基于RBF神经网络的开关磁阻电机瞬时转矩控制

开关磁阻电机(SRM)因其结构简单、工作可靠、效率高、成本低等优点使之成为当前极具竞争力的一种调速电动机。但由于电机本身的非线性电磁特性,导致了其转矩脉动比其他传动系统严重。如何更好地对开关磁阻电机的转矩进行控制,抑制转矩脉动也成为了近年来研究的热点。针对这一问题,提出了一种基于基于径向基函数(radial basis function,RBF)神经网络的开关磁阻电机瞬时转矩控制方法。利用从SRM动态模型仿真中产生的数据来对RBF神经网络进行离线训练,使之学习不同转速和转矩下的优化电流波形,再将训练好的RBF网络用于电机的转矩控制中,完成不同转速下,转矩、位置到电流的非线性映射。最后通过瞬时电流跟踪控制使电机电流跟踪参考电流,完成电机的转矩控制。该控制方法充分利用了RBF神经网络逼近、泛化能力强,运算速度快的优点,且控制过程简单,网络无需在线训练。实验结果证明,该控制策略能有效减小开关磁阻电机的转矩脉动,具有控制精度高、能适应转速变化等优点。     

An automatic torque ripple compensation system for direct drive motors

A serious problem in motion control is the occurrence of torque ripple. Since a direct drive (DD) motor with a magnet rotor uses a rare-earth magnet, the torque ripple is more serious than that of conventional servomotors. This paper presents an auto-compensation of torque ripple using a software-implemented torque observer. The frequency and amplitude of torque ripple can be obtained in the controller by using the estimated torque from an observer, and the autonomous generation of a compensating current component for a torque ripple is possible. The proposed algorithm has been verified by experiments.     

多单元永磁同步电机数学模型与转矩波动抑制

为了提升永磁同步电机整机输出功率,同时降低每相绕组的电压、电流等级,通常采用多相或多单元设计.以一台五单元直驱式低速大扭矩永磁同步电动机为对象,建立了多单元永磁同步电机的电压、转矩方程.在部分单元电机容错运行时,采用磁共能法推导出单元电机不同数量、位置时的转矩波动解析表达式,并给出采用注入3次谐波电流抑制转矩波动的方法.数值分析和试验结果表明,所建立的多单元电机数学模型准确,转矩波动抑制方法有效,在部分单元电机额定状态运行时,转矩波动最多可降低3.5％,该数学模型和转矩波动公式及其抑制方法均可有条件推广至不同单元数量的电机分析之中.     

一种恒定开关频率感应电机直接转矩控制

在感应电机I(M)的直接转矩控制(DTC)中,为了提高定子磁链观测的准确性,引入一种结合常规电压模型法和电流模型法优点的混合定子磁链观测模型代替常用的电压模型来观测磁链。针对传统开关表-滞环DTC中开关频率变化大和转矩脉动大的缺点,提出一种具有恒定开关频率控制的DTC策略,使其在定子磁链旋转坐标系内,利用空间电压矢量调制技术合成电压矢量,以实时准确补偿当前定子磁链与转矩误差,从而有效降低了电机运行中的转矩脉动和电流畸变。最后,通过仿真和实验验证了方案的可行性。     

模糊自适应控制在永磁同步电机直接转矩控制的应用

提出了一种新的永磁同步电机直接转矩控制方法。永磁同步电机直接转矩控制中,没有任何一个逆变器开关矢量能够产生恰好的定子电压,使该电压可以产生所期望的转矩和磁通变化,因而产生了较大的转矩和磁通脉动,并且逆变器的开关周期不恒定。这种脉动通过控制正反电压矢量作用时间可以降低,提出了一种自适应模糊控制器确定占空比的方法。该控制器输出部分的比例因子可以根据转矩的变化趋势经自适应机构的模糊规则库在线调整,不仅可以使永磁同步电机直接转矩控制系统保持恒定的开关频率,而且可以有效地减小磁链和转矩脉动,特别是低速时的转矩脉动。仿真验证了自适应模糊永磁同步电机直接转矩控制策略的有效性。     

