A new induction motor drive based on the flux vector acceleration method

A novel control strategy for the induction motor drive, based on the field acceleration method, is presented. The torque is controlled through variations of the stator flux angular velocity. The stator flux is controlled by using a feedforward control scheme, with the stator flux reference vector adjusted so as to obtain the fixed rotor flux amplitude. The applied controller assures a fast torque response, low torque ripple in the steady state, and drive operation with a constant switching frequency. The algorithm includes the improved stator and rotor flux estimation that guarantees the stable drive operation in all operating conditions, even at low speeds. The experimental tests verify the performance of the proposed algorithm, proving that good behavior of the drive is achieved in the transient and steady-state operating conditions.     

Machine modeling and universal controller for vector-controlled induction motor drives

Developments of machine model and a universal controller for vector-controlled induction motor drives are presented in this paper. The machine representations associated with vector-control methods referring to various frames, including stator, rotor, and air-gap flux frames, can be derived simply by selecting different state variables; thereby clearly identifying the relationship between machine modeling and vector control. Moreover, a universal vector controller for induction motor drives fed by a voltage-controlled voltage source inverter is presented. It is shown in this paper that various vector controllers, including rotor flux-oriented controller, stator flux-oriented controller and air-gap flux-oriented controller, can be realized by simply changing few parameters. It is demonstrated by experimental results that the developed universal vector controller for various vector-control approaches can be implemented using the same hardware with a minor change to software associated with parameters; and thereby confirming the theoretical analysis.     

Preliminary Evaluation of a Megawatt-Class Low-Speed Axial Flux PMSM With Self-Magnetization Function of the Armature Coils

This paper presents an axial flux permanent magnet synchronous machine (PMSM) with a disk rotor between two stators, which are wound in a tooth-coil technology (a concentrate winding type with subunitary number of slots/pole/phase). This type of winding facilitates the magnetizing inductor function of stator coils. A potential magnetizing system can be envisioned by taking into account that the coil span and the slot pitch are practically identical, the number of tooth-coils and poles are almost the same, and that there are two rotor poles between four tooth-coils (two adjacent tooth-coils on each stator). Thus, a special magnetizing inductor is not required in order to magnetize, pair by pair, the permanent magnet (PM) rotor poles. The number of tooth-coils exceeds the number of rotor poles by one (Ns = 2p + 1). Some aspects of the average performance obtained in both modes of operation-machine and magnetizing inductor-are highlighted by digital simulation. A scale-down demonstrating model also confirmed the feasibility of the magnetizing inductor function of the stator.     

Stator and rotor resistance observers for induction motor drive using fuzzy logic and artificial neural networks

This paper presents a new observer for the rotor resistance of an indirect vector controlled induction motor drive using artificial neural networks supplemented by a fuzzy logic based stator resistance observer. The error between the rotor flux linkages based on a neural network model and a voltage model is back propagated to adjust the weights of the neural network model for the rotor resistance estimation. The error between the measured stator current and its corresponding estimated value is mapped to a change in stator resistance with a proposed fuzzy logic. The stator resistance observed with this approach is used to correct the rotor resistance observer using neural networks. The performance of these observers and torque and flux responses of the drive, together with these estimators, are investigated with the help of simulations. Both modeling and experimental data on tracking performances of these observers are presented. With this approach accurate rotor resistance estimation was achieved and was made insensitive to stator resistance variations both in modeling and experiment.     

An induction machine model for predicting inverter-machineinteraction

The conventional qd induction motor model typically used in drive simulations is very inaccurate in predicting machine performance, except perhaps for the fundamental component of the current and the average torque near rated operating conditions. Predictions of current and torque ripple are often in error by a factor of two to five. This work sets forth an induction machine model specifically designed for use with inverter models to study machine-inverter interaction. Key features include stator and rotor leakage saturation as a function of current and magnetizing flux, distributed effects in the rotor circuits, and a highly computationally efficient implementation. The model is considerably more accurate than the traditional qd model, particularly in its ability to predict switching frequency phenomena. The predictions of the proposed model are compared with those of the standard qd model and to experimental measurements on a 37 W induction motor drive     

Induction motor dynamic and static inductance identification usinga broadband excitation technique

