Novel torque ripple minimization algorithm for direct torque control of induction motor drive

To elucidate the principles of notable torque and flux ripple during the steady state of the conventional direct torque control （DTC） of induction machines, the factors of influence torque variation are examined. A new torque ripple minimization algorithm is proposed. The novel method eradicated the torque ripple by imposing the required stator voltage vector in each control cycle. The M and T axial components of the stator voltage are accomplished by measuring the stator flux error and the expected incremental value of the torque at every sampling time. The maximum angle rotation allowed is obtained. Experimental results showed that the proposed method combined with the space vector pulse width modulation （SVPWM） could be implemented in most existing digital drive controllers, offering high performance in both steady and transient states of the induction drives at full speed range. The result of the present work implies that torque fluctuation could be eliminated by imposing proper stator voltage, and the proposed scheme could not only maintain constant switching frequency for the inverter, but also solve the heating problem and current harmonics in traditional induction motor drives.

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.

Induction Motor Modeling Based on a Fuzzy Clustering Multi-Model—A Real-Time Validation

This paper discusses a comparative study of two modeling methods based on multimodel approach. The first is based on C-means clustering algorithm and the second is based on K-means clustering algorithm. The two methods are experimentally applied to an induction motor. The multimodel modeling consists in representing the IM through a finite number of local models. This number of models has to be initially fixed, for which a subtractive clustering is necessary. Then both C-means and K-means clustering are exploited to determine the clusters. These clusters will be then exploited on the basis of structural and parametric identification to determine the local models that are combined, finally, to form the multimodel. The experimental study is based on MATLAB/SIMULINK environment and a DSpace scheme with DS1104 controller board. Experimental results approve that the multimodel based on K-means clustering algorithm is the most efficient.

A study of EV induction motor controller based on rotor flux oriented control

Induction motor is a multi-parameter, non-linear and strong coupling system, which requires efficient control algorithms. In this paper, rotor flux oriented control （FOC） algorithm based on voltage source inverter-fed is deduced in detail, including stator voltage compensation, closed-loop PI parameters＇ calculation of torque and rotor flux. FOC＇ s Simulink model is setup to simulate torque and rotor flux＇s response. At last, the experimental results are shown.

Matlab/Simulink环境下异步电机建模及其工程应用

基于数学分析,建立了αβ静止坐标系下包含铁损的异步电机仿真模型,对应空载工况下的计算机仿真结果与真实电机空载实验结果非常相符。此外,应用本模型进行异步电机效率优化控制以及SVPWM过调制控制的仿真和实验,结果良好。

基于广义似然比检验算法的IM定子故障诊断

围绕闭环控制下逆变器驱动感应电机(IM)系统的定子故障问题,设计了一种新型的基于广义似然比检验算法的定子故障诊断方法。IM定子故障通常从匝间短路开始,可演变为相间或相对地故障,从而导致定子电流不平衡。所提出的诊断方法首先进行定子电流对称分量计算,然后基于最大似然估计器估计基频和三相相量,并应用广义似然比检验实现不平衡故障诊断。在1.5 kWIM测试平台上,用与定子绕组串联的附加电阻模拟故障,并进行了故障诊断测试,实验结果验证了新方案可对IM定子故障进行有效检测。

模糊规则下IM换相转矩脉动控制方法仿真

为了抑制感应电动机在换相过程中产生的转矩脉动,保证其稳定运行,依据模糊规则,设计一种感应电动机(Induction motor, IM)换相转矩脉动控制方法。根据换相过程中产生的低速段和高度段电流转矩,得出导致电动机产生转矩脉动的主要原因是电流变化率,根据上述结论利用模糊理论的模糊逻辑对定子磁链和换相转矩误差属性进行模糊化处理,在模糊集控制器中导入模糊化处理结果,调整变论域,获取变论域模糊控制器输出信号。进一步根据模糊规则对模糊控制器进行模糊推理,由此完成IM换相转矩脉动控制。仿真结果表明,所提方法下控制器的跟随性能良好,可及时跟随开通相和关断相的动作变化,有效控制转矩脉动,保证换相过程中转矩的稳定,有利于降低电动机故障的发生频率。

基于二阶变增益滑模的感应电机电压模型磁链观测器

针对无速度传感器感应电机驱动系统,基于二阶滑模的电压模型磁链观测器可以有效提升传统开环电压模型观测器的转速估计鲁棒性。然而,现有二阶滑模电压模型观测器仍然存在以下2个问题:1)滑模观测器常数增益与可变稳定性条件间的不匹配问题;2)由于存在直流偏置,需要采用非理想积分器来估计转子磁链。针对这2个问题,该文提出相应解决方案:1)改进二阶滑模观测器结构,并根据稳定性条件设计可变增益,以同时实现宽调速范围内的观测器稳定性与抖振抑制;2)根据滑模观测器的输出,设计一种带直流偏置补偿的积分器,以提升磁链估计精确度。最后,在3.7 kW的感应电机实验装置上进行对比实验,证明所提方法有效性。