A three-phase switched reluctance motor with two-phase excitation

A new excitation strategy for a switched reluctance motor (SRM) is described and tested. This scheme excites two phases of an SRM simultaneously, which is similar to the two-phase excitation method of a step motor. In this scheme, the torque is produced by mutual-inductance as well as by self-inductance. The abrupt change of a phase excitation produces mechanical stresses, resulting in torque ripple and noise. The acoustic noise is reduced through a sequential two-phase excitation. Noise reduction occurs because the scheme reduces abrupt changes in excitation levels by distributed, balanced excitation and freewheeling during commutation. The operational principle and a characteristic comparison to that of the conventional SRM show that this novel excitation scheme has some advantages, including torque ripple and noise reduction, as well as simple inverter topology     

An Iterative Learning-Based Modulation Scheme for Torque Control in Switched Reluctance Motors

This paper deals with an iterative learning approach for modulating the desired torque profile so as to obtain ripple-free torque in switched reluctance motors. Because of the highly nonlinear relation between torque, current, and rotor position for this motor, it is not possible to obtain a closed-form mathematical expression for current as a function of torque and rotor position. Thus, the current waveforms are conventionally computed by using the linear torque model of the motor, and it is well known that such a scheme results in high torque ripple. In this paper, a novel method is proposed to minimize the ripple. In this new scheme, the current is still computed using the linear torque model, but the value of the torque used for this is not the desired (specified) torque, but rather a modulated-desired torque that is obtained by repeated corrections to the desired torque from iteration to iteration. The conventional rectangular pulse profile is taken as the initial current waveform. The method requires much less a priori knowledge of the magnetic characteristics of the motor. The algorithms have been formulated for both one-phase-on and two-phase-on schemes, for a four-phase switched reluctance motor, in the light of the principles behind iterative learning. Based on the observations from the simulation results of these schemes, a modified scheme has been proposed by incorporating a suitable commutation process, often called torque sharing functions, in order to generate reasonably smooth current waveforms for the ease of tracking by the stator circuit of the motor. The performances of all the proposed schemes have been verified by computer simulation.     

Direct torque control of permanent magnet drives

Many permanent magnet motor drives use an open loop form of torque control, based on the assumption that output torque is proportional to applied current. In a practical motor this assumption may not always be correct, due to suboptimal alignment of magnets, nonuniformity of magnetic material, current sensor nonlinearities, and current controller limitations. These factors, together with nonoptimized current references, can lead to undesirable levels of torque ripple and copper loss. This paper describes a method of estimating the electromagnetic torque from the rate of change of coenergy with respect to position, thus taking account of mutual torque, reluctance torque and saturation effects. The paper shows how the estimator can be used in a direct torque control scheme. The direct torque controller maximizes the torque:copper loss ratio. Implementation of the direct torque controller in a digital signal processor (DSP)-based drive system is described, with steady-state and transient experimental results illustrating the effectiveness of the direct torque control scheme     

Smart bacterial foraging algorithm based controller for speed control of switched reluctance motor drives

In this paper, a innovative methodology for Switched Reluctance Motor (SRM) drive control using Smart Bacterial Foraging Algorithm (SBFA) is presented. This method mimics the chemotactic behavior of the E. Coli bacteria for optimization. The proposed algorithm uses individual and social intelligences, so that it can search responses among local optimums of the problem adaptively. This method is used to tune the coefficients of a conventional Proportion–Integration (PI) speed controller for SRM drives with consideration of torque ripple reduction. This matter is done by applying the proposed algorithm to a multi-objective function including both speed error and torque ripple. This drive is implemented using a DSP-based (TMS320F2812) for an 8/6, 4-kW SRM. The simulation and experimental results confirm the improved performance of adjusted PI controller using SBFA in comparison with adjusted PI controller using standard BFA. Excellent dynamic performance, reduced torque ripple and current oscillation can be achieved when the coefficients of PI controller are optimized by using SBFA.     

