Online identification of induction machine electrical parameters for vector control loop tuning

In a vector-controlled induction machine drive, accurate knowledge of the machine electrical parameters is required to ensure correct alignment of the stator current vector relative to the rotor flux vector, to decouple the fluxand torque-producing currents and to tune the current control loops. This paper presents a new method for online identification of the induction machine parameters required to tune a rotor-flux-oriented (RFO) vector control scheme. Accuracy of the slip frequency estimation required for RFO vector control is achieved by utilizing the parameter independent "flux pulse" rotor time constant estimation scheme, which utilizes short-duration pulses injected into the flux-producing current. The parameters required to tune the synchronous frame current control loops with a decoupling circuit are estimated using a recursive estimation scheme derived from the synchronous frame voltage equations. As the "flux pulse" scheme requires signal injection into the flux-producing current a new rotor time constant estimation scheme is presented, based on the sensitivity analysis of the recursive parameter estimation scheme. Simulation and experimental results are presented which demonstrate the effectiveness of the online parameter identification and control loop tuning technique.     

Modeling and simulation of induction machine vector control withrotor resistance identification

This paper shows that it is possible to use available commercial software to model and simulate a vector-controlled induction machine system. The components of a typical vector control system are introduced and methods given for incorporating these in the MATLAB/SIMULINK software package. The identification of rotor resistance is important in vector control, if high-performance torque control is needed, and modeling of the extended Kalman filter (EKF) algorithm for parameter identification is discussed. It is certainly advisable, when feasible, to precede implementation of new algorithms, whether for control or identification purposes, with an extensive simulation phase. Additionally, a technique for generating pulse-width modulation (PWM) phase commands to extend machine operation to higher speeds before field weakening occurs is simulated in a vector-controlled induction machine, driven by a PWM inverter. This demonstrates the versatility of the vector-controlled induction machine system model     

Estimation of induction machine inverse rotor time constant using torque angle tangent calculation

A new inverse rotor time constant estimation scheme for an induction machine is presented. For high performance induction machine control, indirect rotor flux oriented vector control is the most commonly applied control technique. It requires that an accurate estimate of the inverse rotor time constant is obtained to ensure correct orientation of the current vector with the rotor flux vector. An incorrect estimate will result in an incorrect flux level, reduced dynamic torque performance and reduced maximum available torque. A novel parameter estimation scheme is presented, based on the calculation of the tangent of the torque angle. The effectiveness of the technique is demonstrated through simulation and practical results.     

Field oriented control of induction machines employing rotor endring current detection

The usual method of induction motor torque control uses the indirect field orientation principle in which the rotor speed is sensed and slip frequency is added to form the stator impressed frequency. Unfortunately, the rotor resistance varies as the motor heats up under load thereby changing the rotor time constant which has a deleterious effect on the torque response. In this paper two new field oriented control schemes are presented which employ rotor end ring current detection and thereby remove the dependence of the controller accuracy on temperature so that the controller is entirely independent of rotor time constant variations. The field orientation schemes do not require an incremental encoder for rotor position sensing. The motor torque can be accurately controlled even down to zero speed operation     

Decoupled stator-flux-oriented induction motor drive with fuzzyneural network uncertainty observer

A stator-flux-oriented induction motor drive using online rotor time-constant estimation with a robust speed controller is introduced in this paper. The estimation of the rotor time constant is made on the basis of the model reference adaptive system using an energy function. The estimated rotor time-constant is used in the current-decoupled controller, which is designed to decouple the torque and flux in the stator-flux-field-oriented control. Moreover, a robust speed controller, which is comprised of an integral-proportional speed controller and a fuzzy neural network uncertainty observer, is designed to increase the robustness of the speed control loop. The effectiveness of the proposed control scheme is demonstrated by simulation and experimental results     

Flux observer with online tuning of stator and rotor resistancesfor induction motors

This paper proposes an adaptive flux observer for induction motors, where stator and rotor resistances are estimated in online environments. The variation of motor parameters during operation degrades the performance of the controller and the flux observer. Among the parameters of induction motors, rotor resistance is a crucial one for flux estimation, and stator resistance also becomes critical in the low-speed region. Under the persistent excitation condition, the proposed method estimates the actual values of stator and rotor resistances simultaneously, which guarantees the exact estimation of the rotor flux. The persistent excitation condition is not satisfied when the electric torque of an induction motor is absent due to the lack of rotor currents. Even in this case, the proposed method achieves the correct estimation of the rotor flux. Simulations and actual experiments show that the rotor flux is estimated in all operating conditions and that both resistances converge to their actual values when the electrical motor torque exists     

