升级过程中应加强节能技术的改进。基于此,结合实际案例深入分析污水处理厂污水处理节能技术的改进方向、改进思路和具体的改进策略,以求降低污水处理费用、能耗,提高污水处理厂的整体效益。

新能源汽车电机控制技术及其性能优化策略探索

随着社会对于环境保护的重视与新能源汽车技术发展,使得新能源汽车成为了全球汽车产业中的热点话题。在新能源汽车中,电机控制技术是关键的核心技术之一,对于提升车辆性能、延长续航里程以及实现智能化驾驶都具有重要意义。因此对新能源汽车电机控制技术及其性能优化策略进行分析,旨在为推动新能源汽车行业转型与升级提供一定的参考借鉴。

新能源汽车电子控制系统的优化分析

新能源汽车作为环保和能源转型的重要载体,其电子控制系统的性能直接影响车辆的安全性、效率和驾驶体验。文章以新能源汽车电子控制系统为切入点,首先分析了电子控制系统的组成和工作原理,然后对电子控制系统存在的问题进行了探讨,包括动力电池管理系统问题、驱动电机控制系统问题、制动能量回收系统问题和总线网络通信系统问题等。在此基础上,提出了针对电子控制系统的优化策略,包括动力电池管理系统、驱动电机控制系统等多个方面的具体优化方案,旨在为新能源汽车电子控制系统的设计和优化提供参考依据,推动新能源汽车电子控制技术得到进一步发展。

光伏发电系统与储能技术的集成与优化

探讨光伏发电系统与储能技术的集成与优化,以提高能源利用效率和系统稳定性。阐述光伏发电系统和储能技术的基本原理与特点,并分析其集成方法,包括性能优化、能量管理与调度策略以及智能控制与监测系统的设计应用。通过对某光伏发电站与储能系统的集成优化方案进行实例分析,并对实施效果进行评估与分析,验证集成优化的有效性和实用性,为光伏发电系统与储能技术的进一步发展提供重要参考。

电子信息科学中的自动控制技术研究与应用

本研究通过深入探索优化算法、模糊控制和神经网络等控制方法,成功将其用于电子设备控制、信息处理和数据分析等关键环节。研究结果显示,这些技术的应用不仅显著提升工作效率,减少人工干预,而且有效降低错误率,提高信息处理的准确性。具体来说,模糊控制方法在处理模糊、不确定的数据时表现出色;优化算法帮助找到最优操作策略;神经网络则展现出深度学习和自主决策的强大能力。展望未来,这些自动控制技术在通信、网络安全、人工智能等多个领域具有广阔的应用前景,将推动电子信息科学领域的持续发展。根据研究结果,深入研究和应用自动控制技术在电子信息科学中的应用,将大幅提升电子信息设备的控制效能和信息数据的处理质量,同时,令相关技术领域取得更大的突破。

智能控制技术在电子信息系统中的优化与改进

阐述智能控制技术在提高系统性能、响应速度和节能方面的优势。探讨智能控制技术的改进方向,包括机器学习和深度学习的应用。分析智能控制技术在实际应用中的挑战与解决方法。