Mechanical sensorless speed control of permanent-magnet AC motors driving an unknown load

A new sensorless scheme for high-performance speed control of permanent-magnet ac motors (PMACMs) driving an unknown load is proposed. This scheme uses an extended nonlinear reduced-order observer to estimate the induced electromotive force (EMF) and load torque. From the estimated variables, the rotor position, the rotor speed, and the position derivative of flux are calculated and are used to close the control loop. In order to improve the drive performance, the estimated load torque is incorporated as a feedforward signal in the closed control loop. In addition, the proposed sensorless PMACM drive allows the torque-ripple and copper-loss minimization for motors with an arbitrary EMF waveform. Simulation and experimental results to validate the proposal are presented in this paper.     

Sensorless control of induction Machines at zero and low frequency using zero sequence currents

This paper considers both flux and rotor position estimations for sensorless control of delta-connected cage induction machines (IMs) at low and zero frequency operation. The variation of leakage inductance due to either saturation or rotor slotting is tracked by measuring the derivative of the zero sequence current in response to the application of appropriate voltage test vectors. The method requires only a single extra sensor. It requires access to machine phase windings and is appropriate for integrated-type induction motor drives. Both a closed-slot and an open-slot machine is used to demonstrate rotor flux and rotor position tracking, respectively. Experimental results are presented showing sensorless torque control and sensorless speed and position control at low and zero frequencies.     

Sensorless vector control of synchronous reluctance motors withdisturbance torque observer

The elimination of the position sensor has been one important requirement in vector control systems because the position sensor spoils the reliability and simplicity of drive systems. Therefore, we present a sensorless vector control technique for synchronous reluctance motors. The rotor position is calculated easily from ds-qs-axes flux linkages which are estimated with a first-order lag compensator. Furthermore, utilizing estimated rotor position as the input of the full-order observer, the rotor speed and disturbance torque are estimated. The proposed sensorless vector control scheme is demonstrated with experimental results     

Four-quadrant position sensorless control in SRM drives over the entire speed range

Proper synchronization of the excitation with respect to the rotor position is essential in optimal control of switched reluctance motor (SRM) drives. To avoid additional cost, size, and unreliability caused by the external position sensors, magnetic status of the SRM can be directly monitored to detect commutation instants. A one-to-one correspondence between magnetic status of the SRM and rotor position removes the need for an explicit access to the rotor position. In order to obtain a good precision over the entire speed range, educated modifications on the structure of the sensorless strategy is necessary. This is due to the impact of the operational regions on dynamic behavior of the SRM. In addition, introduction of SRM technology to industrial and domestic applications has raised the need for four-quadrant operation of the SRM drives. The present paper introduces a range of strategies that are necessary to accommodate this requirement in a sensorless format. Our experimental findings indicate that high-grade sensorless operation in a four-quadrant SRM drive is possible and can be integrated in a variety of applications.     

An approach for sensorless position estimation for switchedreluctance motors using artifical neural networks

This paper presents a new approach to the sensorless control of the switched-reluctance motor (SRM). The basic premise of the method is that an artificial neural network (ANN) forms a very efficient mapping structure for the nonlinear SRM. Through measurement of the phase flux linkages and phase currents the neural network is able to estimate the rotor position, thereby facilitating elimination of the rotor position sensor. The ANN training data set is comprised of magnetization data for the SRM with flux linkage (λ) and current (i) as inputs and the corresponding position (&thetas;) as output in this set. Given a sufficiently large training data set, the ANN can build up a correlation among λ, i and &thetas; for an appropriate network architecture. This paper presents the development, implementation, and operation of an ANN-based position estimator for a three-phase SRM     

An improved sensorless driving method for SRM using a phase-shift circuit technique

This paper presents an improved sensorless driving method for switched reluctance motor (SRM) using a phase-shift circuit technique. The conventional method consists of impressing short voltage pulses during unenergized phases, measuring the phase current pulses, and finding the correlation between the filtered current signals and rotor position. However, the filtering process causes a signal phase delay which varies with motor speed. This delay must be compensated for in providing the sensorless signal which is proper to the rotor position. A solution for this phase delay compensation, based on a simple analog and digital circuit, is proposed in this paper.     