感应电机损耗最小化预测控制策略研究

针对传统感应电机效率优化算法在复杂工况下存在鲁棒性和动态性能差的问题,提出了一种基于损耗模型控制算法的感应电机效率优化预测控制策略。搭建考虑铁损的电机功率损耗模型,包含铁损、铜损以及漏感等因素,提高了损耗模型的精度。采用模型参考自适应观测器估计损耗模型中的定子电阻,设计电流模型为参考模型,电压模型为可调模型。基于电机铁损模型构建连续集模型预测电流控制器,提升系统的动态性能。实验结果验证了所提算法的可行性和有效性。

Overview of Model Predictive Control for Induction Motor Drives

Model predictive control(MPC)has attracted widespread attention in both academic and industry communities due to its merits of intuitive concept,quick dynamic response,multi-variable control,ability to handle various nonlinear constraints,and so on.It is considered a powerful alternative to field oriented control(FOC)and direct torque control(DTC)in high performance AC motor drives.Compared to FOC,MPC eliminates the use of internal current control loops and modulation block,hence featuring very quick dynamic response.Compared to DTC,MPC uses a cost function rather than a heuristic switching table to select the best voltage vector,producing better steady state performance.In spite of the merits above,MPC also presents some drawbacks such as high computational burden,nontrivial weighting factor tuning,high sampling frequency,variable switching frequency,model/parameter dependence and relatively high steady ripples in torque and stator flux.This paper presents the state of the art of MPC in high performance induction motor(IM)drives,and in particular the progress on solving the drawbacks of conventional MPC.Finally,one of the improved MPC is compared to FOC to validate its superiority.It is shown that the improved MPC has great potential in the future high performance AC motor drives.

The use of feld programmable gate array(FPGA)in direct torque control of induction motor

In this paper, the feasibility of embedding the direct torque control （DTC） of an induction machine into field programmable gate arrays （FPGA） is investigated. DTC of an induction machine is simulated in a MATLAB/Simulink environment using a Xilinx system generator. The resulting design has a flexible and modular structure where the designer can customize the hardware blocks by changing the number of inputs, outputs, and algorithm when it is compared to the designs implemented using classical microcontrollers and digital signal processors. With its flexibility, other control algorithms can easily be programmed and embedded into the FPGA. The above system has been implemented on Xilinx Spartan 3A DSP FPGA controller. Simulation and experimentation have been performed to prove the validity of the proposed methodology.

A robust principal component analysis-based approach for detection of a stator inter-turn fault in induction motors

Health condition monitoring of induction motors is important because of their vital role and wide us in a variety of industries.A stator inter-turn fault(SITF)is considered to be the most common electrical failure according to statisti-cal studies.In this paper,an algorithm for the detection of an SITF is presented.It is based on one of the blind source separation techniques called principal component analysis(PCA).The proposed algorithm uses PCA to discriminate between the faulty components of motor current signatures and motor voltage signatures from other components.The standard deviation of one of the decomposed vectors is used as a statistical SITF criterion.The proposed criterion is robust to non-fault conditions including voltage quality problems and large mechanical load changes as well as harmonic contaminants in the voltage supply.In addition,with a straightforward and low computational burden in the fault detection process,the proposed method is computationally efficient.To evaluate the performance of the proposed method,large numbers of practical and simulation scenarios are considered,and the results confrm the good performance,high degree of accuracy,and good convergence speed of the proposed method.

异步电机定转子参数的辨识方法研究

基于异步电机在两相坐标系里的状态方程,通过检测电机的定子电压、电流和转速信号,而不需要转子磁链信号,利用最小二乘法递推算法对电机参数进行了辨识,由于不需要转子磁链,这样通过观测得到的磁链就不会影响辨识的准确性,消除了参数计算和磁链观测之间的耦合,仿真结果和实验验证了辨识的准确性。

电机故障诊断支持向量机

基于数据的机器学习是现代智能技术中的重要方面。统计学习理论 (Statistical learning theory SL T)是研究小样本情况下机器学习规律的新理论。支持向量机 (Supportvector machine SVM)是在这一理论体系基础上发展起来的一种通用学习方法。SL T和 SVM正成为继神经网络研究之后新的研究热点。通过对鼠笼式异步电动机转子断条故障进行实验模拟 ,对实验获取的采样电流信号经 FFT分析 ,构造以低频到高频的频谱特性为分量的学习样本向量 ,通过支持向量机 SVM对故障电流样本的训练 ,使 SVM具有分类功能。最后 ,采用 SVM对电动机各种转子断条故障进行诊断分类 ,取得较满意的结果 ,说明支持向量机 SVM是进行故障诊断的一种新方法。

