Improved Clamped Diode Based Z-Source Network for Three Phase Induction Motor

The 3Φinduction motor is a broadly used electric machine in industrial applications,which plays a vital role in industries because of having plenty of beneficial impacts like low cost and easiness but the problems like decrease in motor speed due to load,high consumption of current and high ripple occurrence of ripples have reduced its preferences.The ultimate objective of this study is to control change in motor speed due to load variations.An improved Trans Z Source Inverter(ΓZSI)with a clamping diode is employed to maintain constant input voltage,reduce ripples and voltage overshoot.To operate induction motor at rated speed,different controllers are used.The conventional Proportional-Inte-gral(PI)controller suffers from high settling time and maximum peak overshoot.To overcome these limitations,Fractional Order Proportional Integral Derivative(FOPID)controller optimized by Gray Wolf Optimization(GWO)technique is employed to provide better performance by eliminating maximum peak overshoot pro-blems.The proposed speed controller provides good dynamic response and controls the induction motor more effectively.The complete setup is implemented in MATLAB Simulation to verify the simulation results.The proposed approach provides optimal performance with high torque and speed along with less steady state error.

A Digital Phase Locked Loop Speed Control of Three Phase Induction Motor Drive: Performances Analysis

This paper deals with performance analysis and implementation of a three phase inverter fed induction motor (IM) drive system. The closed loop control scheme of the drive utilizes the Digital Phase Locked Loop (DPLL). The DPLL is safely implemented all around the well known integrated circuit DPLL 4046. An ex-perimental verification is carried out on one kw scalar controlled IM system drives for a wide range of speeds and loads appliance. This presents a simple and high performance solution for industrial applications.

Analysis and Design of Derivative Free Filters against Derivative Based Filter on the Simulated Model of a Three Phase Induction Motor

Recursive state estimation methods have aroused substantial attraction among many researchers and in particular, the drives research fraternity has shown increased interest in recent years. State estimators that surrogate direct measurements play an integral part in the operation of modern a.c. drives. Their robustness and accuracy are very much decisive for the performance of the drive. In this paper, a comparative analysis of the three nonlinear filtering schemes to estimate the states of a three phase induction motor on the simulated model is presented. The efficacy of Ensemble Kalman Filter (EnKF) against the traditional Jacobian based Filter or Extended Kalman Filter (EKF) and almost forbidden, hitherto least-attempted Unscented Kalman Filter (UKF) is very much exemplified. Theoretical aspects and comparative simulation results are investigated comprehensively with respect to three different scenarios viz., step changes in load torque, speed reversal, and low speed operation. Also, “Monte Carlo Simulation” runs have been exploited very extensively to show the superior practical usefulness of EnKF, by which the minimum mean square error (MMSE), which is often used as the performance index, ostensibly gets mitigated very radically by the proposed approach. The results throw light on alleviating the intrinsic intricacies encountered in EKF in parlance with the observer theory.

Single Phase Induction Motor Drive with Restrained Speed and Torque Ripples Using Neural Network Predictive Controller

In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of DC drives. Precise control of drives is the main attribute in industries to optimize the performance and to increase its production rate. In motion control, the major considerations are the torque and speed ripples. Design of controllers has become increasingly complex to such systems for better management of energy and raw materials to attain optimal performance. Meager parameter appraisal results are unsuitable, leading to unstable operation. The rapid intensification of digital computer revolutionizes to practice precise control and allows implementation of advanced control strategy to extremely multifaceted systems. To solve complex control problems, model predictive control is an authoritative scheme, which exploits an explicit model of the process to be controlled. This paper presents a predictive control strategy by a neural network predictive controller based single phase induction motor drive to minimize the speed and torque ripples. The proposed method exhibits better performance than the conventional controller and validity of the proposed method is verified by the simulation results using MATLAB software.

Intelligence Based Soft Starting Scheme for the Three Phase Squirrel Cage Induction Motor with Extinction Angle AC Voltage Controller

Whenever a squirrel cage induction motor is started, notable electromechanical torque and current pulsations occur. The adverse effects of starting torque pulsations and high inrush current in induction motor are eliminated using digital power electronic soft starting schemes that guarantee higher degrees of compliance of the requirements of an ideal soft starter for the induction motor. Soft starters are cheap, simple, reliable and occupy less volume. In this paper, an experimental setup of soft starting technique with extinction angle AC voltage controller and a speed and stator current based closed loop scheme is demonstrated using Artificial Neural Network (ANN) and Fuzzy Logic Control (FLC) by the way of MATLAB/SIMULINK based simulation. The ANN based soft starting scheme produces best results in terms of smooth starting torque and least inrush current. The results thus obtained were satisfactory and promising.