Advanced simulation model for IPM motor drive with considering phase voltage and stator inductance

This paper proposes an advanced simulation model of driving system for Interior Permanent Magnet (IPM) BrushLess Direct Current (BLDC) motors driven by 120-degree conduction method (two-phase conduction method, TPCM) that is widely used for sensorless control of BLDC motors. BLDC motors can be classified as SPM (Surface mounted Permanent Magnet) and IPM motors. Simulation model of driving system with SPM motors is simple due to the constant stator inductance regardless of the rotor position. Simulation models of SPM motor driving system have been proposed in many researches. On the other hand, simulation models for IPM driving system by graphic-based simulation tool such as Matlab/Simulink have not been proposed. Simulation study about driving system of IPMs with TPCM is complex because stator inductances of IPM vary with the rotor position, as permanent magnets are embedded in the rotor. To develop sensorless scheme or improve control performance, development of control algorithm through simulation study is essential, and the simulation model that accurately reflects the characteristic of IPM is required. Therefore, this paper presents the advanced simulation model of IPM driving system, which takes into account the unique characteristic of IPM due to the position-dependent inductances. The validity of the proposed simulation model is validated by comparison to experimental and simulation results using IPM with TPCM control scheme.     

Sensorless Control for a Switched Reluctance Wind Generator, Based on Current Slopes and Neural Networks

In this paper, the analysis, design, and implementation of a novel rotor position estimator for the control of variable-speed switched reluctance generators (SRGs) are presented. The rotor position is obtained using the unsaturated instantaneous inductance. This unsaturated inductance is estimated calculating the slope of the phase current and using a reduced-size neural network (NN) whose inputs are the average current and the saturated inductance. The proposed estimator requires less processing time than traditional methods and can be fully implemented using a low-cost DSP with very few additional analog/digital components. The rotor position estimator presented in this paper can be applied to a wind energy conversion system where the SRG is used as a variable-speed generator. This application is currently being studied because the SRG has well-known advantages such as robustness, low manufacturing cost, and good size-to-power ratio. Simulation and experimental results are presented using a 2.5-kW 8/6-SRG prototype.      

Accurate rotor position detection and sensorless control of SRM for super-high speed operation

Based on the general nonlinear magnetizing model (GNMM) from our previous research work, an improved method of detecting rotor position for sensorless control of SRMs in super-high speed operation has been developed. With minimum input data, the approximated GNMM is obtained and the rotor speed estimated. Then the rotor position is detected by the motion equation. To remove rotor position error, the proposed scheme updates the reference at critical points using the flux observation. Further, the GNMM is adaptively tuned based on the updated information. The improved rotor position detection method has been implemented by fully exploring the computation power of the modern DSP. Laboratory verification on different types of SRMs with sensorless control up to 20000 rpm is accomplished.     

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     

A novel, robust DSP-based indirect rotor position estimation for permanent magnet AC motors without rotor saliency

This paper proposes and implements a novel rotor position sensorless technique for PM AC motor drives, which allows acceleration from standstill and can operate under various practical operating conditions including transient speed changes. The technique developed here relies on the measurement of the phase voltages and currents of the motor. It uses the incremental values of flux linkage, and the back-EMF functions to estimate incremental rotor position. Using a phase-locked loop (PLL) algorithm, an internal closed-loop correction algorithm can correct rotor position estimation drift, which may be due to the motor parameter variations or measurement inaccuracies. The method is implemented in closed-loop using a digital signal processor (DSP), and details of the implementation are provided in the paper. To demonstrate accuracy, robustness and reliability of the position estimation scheme, the paper presents a number of real-time experimental results, including dynamic operating conditions.     

Sensorless field orientation control of induction machines based ona mutual MRAS scheme

A mutual model reference adaptive system (MRAS) is proposed to implement a position sensorless field-orientation control (FOC) of an induction machine. The reference model and adjustable model used in the mutual MRAS scheme are interchangeable. Therefore, it can be used to identify both rotor speed and the stator resistance of an induction machine. For the rotor speed estimation, one model is used as a reference model and another is the adjustable model. Pure integration and stator leakage inductance are removed from the reference model, resulting in robust performance in low and high speed ranges. For the stator resistance identification, the two models switch their roles. To further improve estimation accuracy of the rotor speed and stator resistance, a simple on-line rotor time constant identification is included. Computer simulations and experimental results are given to show its effectiveness     

Indirect torque control of switched reluctance motors using iterative learning control