改进的感应电机静态补偿电压模型及低速性能分析

针对静态补偿电压模型磁链观测器存在的低速运行时磁链估计不准确、低速性能不佳等问题,提出了一种改进的感应电机静态补偿磁链估计电压模型。该模型在高速运行时采用静态补偿电压模型进行磁链估计,低速时采用d-q电流模型进行补偿。该模型能在全速范围内实现平滑切换,有效提高了电机低速运行磁链估计性能。结合感应电机数学模型,通过理论推导建立了基于改进静态补偿电压模型的矢量控制非线性磁链动态模型,并利用李雅普诺夫线性化理论分析了该非线性动态模型在低速运行时的稳定性。同时,对电机参数不准确情况下的改进静态补偿电压模型磁链估计参数敏感性进行了分析。仿真研究和实验结果验证了理论分析的正确性。

基于新型转子磁链观测器的异步电机转矩闭环矢量控制

在电动汽车等特殊应用领域,异步电机通常需要直接跟踪主控系统下发的转矩指令。扭矩传感器的安装不仅会增加成本,而且降低系统的可靠性。因此,对电磁转矩的准确观测至关重要。在设计滑模观测器实现异步电机反电动势准确观测的基础上,通过构造反电动势和转子磁链的状态方程,提出一种新型转子磁链滑模观测器。该观测器实现了对转子磁链的准确观测,继而实现了电磁转矩观测及转矩闭环控制。该方案的突出优势在于,转子磁链的观测对转子电阻、励磁电感等电机参数有着较强的鲁棒性。同时,基于此设计的转矩闭环控制系统具有较好的转矩跟踪控制能力。仿真及实验验证了该方案的可行性和有效性。

感应电机模型预测磁链控制

模型预测控制(model predictive control,MPC)具有原理简单、多变量控制和容易处理非线性约束等优点,是近年来在电力电子与电力传动领域受到广泛关注和研究的一种控制方法。MPC一般基于最小化目标函数的原则来实现系统的优化控制,但当目标函数中控制变量的量纲不一致时,需要设计相应的权重系数来实现对多个变量的同时控制。以感应电机的磁链和转矩控制为例,由于目前尚缺乏通用的理论设计方法来确定磁链和转矩的权重系数,为保证调速系统在不同的运行点具有良好的动静态性能,在实际应用中需要通过大量的仿真或实验来确定权重系数的大小。为此,提出一种适用于感应电机控制的改进MPC。通过深入推导磁链和转矩之间的解析关系,将定子磁链幅值和电磁转矩的同时控制转换为等效的定子磁链矢量的控制,从而消除了传统方法中繁琐的权重设计,而且算法简单,容易实现。此外,文中还对数字控制延迟进行了补偿,并且采用预励磁的方法来增大起动转矩,并减小起动电流。最后,在两电平逆变器感应电机平台上进行了仿真和实验,结果表明所提方法在很宽的速度范围内都有良好的性能。

一种感应电机直接转矩控制系统性能改善方案

该文首先从理论上对数字化控制感应电机传动系统的性能进行了推导,对电机转矩的变化量进行了详细的分析然后结合直接转矩控制的原理,提出了一种新型的控制方案。从仿真结果可以看出:不仅系统的动态响应依然很快而且可以有效地改善稳态转矩脉动较大的情况;同时由于采用了空间电压矢量调制,稳定了逆变器的开关频率。

考虑铁损的电动汽车用感应电机矢量控制及其能量优化策略

电动汽车用感应电机励磁电感一般较小,高速时铁损大,采用经典矢量控制策略存在轻载低效和由忽略铁损引起的控制不精确等问题.首先根据同步旋转坐标系下考虑铁损的感应电机动态数学模型,分析了铁损对按转子磁场定向矢量控制的影响,给出了动态和稳态两种补偿方案.然后从调节磁通水平的角度,提出了一种基于损耗模型的感应电机能量优化控制策略,并讨论了铁损等效电阻变化对优化控制的影响.仿真和实验结果表明,给出的补偿控制策略克服了经典矢量控制磁场定向及转矩控制不准确的缺陷;提出的的能量优化控制策略不但节能效果明显,而且具有寻优速度快、转矩和转速波动小等优点,为高性能要求的电动汽车电驱动系统高效运行提供了有效途径.

电动汽车用感应电机动态平衡点的反馈耗散Hamilton控制

针对电动汽车行驶过程中路况变化频繁,其对应的配套感应电机给定转速和负载不断变化,从而导致系统平衡点也随之变化的特点和忽略铁损引起的控制不精确的问题,研究了基于动态平衡点的计及电动汽车用感应电机反馈耗散Hamilton控制问题.首先根据感应电机的工作特性计算出平衡点,然后选取适当的状态反馈,通过预置反馈的方法建立了系统的动态模型,并基于能量耗散特性实现了对电动汽车用感应电机在动态平衡点处的反馈耗散Hamilton控制,保证了整个系统的全局稳定性.最后仿真结果验证了该控制策略的有效性.