A dynamic decoupling control scheme for high-speed operation ofinduction motors

In a high-speed operation of a vector-controlled induction motor, coupling between d-q current dynamics impairs the characteristics of torque response. The feedforward decoupling scheme does not perform well if an error exists in the motor parameter estimation. We derive a dynamic decoupling condition when the two additional proportional integral current controllers are used. A great advantage of this dynamic decoupling controller is the robustness to the motor parameter estimation errors. Further, we observe that overmodulation methods lead to the violation of the decoupling condition, thereby yielding a poor performance in the high-speed high-power operation. As a method of resolving this problem, we propose a decoupling preserving overmodulation algorithm which also enhances the torque transient response. Through simulation and experimental results, we demonstrate the improved performance of the proposed controller     

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     

Quasi-fuzzy estimation of stator resistance of induction motor

This paper describes a quasi-fuzzy method of online stator-resistance estimation of an induction motor, where the resistance value is derived from stator-winding temperature estimation as a function of stator current and frequency through an approximate dynamic thermal model of the machine. The estimator has been designed and iterated by simulation study and then implemented by a digital signal processor on a 5 hp stator-flux-oriented direct vector-controlled drive. The experimental performance of the estimator has been calibrated extensively both at static and dynamic conditions by a stator-mounted thermistor network-based estimation and gives excellent performance. The stator-winding temperature information can also be used for monitoring, protection, and fault-tolerant control of the machine     

Thermal and slip effects on rotor time constant in vector controlled induction motor drives

In this paper, the fast variation of rotor resistance due to winding temperature is shown. Thus, the rotor time constant in the vector controlled induction motor drives, in contrary to common belief, changes fast via temperature. Moreover, it depends on the motor slip. The slip dependency of rotor time constant is due to motor loss that is usually ignored. The iron and stray loss is introduced in the induction machine dynamic and static models and a new expression of the rotor time constant is derived, that contains the motor slip. Thus, the rotor time constant rapidly varies at load torque changes. A novel slip frequency calculation procedure is proposed that ensures the accurate and fast estimation of the valid machine rotor time constant. The above aspects have been verified by extensive simulation and experimental tests in a wide speed-torque range.     

A rotor time constant evaluation for vector-controlled inductionmotor drives

The online identification method for the rotor time constant of an induction machine is derived from the steady-state analysis of the machine space vectors. The indirect field orientation system is simulated to verify the convergence of the method in quasi-steady-state operation, independent of the initial controller parameters     

Implementation of a DSP based real-time estimator of inductionmotors rotor time constant

Implementation of ac drives insensitive to parameter variations is an important need in the field of high performance drives. For drives controlled by the indirect rotor flux oriented control method (IRFOC), the rotor time constant (τ_r = L_r/R_r) exerts a dominant role in the loss of dynamic performance and its variation results in an undesirable coupling between flux and torque of the machine. This paper presents a new scheme for on-line estimation of rotor time constant using dq representation of the model in the stationary reference frame and measurements of accessible motor variables only (voltages, currents and speed). The estimator is tested by simulation in the MATLAB/SIMULINK environment and validated experimentally on a 1/4 hp squirrel cage motor and a 1/4 hp wound rotor motor with implementation on a TMS320C31 digital signal processor     

Speed-sensorless sliding-mode torque control of an induction motor

Novel induction motor control optimizing both torque response and efficiency is proposed in the paper. The main contribution of the paper is a new structure of rotor flux observer aimed at the speed-sensorless operation of an induction machine servo drive at both low and high speed, where rapid speed changes can occur. The control differs from the conventional field-oriented control. Stator and rotor flux in stator fixed coordinates are controlled instead of the stator current components in rotor field coordinates i_sd and i_sq. In principle, the proposed method is based on driving the stator flux toward the reference stator flux vector defined by the input command, which are the reference torque and the reference rotor flux. The magnitude and orientation angle of the rotor flux of the induction motor are determined by the output of the closed-loop rotor flux observer based on sliding-mode control and Lyapunov theory. Simulations and experimental tests are provided to evaluate the consistency and performance of the proposed control technique     

High-performance speed servo system considering Voltage saturation of a vector-controlled induction motor

Generally, a speed servo system of a vector-controlled induction motor has limitations of motor voltage and current. When the speed servo system has a large torque reference, the output of its PI controller is often saturated. In this case, the conventional servo system stops the integral calculation of its PI controller. However, this system often has a large overshoot and/or an oscillated response caused by both a windup phenomenon and phase error on the vector control condition. This paper proposes a new speed servo system considering voltage saturation for the vector-controlled induction motor. The proposed control method compensates the phase error on vector control condition quickly, and always keeps the vector control condition. The experimental results show that the proposed system well regulates the motor speed and the secondary magnetic flux for a large torque reference without a windup phenomenon.     