This paper proposes the use of iterative learning control (ILC) in designing a torque controller for switched reluctance motors (SRMs). The demanded motor torque is first distributed among the phases using a torque-sharing function. Following that, the phase torque references are converted to phase current references by a torque-to-current converter and the inner current control loop tracks the phase current references. SRM torque is a highly nonlinear and coupled function of rotor position and phase current. Hence, the phase current references for a given demanded torque can not be obtained analytically. Assumption of linear magnetization characteristics results in an invertible torque function. However, the nominal phase current references obtained using this torque function will lead to some torque error as motor enters into magnetic saturation. For a constant demanded torque, the error in the phase current references will be periodic with rotor position. Hence, we propose to use ILC to add a compensation current to the nominal phase current references so that torque error is eliminated. Similarly, current tracking for the nonlinear and time-varying system is achieved by combining a simple P-type feedback controller with an ILC controller. The proposed scheme uses ILC to augment conventional feedback techniques and hence, has better dynamic performance than a scheme using only ILC. Experimental results of the proposed scheme for an 8/6 pole, 1-hp SRM show very good average as well as instantaneous torque control.     

Position control of a sensorless synchronous reluctance motor

This paper presents a novel position control for a sensorless synchronous reluctance drive system. By measuring the three-phase currents of the motor, a rotor position estimator is achieved. Then, a velocity estimator is derived from the estimated rotor position by using a state estimating technique. The estimated velocity tracks the real velocity well. Next, a robust position controller is designed to improve the transient and load disturbance responses. By using the proposed estimating techniques and control algorithm, a high-performance sensorless synchronous reluctance drive is obtained. A digital signal processor, TMS-320-C30, is used to execute the estimating and control algorithms. No hardware circuit or external signal is added as compared with the traditional drive system with an encoder or resolver. To evaluate the performance of the position control system, a moving table is connected with the drive system. The drive system can precisely control the moving table. Experimental results show that the proposed system has good performance. Several experimental results validate the theoretical analysis.     

An extended electromotive force model for sensorless control of interior permanent-magnet synchronous motors

During the last decade, many sensorless control methods have been proposed for surface permanent-magnet synchronous motors (SPMSMs) based on the estimation of electromotive force (EMF) in which the motor's position information is contained. However, these methods cannot be applied to interior PMSMs (IPMSMs) directly, because the position information is contained in not only the EMF, but also the inductance of stators. In this paper, a new mathematical model for IPMSMs is proposed and an extended EMF is defined, which includes both position information from the EMF and the stator inductance. By using the newly proposed model, sensorless controls proposed for SPMSMs can easily be applied to IPMSMs. As an example, a disturbance observer is studied and the experimental results show that the proposed method on the proposed model is very effective.     

Review of position-sensorless operation of brushless permanent-magnet machines

The operation of a brushless permanent-magnet machine requires rotor-position information, which is used to control the frequency and phase angle of the machine's winding currents. Sensorless techniques for estimating rotor position from measurements of voltage and current have been the subject of intensive research. This paper reviews the state of the art in these sensorless techniques, which are broadly classified into three types: motional electromotive force, inductance, and flux linkage.     

Position-sensorless control of surface-mount permanent-magnet AC(PMAC) motors at low speeds

A position-sensorless field-oriented control scheme for a surface-mount permanent-magnet AC (PMAC) motor is presented. A digital signal processor is used to implement the sensorless scheme. The PMAC stator is wound like that of a conventional three-phase induction motor. The coils of the motor are all brought out and it is possible to connect the motor in different configurations. Taps are also provided which are used for voltage measurements. By measuring the tap voltages, absolute position of the PMAC motor is estimated. The estimated position information is independent of the stator resistance, thus, this scheme is even applicable at low speeds. Results are presented to show the effectiveness of the new sensorless scheme     

PMSM无传感器初始位置检测及低速运行研究

目前,永磁同步电机(PMSM)无位置传感器运行研究受到广泛关注。文章采用一种基于高频方波信号注入的方法实现PMSM无位置传感器启动以及低速运行。首先详细分析了高频方波信号注入检测原理,然后对注入的高频方波信号以及电流采样模式进行了改进。在估计的两相旋转坐标系轴向注入频率等于逆变器开关频率的高频方波电压信号,通过巧妙的安排定子电流采样模式,根据检测到的定子电流并结合注入的方波电压信号即可获得转子位置信息;采用Luenberger观测器对转子位置信息进行观测,以获得较为平稳准确的电机转速和转子角度估计值;利用电机的磁路饱和特性,实现基于高频方波信号注入法的PMSM无位置传感器转子初始位置检测。所提出的改进方法不依赖于准确的电机参数,不需要使用任何滤波器,信号处理过程简单易实现。仿真结果验证了该方法的正确性。     

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.     

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。