基于高频电压注入法的永磁同步电机转子初始位置检测

为了解决新型无位置传感器永磁同步电机的起动问题,提出了一种在电机静止状念下检测转子位置的新方法。该方法在算法上改进了传统的旋转高频电压注入法,使得可以更为快速、准确的检测出转子初始d轴位置。并且针对传统旋转高频电压注入法无法检洲出转子永磁体极性问题,在dq旋转坐标系下,通过分析永磁同步电机d轴磁链和定子电流之间的关系,利用d轴电流的泰勒级数展开,提出了根据定子铁芯非线性磁化特性获得判别N/S极极性信息的新方案。最后,建立了系统仿真模型。仿真结果验证了这种方法的有效性和可行性。此方法同样适用于永磁同步电机在中、低速时的转子位置检测。     

电机转子初始位置检测新方法研究

针对转子磁钢内埋式永磁同步电动机(PMSM)无速度传感器控制系统,提出一种新型转子初始位置检测方法。该方法通过注入高频旋转电压,在定子绕组中产生包含转子空间位置信息的高频电流。与传统高频注入法不同的是,采用离散傅里叶变换(DFT)对高频电流进行解调。避免了传统外差法解调时使用大量滤波器造成信号相位延迟,同时该方法与注入信号初始相位无关,相比于外差法,提取出的转子位置角度更精确,而且结构简单非常适用于数字系统。仿真和基于dSPACE实验平台上验证了该方法的有效性与可行性。     

无刷电机转子状态的无位置传感器检测方法

在无刷电机控制系统中,经常使用位置传感器对电机转子状态进行检测.而无位置传感器检测法可以简化电机控制系统的结构,提高系统的可靠性.为解决此问题,将定子电流、转子转速和位置作为状态变量,利用扩展卡尔曼滤波器对电机转子的状态做出最小方差估计,从而实现无刷电机的无位置传感器检测.通过仿真实验证明了电机运行在高速和低速时此方法都能快速、准确地检测出转子的转速.     

无传感器交流传动技术的展望

在电机轴上无机械速度传感器的可控交流电机驱动，由于其低廉的价格和较高的可靠性，一直备受关注。为了取代传感器，它通过测量定子电流和电机端电压得到转子速度信息。矢量控制传动需要估计定子或转子磁通基波的大小和空间位置。为此需要使用开环估计器或闭环观测器，它们在准确性、鲁棒性以及对模型参数变化的敏感性等性能上均不相同。通过信号注入即利用电机的各向异性，可以获得零速范围附近的动态性能和稳态速度精度。本文使用复杂空间矢量的信号流程图来形象地描述交流电机无传感器的控制系统。     

无传感器永磁同步电机的位置辨识与控制研究

永磁同步电机由于自身以永磁体提供励磁,结构较为简单,在工业上被广泛应用。在当前永磁同步电机的矢量控制系统中,最为必要的条件就是需要准确获取电机转子的位置信号,以往通常会利用传感器技术的优势通过传感器的信号变化来判断电机的转子位置信息,但是在有些复杂的工业生产环境却不适合传感器的应用,例如高温、腐蚀性较强的环境就会对传感器的测量或者传感器本身造成很大的影响。本文主要介绍了滑模变结构理论,并在滑模变结构控制的基础上,通过监测电动机的反电势来判断转子的位置;此外,引入了脉振高频电压注入法实现永磁同步电动机无传感器的位置辨识与控制。     

基于EKF的异步电机直接转矩控制系统仿真研究

为了提高直接转矩控制(DTC)系统定子磁链估计精度,降低电流、电压测量的随机误差,提出了一种基于扩展卡尔曼滤波(EKF)实现异步电机转子位置和速度估计的方法.扩展卡尔曼滤波器是建立在基于旋转坐标系下由定子电流、电压、转子转速和其它电机参量所构成的电机模型上,将定子电流、定子磁链、转速和转子角位置作为状态变量,定子电压为输入变量,定子电流为输出变量,通过对磁链和转速的闭环控制提高定子磁链的估计精度,实现了异步电机的无速度传感器直接转矩控制策略,仿真结果验证了该方法的可行性,提高了直接转矩的控制性能.     