The time and space characteristics of magnetomotive force in the cascaded linear induction motor

To choose a reasonable mode of three-phase winding for the improvement of the operating efficiency of cascaded linear induction motor, the time and space characteristics of magnetomotive force were investigated. The ideal model of the cascaded linear induction motor was built, in which the B and C-phase windings are respectively separated from the A-phase winding by a distance of d and e slots pitch and not overlapped. By changing the values of d and e from 1 to 5, we can obtain 20 different modes of three-phase winding with the different combinations of d and e. Then, the air-gap magnetomotive forces of A-, B-, and C-phase windings were calculated by the magnetomotive force theory. According to the transient superposition of magnetomotive forces of A-, B-, and C-phase windings, the theoretical and simulated synthetic fundamental magnetomotive forces under 20 different arrangement modes were obtained. The results show that the synthetic magnetomotive force with d = 2 and e = 4 is close to forward sinusoidal traveling wave and the synthetic magnetomotive force with d = 4 and e = 2 is close to backward sinusoidal traveling wave, and their amplitudes and wave velocities are approximately constant and equal. In both cases, the motor could work normally with ahigh efficiency, but under other 18 arrangement modes （d= 1, e=2; d= 1, e=3; d= 1, e=4;...）, the synthetic magnetomotive force presents obvious pulse vibration and moves with variable velocity, which means that the motor did not work normally and had high energy loss.

Off-Line Identification of Induction Motor Parameters

This study presented an off-line identification method of induction motor (IM) parameters. Before startup,the inverter drive performed automatically a modified DC test, a locked-rotor test, a no-load test and a step-voltage test to identify all the parameters of an induction motor. No manual operation and speed signals were required in the process. In order to obtain effective messages and improve the accuracy of identification, the discrete fast Fourier transform (DFFT) and the least-squares were used to process the signals of currents and voltages. A phase-voltage measuring method for motors was also proposed, which measured directly the actual conducting time of three upper switches in the inverter without need for a dead-time compensator. The validity, reliability and accuracy of the presented methods have been verified by the experiments on a VSI-fed IM drive system.

Testing and Analysis of Induction Motor Electrical Faults Using Current Signature Analysis

The proposed method deals with the emerging technique called as Motor Current Signature Analysis (MCSA) to diagnosis the stator faults of Induction Motors. The performance of the proposed method deals with the emerging technique called as Motor Current Signature Analysis (MCSA) and the Zero-Sequence Voltage Component (ZSVC) to diagnose the stator faults of Induction Motors. The unalleviated study of the robustness of the industrial appliances is obligatory to verdict the fault of the machines at precipitate stages and thwart the machine from brutal damage. For all kinds of industry, a machine failure escorts to a diminution in production and cost increases. The Motor Current Signature Analysis (MCSA) is referred as the most predominant way to diagnose the faults of electrical machines. Since the detailed analysis of the current spectrum, the method will portray the typical fault state. This paper aims to present dissimilar stator faults which are classified under electrical faults using MCSA and the comparison of simulation and hardware results. The magnitude of these fault harmonics analyzes in detail by means of Finite-Element Method (FEM). The anticipated method can effectively perceive the trivial changes too during the operation of the motor and it shows in the results.

能够校正相位误差的感应电机全阶磁链观测器

感应电机的传统全阶磁链观测器,采用预估校正法进行离散时转子磁链估计相位的误差较小。但是电机高速运行时,随着载波比的减小,估计相位误差会随之增大,进而引起电机控制性能下降。有鉴于此,通过分析磁链相位误差的影响以及电机控制变量之间的相互作用关系,推导出一种具有相位误差自校正功能的改进全阶磁链观测器。最后在感应电机实验平台上验证了改进全阶观测器的有效性。

不同绕组连接方式对五相电机故障后的电磁性能影响

针对五相电动机的星形连接方式和五边形连接方式进行仿真,得出转矩、转速、气隙磁密、磁密、电磁损耗等数据,以及在缺相故障后星形连接方式和五边形连接方式产生的数据进行比对,尽可能的分析两种不同连接状态下的电磁影响。对在不同工况下的不同连接方式所得的不同结果进行比对,得到这两种连接状态下的优缺点,并对两种连接方式在故障后的电磁影响进行分析,提出在缺相故障后的电磁区别。