The performance of indirect vector control depends upon accurate prediction of the motor slip angular frequency (ω_s) for the demand torque. The required slip gain depends upon the rotor time constant of the motor (T_r). This value varies significantly over the operating temperature range and saturation level of a typical motor. This variation, if not compensated for, results in a significant degradation in torque production from a vector control system. The saturation effect can be compensated by an adaptive flux model if precise knowledge of the induction motor magnetizing curve is available. The aim of this paper is to present the application of an advanced system identification methodology enabling the off-line estimation of the magnetizing curve (dynamic and static inductance) of induction motors     

Operating principles of a novel multiphase multimotor vector-controlled drive

Independent flux and torque control of an ac machine can be achieved by means of vector control, utilizing only two stator d-q current components. Consequently, in ac machines with a phase number greater than three, there exist additional degrees of freedom. Although they can be used to enhance the torque production of a multiphase machine through injection of higher stator current harmonics, an entirely different purpose is possible as well. The additional degrees of freedom can be utilized to control independently other machines within a multimotor drive system. In order to do so, it is necessary to connect stator windings of all the multiphase machines in series, with an appropriate phase transposition, apply a vector control algorithm to each machine separately, and supply the stator windings of the multi-machine system from a single current controlled voltage source inverter (VSI). Inverter current control is performed in the stationary reference frame, using inverter phase currents. The foundations of the concept are set forth in the paper, for an arbitrary odd n-phase case, using the general theory of electrical machines. Further analysis is performed for all the theoretically possible odd phase numbers and it is shown that the number of machines connectable in series depends on the properties of the phase number. Connection diagrams are illustrated next for some selected phase numbers and vector control, including the inverter reference current generation, is detailed for the multimotor drive system. The main advantages and drawbacks of the concept are discussed and verification is provided by simulation of a nine-phase four-motor drive system.     

An improved model for saturated salient pole synchronous motors

An improved model for the transient analysis of saturated salient pole synchronous motors is presented. With the aid of saturation factors obtained by test or with finite elements, Park's equations for a synchronous machine are modified to independently account for the saturation of the magnetizing flux linkages in the region of the stator teeth and rotor pole face as well as saturation of the total flux linking the stator core. The model is used to calculate the starting performance for a direct online start as well as the transient performance during a load change. The model shows improvement over more traditional models, indicating that representation of both main flux and core saturation are important for synchronous machine analysis     

A method of tracking the peak power points for a variable speed wind energy conversion system

In this paper, a method of tracking the peak power in a wind energy conversion system (WECS) is proposed, which is independent of the turbine parameters and air density. The algorithm searches for the peak power by varying the speed in the desired direction. The generator is operated in the speed control mode with the speed reference being dynamically modified in accordance with the magnitude and direction of change of active power. The peak power points in the P-/spl omega/ curve correspond to dP/d/spl omega/=0. This fact is made use of in the optimum point search algorithm. The generator considered is a wound rotor induction machine whose stator is connected directly to the grid and the rotor is fed through back-to-back pulse-width-modulation (PWM) converters. Stator flux-oriented vector control is applied to control the active and reactive current loops independently. The turbine characteristics are generated by a DC motor fed from a commercial DC drive. All of the control loops are executed by a single-chip digital signal processor (DSP) controller TMS320F240. Experimental results show that the performance of the control algorithm compares well with the conventional torque control method.     

Induction machine field orientation along airgap and stator flux

Airgap and stator flux field orientation control (FOC) methods are discussed as an alternative to the familiar rotor flux orientation approach. The principal motivation is the relative accessibility of the two alternative fluxes. Motor flux models are developed in a unified manner, and it is shown that inherent coupling between flux and torque exists in the stator and airgap models. Two decoupling methods are presented. Simulation results are given for an airgap oriented control; the performance approaches that of a rotor flux oriented drive     

Speed and efficiency control of an induction motor withinput-output linearization

A combination of a composite adaptive speed controller and an explicit efficiency control algorithm is proposed to control the speed and power efficiency of the induction motor in this paper. First, the input-output linearization method is used to dynamically decouple the motor speed and rotor flux. Then, a composite adaptive control algorithm is designed to control the speed of the induction motor. At steady-state light-load condition, the magnetizing current command is adjusted on the basis of the product of magnetizing current command and torque current command such that the steady-state power loss is minimum. A PC-based experimental drive system has been implemented, and some experimental results are provided to demonstrate the effectiveness of the presented approach     