Studies of torque ripple in a switched reluctance motor under a controlled average torque value in a low-velocity mode

In the case of adjusting the average torque value of switched reluctance motors, torque ripple is most pronounced in a low-velocity mode. In this mode, the motor phase-currents are usually forcibly limited; therefore, owing to the available voltage margin, by properly selecting the positions of phase switching, one can influence the shape of the phase-currents within certain limits and, thereby, achieve a decrease in the torque ripple. This paper considers the possibilities of reducing torque ripple using very common methods for restricting the phase-current, such as voltage control and current control. Using simulation modeling in the Matlab–Simulink environment, the best combinations of control actions are found, with which torque ripple is minimal. It is shown that, by using the first method of phase-current restriction, the reduction in torque ripple under certain conditions is achieved via a forced pulling of the range of phase-current increase due to a later switching on of the phase with a simultaneous increase in the voltage across this phase. In a number of cases, the desired effect can be achieved only owing to a certain delay in the command for switching the phase off with respect to the position corresponding to a single-switching mode. For the second method of phasecurrent restriction, the best switching conditions are found for fixed levels of current restriction determined from the desired values of the average motor torque, and independent adjusting of the switch-on and switchoff positions of its phases.     

开关磁阻电机直接瞬时转矩控制的优化研究

为改善开关磁阻电机(SRM)的转矩脉动和效率,提出了一种改进的SRM直接瞬时转矩控制(DITC)方法。该方法采用了灵活的转矩分配方式获得各相参考转矩,用来对瞬时转矩进行闭环控制;同时增加了角度优化方案,根据每相绕组导通期间的累积转矩误差、转速和参考转矩等变量,通过模糊算法实现电机开通角度的在线调整,动态的改善转矩误差和电机的效率。在MATLAB/Simulink软件中分别根据改进前后的DITC方法建立SRM控制系统仿真模型,仿真试验结果表明所提的优化方法能够达到较小的转矩误差和相电流,实现了电机的平稳、高效控制。     

四开关逆变器供电永磁同步电机直接转矩控制系统转矩脉动抑制

永磁同步电机直接转矩控制(PMSM DTC)系统的转矩脉动问题一直被广泛关注，特别是在四开关逆变器供电系统中，由于可用电压矢量减少，转矩脉动更加严重。空间矢量调制(SVM)是一种常用的消除电力谐波的调制技术，更可用于电机控制中转矩脉动的削减。该文针对四开关逆变器供电PMSM DTC系统的特殊性，采用了一种新型SVM方法，分析了等效零矢量模拟技术，将传统SVPWM调制中的劈零思想引入到空间矢量的合成上。仿真及实验结果验证了该新型SVM DTC方法大大减小了转矩脉动，且仍保持了DTC系统固有的快速转矩动态响应。     

基于在线模糊神经网络建模的开关磁阻电机高性能转矩控制

针对开关磁阻电机(SRM)的转矩脉动问题,提出了一种新的SRM转矩控制方案。首先应用自适应模糊神经网络(ANFIS)对SRM静态转矩逆模型和磁链模型进行离线学习,然后根据转矩分配函数对各相转矩进行分配,利用ANFIS转矩逆模型求出期望转矩下的SRM优化相电流波形。考虑到离线模型的局限性和实时运行时电机中存在的参数变化等不确定因素,通过在线监督学习的方法调整ANFIS转矩逆模型和磁链模型的参数以提高模型的准确性。基于在线调整的ANFIS磁链模型设计自适应滑模控制器调节SRM相绕组中的实际电流跟踪期望相电流波形,从而实现其高性能转矩控制。     

基于母线电流控制的直流无刷电动机转矩脉动抑制方法研究

针对方波直流无刷电动机转矩脉动控制问题进行了讨论,分析了低速和高速情形下直流无刷电动机转矩脉动抑制的方法,提出基于母线电流控制的直流无刷电动机转矩脉动抑制的方法,仿真结果证明该控制系统能有效地减小转矩脉动.     

