基于模糊自适应的开关磁阻电机变磁链研究

传统直接转矩控制使开关磁阻电机定子电流幅值很大,增加了电机铜耗。通过分析不同磁链对系统性能的影响及磁链与转矩之间的关系,提出了一种变磁链的直接转矩控制改进方法。在Matlab/Simulink中搭建四相开关磁阻电机模糊自适应控制的直接转矩系统仿真模型,仿真结果表明该系统响应速度快,能有效减小定子电流幅值,抑制转矩脉动。针对电机起动过程中电流脉冲大的问题,在改进方法中加入电流控制模块,可明显降低起动时电流的幅值,提高电机的性能。     

变速变桨风力发电机组的优化控制

提出了大型变速变桨风力发电机组在不同控制阶段的优化控制策略。在低风速时,采用自适应转矩控制方式,实现机组的变速运行,追踪最佳风能利用系数。在额定风速以上时,为了解决传统桨距控制方式系统超调量大的问题,提出了一种新型气动转矩观测器,并将气动转矩与发电机转矩偏差输入控制器。通过Bladed外部控制器模块编程并进行仿真,结果表明,所提出的控制策略能够更好地追踪最大功率点,并改善桨距控制效果,稳定功率输出。     

电力系统传动转矩控制器低频振荡控制方法研究

转矩控制器时常发生的低频振荡问题,不仅影响电力系统正常运行、对相关系统设备具有较大危害,而且电力系统参数的过快变化,也在一定程度上提升了低频振荡的控制难度,为此,面向电力系统中的转矩控制器,提出一种低频振荡控制方法。根据网压信号构建系统的状态空间模型方程,经初始化与重采样处理粒子集,依据粒子最优状态估计去除信号噪声,基于dq轴模型与网压网流得到信号序列,识别出低频振荡模式;采用网侧电压、电流基波分量以及输入电压,架构dq坐标下变流器模型,通过选取控制器状态变量,设计灵敏度检验策略,制定加权函数提取条件,得到低频振荡控制器。仿真实验阶段,通过发电机网压波形、变流器交流侧电压及电流波形、中间直流回路电压波形,验证所提方法能够较好地控制低频振荡现象,且有效抑制了发电机数量多少的影响。     

异步电动机的直接转矩控制

阐述了直接转矩控制的基本数学关系,在交流传动机车的整个调速范围内,建立了异步电动机的直接转矩控制方案,并在MATLAB环境下时该方案进行了仿真.仿真结果表明该技术具有优异的静、动态性能,非常适合电力牵引.该研究结果为交流传动机车的设计提供了参考依据.     

基于Super-twisting算法的永磁同步电机直接转矩控制

针对传统永磁同步电机直接转矩控制中转矩和磁链脉动较大的问题,文章基于Super-twisting算法,提出了一种二阶滑模直接转矩控制策略.该控制策略使用二阶滑模控制结构取代传统PI控制和滞环控制结构,设计了磁链和转矩滑模控制器,提高了系统控制的动态响应能力.文章使用SVPWM矢量控制取代传统DTC中的开关表,保持开关频...     

内置式永磁同步电机12扇区直接转矩控制方法

以电压矢量的最大利用率为基础引入12扇区控制方法,该方法细化矢量选择和扇区划分,增加可供选择的电压矢量数目,有效发挥了电压矢量对磁链和转矩的控制优势;研究变化的内滞环带对转矩脉动的影响,仿真结果表明相对于传统的6扇区直接转矩控制方式,该文引入的12扇区控制方法可明显减小转矩和磁链脉动,同时保留了传统的直接转矩控制中转矩动态响应迅速的特点;在不同操作条件(转速和转矩不同)下,进一步优化12扇区的控制效果。仿真结果验证了理论分析的正确性和所提出方法的可行性。     

基于DSVM的无刷双馈风电系统抗脉动模糊DTC策略

无刷双馈发电机没有电刷和滑环,故障率低,在风力发电系统中有良好的应用前景,但其采用直接转矩控制(DTC),在低转速下运行时转矩脉动较大,不利于系统稳定运行。文章提出一种改进的模糊直接转矩控制策略,在控制输入中增加了转矩误差的变化率,从而改进了模糊规则表中低速运行区的控制算法。同时,将离散空间电压矢量调制(DSVM)技术引入到直接转矩控制系统中,增加了可供选择的空间电压矢量。在MATLAB/Simulink中搭建了无刷双馈风力发电系统模型,并在渐变风和随机风两种工况下进行了动态仿真。仿真结果表明,在低风速运行时转矩无明显波动,在两种工况下该系统都能稳定运行,并快速地跟随风速的变化,该控制策提高了系统的稳定性和鲁棒性。     