Speed control of a three-phase induction motor based on robust optimal preview control theory

A synthesized method for speed control of a three-phase induction motor (IM) based on optimal preview control system theory is implemented in this article. An IM model comprises three-input variables and three-output variables that coincide with the synchronous reference frame that is implemented using the vector method. The input variables of this model are the stator angular frequency and the two components of the stator space voltage vector, whereas the output variables are the rotor angular speed and the two components of the stator space flux linkage. The objective of the synthesized control system is to achieve motor speed control, field orientation control, and constant flux control. A novel error system is derived and introduced into the control law to increase the robustness of the system. The preview feed-forward controller, which includes the desired and disturbance signals, is used to improve the transient response of the system. A space vector pulse-width modulation (PWM) control technique for voltage source-fed IM is prepared for microprocessor-based control. Spectral analysis of the output voltage is evaluated to predict the effect of the proposed space vector modulation technique on the dynamic performance of the IM. The optimal preview controlled system is implemented, and its applicability and robustness are demonstrated by computer simulation and experimental results.     

A rotor-flux-observer-based composite adaptive speed controller foran induction motor

A composite adaptive speed controller for an induction motor based on a rotor-flux-observer is proposed in this paper. The rotor flux is estimated with the simplified rotor-flux-observer on the rotor reference frame and the input-output linearization theory is used to decouple the motor speed and the rotor flux. Then, the composite adaptive algorithm is used as the speed controller of the induction motor drive. The resulting system is verified to be stable. Some experimental results are provided to demonstrate the effectiveness of the proposed adaptive controller. Good speed tracking and load regulating responses can be obtained by the proposed composite adaptive controller. Moreover, the system can be operated in a wide range of speed and is robust to parameter variations     

Direct active and reactive power control of DFIG for wind energy generation

This paper presents a new direct power control (DPC) strategy for a doubly fed induction generator (DFIG)-based wind energy generation system. The strategy is based on the direct control of stator active and reactive power by selecting appropriate voltage vectors on the rotor side. It is found that the initial rotor flux has no impact on the changes of the stator active and reactive power. The proposed method only utilizes the estimated stator flux so as to remove the difficulties associated with rotor flux estimation. The principles of this method are described in detail in this paper. The only machine parameter required by the proposed DPC method is the stator resistance whose impact on the system performance is found to be negligible. Simulation results on a 2 MW DFIG system are provided to demonstrate the effectiveness and robustness of the proposed control strategy during variations of active and reactive power, rotor speed, machine parameters, and converter dc link voltage.     

基于矢量分析的转子碰磨故障轴向定位方法

1前言大型旋转机械具有单机功率大、转速高、空间尺寸大、动静间隙小等特点,在运转过程中,热力状态的变化往往会导致动静间隙减小甚至消失,从而引起动静碰磨。大型旋转机械一旦发生动静碰磨故障,轻者使机组的效率降低,重者引起机组剧烈振动,甚至引起重大的设备事故。快速地诊断     

Experimental characterization procedure for use with an advanced induction machine model

An advanced induction motor model that includes stator leakage saturation, rotor leakage saturation, magnetizing saturation, and distributed system effects in the rotor circuits has been set forth. This model is considerably more accurate than traditional models, particularly in terms of predicting switching-frequency dynamics. The model proposed is very general in terms of the range of magnetic properties that can be incorporated. This paper provides suggestions for specific forms for the leakage and magnetizing characteristics and derives the resulting small-signal impedance and large-signal steady-state equivalent circuit. Based on these results, a test procedure for experimentally characterizing the machine is developed. The application of the procedure to a 50-hp test machine is included as an example.     

Numerical and Experimental Modelling of Gas Flow and Heat Transfer in the Air Gap of an Electric Machine. Part Ⅱ： Grooved Surfaces

The study deals with the cooling of a high-speed electric machine through an air gap with numerical and experimental methods. The rotation speed of the test machine is between 5000-40000 r/min and the machine is cooled by a forced gas flow through the air gap. In the previous part of the research the friction coefficient was measured for smooth and grooved stator cases with a smooth rotor. The heat transfer coefficient was recently calculated by a numerical method and measured for a smooth stator-rotor combination. In this report the cases with axial groove slots at the stator and/or rotor surfaces are studied. Numerical flow simulations and measurements have been done for the test machine dimensions at a large velocity range. At constant mass flow rate the heat transfer coefficients by the numerical method attain bigger values with groove slots on the stator or rotor surfaces. The results by the numerical method have been confirmed with measurements. The RdF-sensor was glued to the stator and rotor surfaces to measure the heat flux through the surface, as well as the temperature.     