Single-Phase SRM Drive With Torque Ripple Reduction and Power Factor Correction

In a single-phase switched reluctance motor (SRM) drive, the dc voltage source is generally supplied by a circuit consisting of a bridge rectifier and a filter capacitor connected to an ac line. The charging time of the capacitor is shorter from the ac source as capacity increases. The bridge rectifier draws pulsating current from the ac source, which results in a degraded power factor (PF) and lower system efficiency. A single-phase SRM drive system is presented in this paper, which includes the realization of a drive circuit for the reduction of torque ripple and PF improvement with a novel switching topology. The proposed drive circuit adds one switch and one diode, which can separate the output of the ac/dc rectifier from the large capacitor and supply power to the SRM alternately. This allows the drive system to realize torque ripple reduction and PF improvement through the switching scheme. The validity of the proposed method is analyzed by mathematical modeling and tested by simulations and experiments.     

基于Buck变换器的无刷直流电机转矩控制仿真

无刷直流电动机（BLDCM）存在转矩脉动的突出缺点，提出了一种基于直流环节电压控制和模糊PID控制器的新型混合控制策略，以抑制无刷直流电机的转矩脉。电路拓扑包含功率因数校正降压转换器和逆变器。降压转换器通过控制直流电路电压来降低换向转矩脉动，使用模糊PID控制器和脉冲宽度调制（PWM）技术的逆变器在导通区域提供适当的电流。 Buck变换器降低了通过控制直流环节电压换向转矩脉动，逆变器使用模糊PID和PWM技术提供导通区域的电流。该方法能够消除传导区转矩脉动,削弱换相区转矩脉动，仿真结果表明，该策略具有功率因数校正功能，可有效抑制转矩脉动，提升电机运行的鲁棒性。     

永磁同步电机有限集模型预测直接转矩控制

针对永磁同步电机(PMSM)模型预测直接转矩控制(DTC)转矩脉动大、功率元件开关频率不恒定等问题,将两电平逆变器的8个电压空间矢量作为有限控制集,应用到PMSM DTC中。设计考虑转矩误差、最大转矩电流比及电流约束的成本函数,利用成本函数来估算有限集合中各电压矢量的占空比,从而求得逆变器的最优电压矢量作为系统控制量。与传统模型预测控制方法相比,该方法的电流谐波和转矩脉动显著降低,且转矩动态性能也得到改善。仿真试验结果验证了所提出的控制方案有效性。     

一种基于电流反馈的分段式PWM控制无刷直流电机转矩波动抑制方法

无刷直流电机伺服系统具有广泛的应用场合,但转矩波动限制了其在高精度场合的应用。针对非理想反电动势引起的无刷直流电机转矩波动提出了一种基于电流反馈的分段式PWM控制方法。该方法通过线反电动势观测器获得产生目标转矩值的参考电流,以实现对电机转矩的直接控制。同时,针对电机高速与低速运行状态分别采用不同的PWM控制策略来有效消除换相转矩波动,系统具有低转矩波动和高转矩输出的特点。通过在Matlab/Simulink环境下建立系统仿真模型,对该控制方法的转矩直接控制能力进行检验,并对转矩波动进行了对比;搭建实验平台对具有非理想反电动势的无刷直流电机进行了驱动实验。仿真和实验结果表明,该文所提出的控制方法能有效减小转矩波动,提高无刷直流电机伺服系统输出转矩的稳定性和位置控制精确度。     

无刷直流电机转矩波动降低的电流控制方法

当电枢电流换向时,无刷直流电机定子绕组的电感和反电势导致电流的波动,从而导致了转矩的波动。文中提出应用傅立叶级数系数的电流控制算法,能明显减少转矩波动。     

永磁同步电机转矩脉动抑制方法

分数槽集中绕组永磁同步电机被广泛用于伺服控制系统。由于电机极槽配合以及制造过程中机械加工与装配误差等因素,所以永磁同步伺服电机输出转矩中会存在固有的周期性转矩脉动,影响伺服系统实现高精度的速度与位置跟随。因此,采用转矩观测器来估计由上述原因造成的转矩脉动,再将转矩脉动与位置信号通过一定处理,计算出相应的前馈转矩电流,补偿到电流指令端,对转矩脉动进行抑制,从而减小转速脉动。通过仿真和试验验证了抑制方法的有效性。