基于自适应模糊滑模的PMSM无速度传感控制研究

为研究永磁同步电机（PMSM）在无速度传感器工况下的速度跟踪估计,以PMSM的工作原理为基础,建立了内埋式PMSM的数学模型。利用自适应模糊微分积分滑模鲁棒性强的优点,提出了在自适应模糊微分积分滑模控制条件下采用旋转高频电压注入法对电机转速估计的无速度传感器控制方案,并分析了电机在高低速运行时特点。仿真结果表明,采用高频注入法的自适应模糊微分积分滑模控制系统在高、低速工况下运行时稳定可靠,并具有较好的鲁棒性,能够实现速度跟踪估计。     

永磁同步电机矢量控制系统的EKF无传感器控制策略

介绍了一种基于扩展卡尔曼滤波的永磁同步电机无传感器转子位置与速度估算方法,并以此为基础实现了永磁同步电机的无传感器矢量控制系统。通过测量流过电机定子电流和电机端电压在线估计电机转子的位置和速度,实现永磁同步电机的无传感器控制策略。仿真和实验结果验证了该方案的可行性及有效性。     

基于扩展滑膜控制器的PMSM无速度传感器研究

本文设计了一种基于永磁同步电机（PMSM）直接转矩控制（DTC）的扩展滑膜观测器,通过测量定子电压与电流,获得电机的转速和转子位置。MATLAB仿真结果表明,扩展的滑膜观测器在空间矢量电压直接转矩控制（SVPWM-DTC）中,所得转速更接近实际转速。     

无轴承开关磁阻电机无位移传感器运行研究

无轴承开关磁阻电机具有体积小,无磨损,效率高,功耗低等优点,但机械式传感器限制了电机固有高速性能的发挥。因此,文中研究了一种基于高频电压信号注入的无径向位移传感器控制方法,并建立了基于此算法的电机转子径向位移预测模型,实现无轴承开关磁阻电机无位移传感器稳定悬浮运行。最后,通过仿真和实验分析对所提方法进行了验证。结果表明,所设计控制策略能够正确估计出单绕组无轴承开关磁阻电机的转子径向位移,且系统具有较好的动态响应能力。     

Sensorless position control of induction motors-an emergingtechnology

Concepts for the sensorless position control of induction motor drives rely on anisotropic properties of the machine rotor. Such anisotropies can be incorporated as periodic variations of magnetic saliencies in various ways. The built-in spatial anisotropy is detected by injecting a high-frequency flux wave into the stator. The resulting stator current harmonics contain frequency components that depend on the rotor position. Models of the rotor saliency serve to extract the rotor position signal using phase-locked loop techniques. A different approach makes use of the parasitic effects that originate from the discrete winding structure of a cage rotor. It has the merit of providing high spatial resolution for incremental positioning without sensor. The practical implementation of sensorless position identification and of a high-accuracy position control system are reported     

Implementation and experimental investigation of sensorless speed control with initial rotor position estimation for interior permanent magnet synchronous motor drive

In this paper, a new approach to sensorless speed control and initial rotor position estimation for interior permanent magnet synchronous motor (IPMSM) drive is presented. In rotating condition, speed and rotor position estimation of IPMSM drive are obtained through an extended Kalman filter (EKF) algorithm simply by measurement of the stator line voltages and currents. The main difficulty in developing an EKF for IPMSM is the complexity of the dynamic model expressed in the stationary coordinate system. This model is more complex than that of the surface PMSM, because of the asymmetry of the magnetic circuit. The starting procedure is a problem under sensorless drives, because no information is available before starting. The initial rotor position is estimated by a suitable sequence of voltage pulses intermittently applied to the stator windings at standstill and the measurement of the peak current values of the current leads to the rotor position. Magnetic saturation effect on the saliency is used to distinguish the north magnetic pole from the south. To illustrate our work, we present experimental results for an IPMSM obtained on a floating point digital signal processor (DSP) TMS320C31/40 MHz based control system.     

Sensorless speed control of nonsalient permanent-magnet synchronous motor using rotor-position-tracking PI controller

This paper presents a new velocity estimation strategy of a nonsalient permanent-magnet synchronous motor (PMSM) drive without a high-frequency signal injection or special pulsewidth-modulation (PWM) pattern. This approach is based on the d-axis current regulator output voltage of the drive system that has the information of rotor position error. Rotor velocity can be estimated through a rotor-position-tracking proportional-integral (PI) controller that controls the position error to zero. For zero and low-speed operation, the PI controller gains of rotor position tracking controller have a variable structure according to the estimated rotor velocity. In order to boost the bandwidth of the PI controller around zero speed, a loop recovery technique is applied to the control system. The proposed method only requires the flux linkage of the permanent magnet and is insensitive to parameter estimation error and variation. The designers can easily determine the possible operating range with a desired bandwidth and perform vector control even at low speeds. The experimental results show the satisfactory operation of the proposed sensorless algorithm under rated load conditions.     