基于运行数据的风电机组转矩控制性能评估

风电机组的性能评估方法具有多样性及复杂性的特点,基于风电场SCADA系统中采集的大量风电机组运行数据,对风电机组转矩控制的性能评估方法进行了研究。在深入分析风电机组中发电机转速与发电机转矩关系的基础上,提出了风电机组在最佳风能利用系数C₍p(max))跟踪区内的转矩优化控制的性能评估方法。通过筛选有效数据,拟合计算出风电机组的实际运行转矩增益系数;再通过与理论最优转矩增益系数进行对比,找出风能捕获能力较弱的风电机组,进而采取措施提高其发电量。通过软件仿真及案例分析表明,该方法在不增加设备及成本的情况下,可有效识别因转矩控制的性能差而影响发电量的风电机组,以便及时进行控制策略调校,维护风电场的利益。     

一种考虑风力机实际大转动惯量的改进最优转矩法

考虑实际大型风力机的大转动惯量,在传统最优转矩控制方法的基础上,提出一种增大加速转矩(IAT)的改进方法,缩短系统的调节时间,以此提高风力机的性能。通过建立小信号分析方法,与最优转矩法相比,证明该方法具有更好的动态特性。最后,在风力机专业仿真软件FAST中进行对比仿真,在不同风况下验证所提出的改进方法具有更好的风能捕获效率。     

永磁技术应用于风力发电机的挑战

世界上十大风机制造商,有超过一半的制造商正在进行永磁发电机技术的研究,或是早已向市场推出了永磁发电机产品.通常,最简单的将传统双馈异步发电机转换为永磁发电机的办法就是用同速的永磁发电机和全功率变流器替代现在高速齿轮箱后面的双馈异步发电机,仅需要对风机和机舱布置做很小的设计改动.永磁技术提供了各种不同的概念,从10 r/min到20 r/min的大转矩直驱发电机.同时也提供了各种结构方式,像外转子轴向磁通发电机,永磁励磁使电机同时具有高效、高转矩,因为励磁不需要向系统连续地输入能量.而且,也会产生较低的同步电感,可使电机具有大转矩.     

Gain scheduling control of variable speed WTG under widely varying turbulence loading

Probabilistic paradigms for wind turbine controller design have been gaining attention. Motivation derives from the need to replace outdated empirical-based designs with more physically relevant models. This paper proposes an adaptive controller in the form of a linear quadratic Gaussian (LQG) for control of a stall-regulated, variable speed wind turbine generator (WTG). In the control scheme, the strategy is twofold: maximization of energy captured from the wind and minimization of the damage caused by mechanical fatigue due to variation of torque peaks generated by wind gusts. Estimated aerodynamic torque and rotational speed are used to determine the most favorable control strategy to stabilize the plant at all operating points (OPs). The performance of the proposed controller is compared with the classical proportional-integral-derivative (PID) controller. The LQG is seen to be significantly more efficient especially in the alleviation of high aerodynamic torque variations and hence mechanical stresses on the plant drive train. Simulation results validate the effectiveness of the proposed method.     

Drive train dynamics assessment and speed controller design in variable speed wind turbines

This paper deals with the speed controller design in DFIG based wind turbines, and investigates stability and performance of the drive train dynamics against different control strategies. It is shown that speed controller design based on the single mass drive train model may result in unstable mechanical modes, because it ignores the dynamics of the flexible shaft. Then, another control approach, known as feedforward compensation of the shaft torsional torque, is examined. It is shown that this control method results in poorly damped oscillations of torsional torque and turbine speed during the transient conditions. The open loop transfer function from the electromagnetic torque to the generator speed contains a dual quadratic function representing the dynamics of flexible shaft. The dual quadratic function comprises resonant and anti-resonant frequencies that greatly affect the stability of the drive train dynamics. Next, a step-by-step procedure for designing the speed controller based on the two-mass drive train model is proposed. The proposed speed controller provides stable closed loop system, zero tracking error, low-frequency disturbance rejection, and open-loop gain attenuation at the resonant frequency. At the end, performance of the proposed controller is investigated by the time domain simulations.     

A robust hybrid current control for permanent-magnet synchronous motor drive

Recently, the permanent-magnet synchronous motor (PMSM) has found widespread utilization in modern adjustable AC drives. This is achieved by using current-controlled voltage source inverter (VSI) systems. Because of its ease of implementation, fast current control response and inherent peak current-limiting capability, hysteresis current control is considered as the simplest technique used to control the motor currents for an AC machine. On the other hand, the ramp comparator controller has some advantages, such as limiting maximum inverter switching frequency to the carrier triangular waveform frequency and producing well-defined harmonics. In order to take advantage of the position features of both these two controllers, this paper presents the design and software implementation of a hybrid current controller. The proposed intelligent controller is a simultaneous combination and contribution of the hysteresis current controller and the ramp comparator. Comparisons using simulations on a 0.9-kW PMSM confirm that the proposed hybrid current controller gives better performance and has the advantage of conceptual simplicity. In particular, harmonic spectra of the stator current, obtained using a fast Fourier transform (FFT), are used for comparison purposes.     