基于EasiMotor的单相感应电机性能计算及成本优化设计

以一个2极单相感应电机作为分析模型,通过EasiMotor软件研究了50W470、50W600这两种硅钢片材料及铁芯长度对电机性能的影响,得出了满足电机技术要求的成本优化设计方案。

参数化分析法在电机类课程教学中的应用

电机结构参数对电机性能的影响是“电机学”及“电机设计”等课程学习的重点和难点,求电机性能指标随电机结构参数变化而变化的关系曲线的过程称为参数化分析。探讨了参数化分析法作为辅助教学手段应用于“电机学”及“电机设计”等课程教学的内容与方法,这对于深入理解“电机学”及“电机设计”基本理论和基本方法,准确把握电机结构参数变化对电机性能的影响,以及设计和研究新型电机非常有利。

三相异步电机匝间短路健康状况评估

三相异步电机是电力系统的重要组成部分,其在生产生活中起着重要作用。电机故障中发生概率最大的一种故障便是匝间短路故障,若不及时解决,会产生不利影响。但正常方法测量匝间短路故障较为困难。因此,现提出基于扩展Park变换和模糊神经网络的匝间故障诊断方法,进一步简化分析计算,准确检测电机故障问题。同时,分别从模拟仿真与实物样机两方面对故障检测法进行验证。

船用五相感应电机模型预测电流控制研究

传统五相感应电机矢量控制中包含多个PI参数需整定,且存在电压调制环节而造成控制系统结构复杂。引入模型预测电流控制代替矢量控制以解决该问题。获得预测模型后,在预测电流控制器中对五相逆变器输出的32个电压矢量进行遍历寻优,得到最优电压矢量的开关状态。为解决五相感应电机谐波空间电流影响,在代价函数中使用权重因子对谐波电流项进行调节,实现对谐波电流的抑制,并给出谐波含量与转速及权重因子之间关系。仿真结果表明,应用模型预测电流控制策略的五相感应电机动态响应速度快,在工况切换时依然具有良好的控制效果。

基于导通相实时电感定位的SRM无位置传感器控制方法

针对目前在开关磁阻电机无位置传感器控制中利用其导通相电感进行转子位置角度估算存在受磁路饱和影响大的问题,提出一种基于导通相实时电感定位的无位置传感器控制方法。通过确定开关磁阻电机导通相对应导通区间及区间内定位点的选取方法,研究该定位点对应相电感与其饱和电流间的函数关系,根据该函数关系并实时检测导通相的实际电流以实现其转子位置角度的估算,最后通过仿真与实验对其效果进行了验证,结果表明:该方法有效提高了开关磁阻电机在磁路饱和状态下的无位置传感器控制精度,因而具有较好的应用价值。

六相直线感应电机模糊间接矢量控制

针对直线电机运行于复杂环境条件下,系统建模准确度不高,参数难以整定的问题,提出了一种适用于六相直线感应电机的模糊间接矢量控制方法;在同步旋转坐标系下对六相直线电机建模,并阐述了间接矢量控制的原理;将模糊控制算法应用于间接矢量控制中的速度环,根据位移和速度的偏差直接模糊调节给定电磁力,使得参数的整定不再依赖准确的系统模型,且参数调节更为简单;通过对隶属函数分区和采用中心法清晰化,减小了模糊控制算法的计算量,从而能够满足实时计算的要求;将所提算法在数字信号处理器(DSP)中实现,并在半实物仿真平台上验证,结果表明所提算法投入后,位移和速度误差减小都超过了65%,能够实现电机速度和位移的准确控制,且通用性好。

船舶电力推进系统的仿真优化策略

电力推进船舶的船—机—桨匹配分析中,仿真所需的模型复杂,工况多,耗时长。用于驱动船舶推进电机的二极管中点钳位(Neutral-Point Clamped,NPC)型三电平逆变器拓扑结构复杂,仿真中计算量大,严重拖慢了船舶电力推进系统整体的仿真速度。为解决此问题,在Matlab/Simulink软件中对一种船舶电力推进系统建模仿真,研究其特性,提出一种由受控电压源替代逆变器驱动十二相感应电机的仿真优化策略以缩短仿真所需时长。对比分析优化模型与原模型的仿真结果可知,优化模型启动与制动性能良好,可在电流、转矩、转速等外特性与原模型基本一致的前提下,将仿真耗时缩短数十倍。表明优化策略准确可行,符合复杂工况的仿真需求,可用于提高电力推进船舶的仿真效率,对同类调速系统有参考意义。