A stator resistance estimation scheme for speed sensorless rotor flux oriented induction motor drives

Accurate knowledge of stator resistance is of utmost importance for correct operation of a number of speed sensorless induction motor control schemes in the low speed region. Since stator resistance inevitably varies with operating conditions, stable and accurate operation at near-zero speed requires an appropriate online identification algorithm for the stator resistance. The paper proposes such an identification algorithm, which is developed for the rotor flux-based model reference adaptive system (MRAS) type of the speed estimator in conjunction with a rotor flux oriented control scheme. In this speed estimation method, only one degree of freedom (out of the two available) is utilized for speed estimation. It is proposed to utilize the second available degree of freedom as a means for adapting the stator resistance online. The parallel stator resistance and rotor speed identification algorithm is developed in a systematic manner, using Popov's hyperstability theory. It increases the complexity of the overall control system insignificantly and enables correct speed estimation and stable drive operation at near-zero speeds. The proposed speed estimator with parallel stator resistance identification is at first verified by simulation. Extensive experimentation is conducted next at low speeds of rotation and successful stator resistance identification is achieved down to 0.5-Hz frequency of rotation.     

A novel NN based rotor flux MRAS to overcome low speed problems for rotor resistance estimation in vector controlled IM drives

This paper presents a new neural network based model reference adaptive system (MRAS) to solve low speed problems for estimating rotor resistance in vector control of induction motor (IM). The MRAS using rotor flux as the state variable with a two layer online trained neural network rotor flux estimator as the adaptive model (FLUX-MRAS) for rotor resistance estimation is popularly used in vector control. In this scheme, the reference model used is the flux estimator using voltage model equations. The voltage model encounters major drawbacks at low speeds, namely, integrator drift and stator resistance variation problems. These lead to a significant error in the estimation of rotor resistance at low speed. To address these problems, an offline trained NN with data incorporating stator resistance variation is proposed to estimate flux, and used instead of the voltage model. The offline trained NN, modeled using the cascade neural network, is used as a reference model instead of the voltage model to form a new scheme named as “NN-FLUXMRAS.” The NN-FLUX-MRAS uses two neural networks, namely, offline trained NN as the reference model and online trained NN as the adaptive model. The performance of the novel NN-FLUX-MRAS is compared with the FLUX-MRAS for low speed problems in terms of integral square error (ISE), integral time square error (ITSE), integral absolute error (IAE) and integral time absolute error (ITAE). The proposed NN-FLUX-MRAS is shown to overcome the low speed problems in Matlab simulation.     

Real-Time Speed and Flux Adaptive Control of Induction Motors Using Unknown Time-Varying Rotor Resistance and Load Torque

In this paper, an algorithm for direct speed and flux adaptive control of induction motors using unknown time-varying rotor resistance and load torque is described and validated with experimental results. This method is based on the variable structure theories and is potentially useful for adjusting online the induction motor controller unknown parameters (load torque and rotor resistance). The presented nonlinear compensator provides voltage inputs on the basis of rotor speed and stator current measurements, and generates estimates for both the unknown parameters and the nonmeasurable state variables (rotor flux and derivatives of the stator current and voltage) that converge to the corresponding true values. Experiments show that the proposed method achieved very good tracking performance within a wide range of the operation of the induction motor (with online variation of the rotor resistance: up to (87%). This high tracking performance of the rotor resistance variation demonstrates that the proposed adaptive control is beneficial for motor efficiency. The proposed algorithm also presented high decoupling performance and very interesting robustness properties with respect to the variation of the stator resistance (up to 100%), measurement noise, modeling errors, discretization effects, and parameter uncertainties (e.g., inaccuracies on motor inductance values). The other interesting feature of the proposed method is that it is simple and easily implementable in real time. Comparative results have shown that the proposed adaptive control decouples speed and flux tracking while standard field-oriented control does not.