Comparative study of various artificial intelligence approaches applied to direct torque control of induction motor drives

In this paper, three intelligent approaches were proposed, applied to direct torque control (DTC) of induction motor drive to replace conventional hysteresis comparators and selection table, namely fuzzy logic, artificial neural network and adaptive neuro-fuzzy inference system (ANFIS). The simulated results obtained demonstrate the feasibility of the adaptive network-based fuzzy inference system based direct torque control (ANFIS-DTC). Compared with the classical direct torque control, fuzzy logic based direct torque control (FL-DTC), and neural networks based direct torque control (NN-DTC), the proposed ANFIS-based scheme optimizes the electromagnetic torque and stator flux ripples, and incurs much shorter execution times and hence the errors caused by control time delays are minimized. The validity of the proposed methods is confirmed by simulation results.     

Cogging torque reduction in axial-flux permanent magnet wind generators with yokeless and segmented armature by radially segmented and peripherally shifted magnet pieces

The inherent cogging torque component of the PM generators can cause problems at the start-up of wind turbines. To improve the operation of wind turbines, especially at low starting speeds, the wind generator cogging torque should be minimized. In this paper, an effective and practical approach is proposed for cogging torque reduction in the AFPM generators with yokeless and segmented armature (YASA). The proposed approach is based on the dividing magnets radially and shifting the magnet pieces peripherally with an appropriate shifting angle. Using a series of 3-D FEA simulations, the proposed approach is compared with the two conventional approaches, i.e. the magnet skewing approach and the selecting an appropriate magnet pole arc to pole pitch ratio, according to the cogging torque reduction and the negative impacts on the generator loadability. It is shown that using the proposed approach, the generator cogging torque can be greatly reduced (about 87%). Also, it is shown that compared with the other studied cogging torque reduction techniques, the proposed approach has less negative impact on the generator loadability. Some of the simulation results are verified using the experimental tests.     

Electromagnetic design and optimization of dual‐stator brushless doubly‐fed wind power generator with cage‐barrier rotor

This paper explores the feasibility of an intuitive solution torque density for the existing brushless doubly‐fed generator by dual‐stator and cage‐barrier rotor structure, so as to better adapt to the offshore wind power generation. The torque density of electrical machine is related to the key design parameters, such as the machine main dimensions, slot‐pole combinations, coupling between stator and rotor, and nonmagnetic ring thickness. According to working principles and design requirements of electrical machine, the dual‐stator brushless doubly‐fed wind power generator (DSBDFWPG) with cage‐barrier rotor is designed, and the key parameters relating to torque density are analyzed and discussed. Meanwhile, the main parameters of electrical machine are optimized by Taguchi method, such as air‐gap length and nonmagnetic ring thickness. On this basis, the performance parameters of DSBDFWPG are analyzed by finite element method, which is verified by experimental tests. Through analysis of the results, not only the design requirements are satisfied by the DSBDFWPG, but also the correctness and rationality of machine design method can also be verified. Finally, the torque density and other aspects of designed DSBDFWPG are compared with dual‐stator brushless doubly‐fed induction generator, doubly‐fed induction generator, asynchronous machine, and brushless doubly‐fed generator; it demonstrates the torque density improvement of the studied machine with its significance and value.     

A robust control method for a PV-supplied DC motor using universal learning networks

In this paper, a new robust control method and its application to a photovoltaic (PV) supplied, separately excited DC motor loaded with a constant torque is discussed. The robust controller is designed against the load torque changes by using the first and second ordered derivatives of the universal learning networks (ULNs). These derivatives are calculated using the forward propagation algorithm, which is considered as an extended version of real time recurrent learning (RTRL). In this application, two ULNs are used: The first is the ULN identifier trained offline to emulate the dynamic performance of the DC motor system. The second is the ULN controller, which is trained online not only to make the motor speed follow a selected reference signal, but also to make the overall system operate at the maximum power point of the PV source. To investigate the effectiveness of the proposed robust control method, the simulation is carried out at four different values of the robustness coefficient γ in two different stages: The training stage, in which the simulation is done for a constant load torque. And the control stage, in which the controller performance is obtained when the load torque is changed. The simulation results showed that the robustness of the control system is improved although the motor load torque at the control stage is different from that at the training stage.