Online Stator and Rotor Resistance Estimation Scheme Using Artificial Neural Networks for Vector Controlled Speed Sensorless Induction Motor Drive

This paper presents a new method of online estimation for the stator and rotor resistances of the induction motor for speed sensorless indirect vector controlled drives, using artificial neural networks. 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. For the stator resistance estimation, the error between the measured stator current and the estimated stator current using neural network is back propagated to adjust the weights of the neural network. The rotor speed is synthesized from the induction motor state equations. The performance of the stator and rotor resistance estimators and torque and flux responses of the drive, together with these estimators, are investigated with the help of simulations for variations in the stator and rotor resistances from their nominal values. Both resistances are estimated experimentally, using the proposed neural network in a vector controlled induction motor drive. Data on tracking performances of these estimators are presented. With this speed sensorless approach, the rotor resistance estimation was made insensitive to the stator resistance variations both in simulation and experiment. The accuracy of the estimated speed achieved experimentally, without the speed sensor clearly demonstrates the reliable and high-performance operation of the drive     

A new stator resistance tuning method for stator-flux-orientedvector-controlled induction motor drive

Field-oriented-controlled induction motor drives have been widely used over the last several years. Conventional direct stator-flux-oriented control schemes have the disadvantage of poor performance in the low-speed operating area when the stator flux is calculated using the voltage model, due to the stator resistance uncertainties and variations. In this paper, a new closed-loop stator-flux estimation method for a stator-flux-oriented vector-controlled induction motor drive is presented in which the stator resistance value is updated during operation. This method is based on a simple algorithm capable of running in a low-cost microcontroller, which is derived from the dynamic model of the induction machine. The effects of stator resistance detuning, especially in the low-speed operating region, are investigated and simulation results are shown. The motor drive system as well as the control logic and the resistance estimator are simulated and characteristic simulation results are derived. In addition, the proposed control scheme is experimentally implemented and some characteristic experimental results are shown. The simulation as well as the experimental results reveal that the proposed method is able to obtain precise flux and torque control, even for very low operating frequencies     

High-bandwidth current control for torque-ripple compensation in PMsynchronous machines

Active compensation of torque harmonics in high-performance synchronous permanent magnet (PM) motor drives requires high-bandwidth current control. It is demonstrated that proportional integral (PI) current control exhibits performance limits, even when feedforward compensation of the rotor induced voltage and the stator inductance drop is used. High bandwidth requirements are satisfied using a digital deadbeat current controller. Sampling time delays are eliminated to the extent possible by means of a current predictor. The current controller and the predictor refer to a model of the parasitic effects of the PM synchronous machine that is acquired and adapted to parameter changes in real time. Stator current distortions due to deviations from the sinusoidal flux linkage distribution are thus eliminated. The control system facilitates compensation of high-frequency torque ripple of the machine     

Stator resistance tuning in a stator-flux field-oriented driveusing an instantaneous hybrid flux estimator

A self-tuning control scheme for stator-flux field-oriented induction machine drives in electric vehicles operating over a wide speed range is discussed in this paper. The stator flux can be determined accurately from the terminal voltage when the machine is operating at high speed. However, at low speed, the stator resistance must be known to calculate the stator flux. The problem of calculating the stator flux accurately over the entire speed range is addressed. The rotor flux can be found from the machine speed and rotor time constant. The stator flux, at low speed, is then calculated directly from the rotor flux. By alternating between these two methods of determining the stator flux, a self-tuning operation is achieved, wherein the stator and rotor resistances are periodically updated. Since both methods of determining the stator flux are forced to track one another, a smooth transition between flux estimators is obtained. The torque and flux are then controlled in a deadbeat fashion. Good torque control over a wide speed range can therefore be obtained. With the proposed scheme, the advantages of direct torque control are obtained over the entire speed range with the addition of a speed sensor     

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