Online rotor resistance estimation using the transient state underthe speed sensorless control of induction motor

In the speed sensorless control of the induction motor, the machine parameters (especially rotor resistance R₂) have a strong influence on the speed estimation. It is known that the simultaneous estimation of the rotor speed and R₂ is impossible in the slip frequency type vector control, because the rotor flux is constant. But the rotor flux is not always constant in the speed transient state. In this paper, the R₂ estimation in the transient state without signal injection to the stator current is proposed. This algorithm uses the least mean square algorithm and the adaptive algorithm, and it is possible to estimate R₂ exactly. This algorithm is verified by the digital simulations and experiments     

A high-performance sensorless indirect stator flux orientation control of induction motor drive

A new method for the implementation of a sensorless indirect stator-flux-oriented control (ISFOC) of induction motor drives with stator resistance tuning is proposed in this paper. The proposed method for the estimation of speed and stator resistance is based only on measurement of stator currents. The error of the measured q-axis current from its reference value feeds the proportional plus integral (PI) controller, the output of which is the estimated slip frequency. It is subtracted from the synchronous angular frequency, which is obtained from the output integral plus proportional (IP) rotor speed controller, to have the estimated rotor speed. For current regulation, this paper proposes a conventional PI controller with feedforward compensation terms in the synchronous frame. Owing to its advantages, an IP controller is used for rotor speed regulation. Stator resistance updating is based on the measured and reference d-axis stator current of an induction motor on d-q frame synchronously rotating with the stator flux vector. Experimental results for a 3-kW induction motor are presented and analyzed by using a dSpace system with DS1102 controller board based on the digital signal processor (DSP) TMS320C31. Digital simulation and experimental results are presented to show the improvement in performance of the proposed method.     

A sensorless initial rotor position estimation scheme for a direct torque controlled interior permanent magnet synchronous motor drive

In direct torque control (DTC) scheme, the requirement of the continuous rotor position sensor and coordinate transformation is eliminated since all the calculation is done in stator reference frame. However, the DTC scheme requires the position sensor to determine the initial position of the rotor at starting. Elimination of the shaft-mounted position encoder is a very desirable objective in many applications since this sensor is often one of the most expensive and fragile components in the entire drive system. This paper presents a sensorless method of determining the initial rotor position of a direct torque controlled interior permanent magnet (IPM) synchronous motor drive. The method consists of injecting a high frequency voltage to the windings and examining the effects of the saliency on the amplitude of the corresponding stator current components. This method does not depend on the level of static load and on any motor parameters. The magnet polarity of the rotor at its initial position is also identified using the effect of saliency. Modeling and experimental results verify the effectiveness of the proposed method.     

Observer using low-frequency injection for sensorless induction motor Control-parameter sensitivity analysis

The zero-frequency vector control of an induction motor without a speed sensor has proven to be a very difficult task. Uncertainty and variation in the electrical parameters of the motor deteriorate the performance of fundamental-wave flux observers as the frequency approaches zero, and observers based on high-frequency signal injection rely on motor-specific phenomena. A new method has recently been proposed, where a low-frequency current signal is injected in the estimated rotor flux direction. If there is an error in the orientation, the signal gives rise to a torque oscillation and affects the back electromotive force (EMF) through the mechanical system. The phenomenon makes it possible to reach sensorless zero-frequency operation. This paper shows that the method is insensitive to the variation of the motor parameters. Experiments confirm the result.     

Design and implementation of the extended Kalman filter for thespeed and rotor position estimation of brushless DC motor

A method for speed and rotor position estimation of a brushless DC motor (BLDCM) is presented in this paper. An extended Kalman filter (EKF) is employed to estimate the motor state variables by only using measurements of the stator fine voltages and currents. When applying the EKF, it was necessary to solve some specific problems related to the voltage and current waveforms of the BLDCM. During the estimation procedure, the voltage- and current-measuring signals are not filtered, which is otherwise usually done when applying similar methods. The voltage average value during the sampling interval is obtained by combining measurements and calculations, owing to the application of the predictive current controller which is based on the mathematical model of motor. Two variants of the estimation algorithm are considered: (1) speed and rotor position are estimated with constant motor parameters and (2) the stator resistance is estimated simultaneously with motor state variables. In order to verify the estimation results, the laboratory setup has been constructed using a motor with ratings of 1.5 kW, 2000 r/min, fed by an insulated gate bipolar transistor inverter. The speed and current controls, as well as the estimation algorithm, have been implemented by a digital signal processor (TMS320C50). The experimental results show that is possible to estimate the speed and rotor position of the BLDCM with sufficient accuracy in both steady-state and dynamic operation. Introducing the estimation of the stator resistance, the speed estimation accuracy is increased, particularly at low speeds. At the end of the paper, the characteristics of the sensorless drive are analyzed. A sensorless speed control system has been achieved with maximum steady-state error between reference and actual motor speed of ±1% at speeds above 5% of the rated value     

Sensorless control of salient PMSM with adaptive integrator and resistance online identification using strong tracking filter

This article presents a sensorless control approach of salient PMSM with an online parameter identifier. Adaptive Integrator is proposed and utilised for the estimation of active flux and rotor position. As a result, integrator overflow caused by DC offset is avoided. Meanwhile, an online stator resistance identification algorithm using strong tracking filter is employed, and the identified stator resistance is fed back to the estimating algorithm. Thus, the estimating algorithm can calculate the rotor position correctly. Simulations and experimental results validate the feasibility of both adaptive integrator and the parameter identification method.