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     

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.     

An improved sensorless vector-control method for an induction motor drive

In the present paper, a new improved sensorless vector-control method for an induction motor drive is presented. The proposed method is based on an improved closed-loop stator-flux estimator, based on the dynamic model of the asynchronous motor, which achieves precise stator-flux estimation over a wide area of operation. This new stator-flux estimator ensures stability of the overall control scheme in a very-wide-speed operation area, as it will be shown in this paper. The rotor-speed-estimation method is based on an observer based on the model reference adaptive systems (MRAS) theory. The control scheme is based on a stator-flux-oriented direct vector-control method, where both flux and speed controllers are optimal tuned. In addition, implementation of the proposed method is based on a simplified algorithm capable of running in a low-cost microcontroller, which is discussed in detail. Also, the motor-drive system, including the stator-flux estimator, the speed estimator, and the control logic are simulated and some characteristic simulation results are presented. These results reveal that the proposed method is able to obtain precise flux and speed control over a wide operation area, including very low operating frequencies.     

Online Identification of Stator Transient Inductance in Rotor-Flux-Oriented Induction Motor Drive

In a rotor-flux-oriented induction motor drive, stator transient inductance is varied with the change of operating conditions. If the stator transient inductance is not tuned, the field orientation cannot be obtained. As a result, q-axis rotor flux does not become zero, and the performance is deteriorated. This paper shows the problems caused by the detuning of stator transient inductance and proposes a simple online tuning scheme of stator transient inductance for an indirect rotor flux-oriented induction motor drive. Stator transient inductance is estimated only by stator voltage and stator current. The proposed method is verified by simulation and experimental results.     

Stator-flux-oriented control of induction motor considering ironloss

Research to consider the influences of iron loss has been made in the vector control of an induction motor. However, little work has been done in the area of a stator-flux-oriented control system of an induction motor. This paper investigates the effects of iron loss in the direct stator-flux-oriented control system of an induction motor, and proposes a control algorithm considering iron loss. The iron loss is modeled by equivalent iron loss resistance in parallel to the magnetizing inductance. Torque control capability is much improved and the speed estimation error for a speed-sensorless drive is reduced by the proposed control algorithm. The effectiveness of the proposed method is verified by simulation and experimental results     

Efficiency enhancement for indirect vector-controlled induction motor drive

In this paper, efficiency enhancement algorithms are developed and implemented on an indirect vector-controlled three-phase induction motor (IM) drive, and its performance under different operating conditions is analysed. The controllable electrical losses in the IM are minimised through the optimal control of direct axis (d-axis) stator current, and improvement in motor efficiency is achieved by weakening the rotor flux. The optimal d-axis stator current is also estimated using particle swarm optimisation (PSO) to validate the results obtained through analytical control method. The developed algorithms are tested under various operating conditions and the dynamic performance of the IM drive is analysed. The effectiveness of analytical and PSO-based efficiency optimisation control over conventional constant flux control, especially during light load at rated speed operation, is summarised. The effectiveness of the developed algorithm is validated experimentally through development of laboratory prototype set-up. The effect of parametric variation on efficiency, stator current, torque and speed of IM drive is studied through sensitivity analysis. The effect of variation in stator and rotor resistance due to change in operating temperature of the IM is also analysed and the robustness of the developed algorithm against parametric variations is demonstrated through simulation and experimental studies.     

基于电阻压降补偿的直接转矩控制的研究

本文分析了异步电动机直接转矩控制的基本原理,完成基于空间电压矢量控制技术(SVPWM)的异步电机直接转距控制的MATLAB/SIMULINK仿真研究,并对低速时异步电动机性能进行了简单分析,采用定子电阻压降补偿来减小磁链轨迹的畸变,得到了较好的控制效果。     

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     

Stator-flux-oriented vector control of synchronous reluctance Machines with maximized efficiency

This paper presents a position-sensorless vector torque controller designed to achieve maximum efficiency over a range of power and rotational speed for a synchronous reluctance machine. A model of the synchronous reluctance machine is presented which incorporates both winding and core losses. It is then shown that a stator-flux-oriented control scheme can achieve synchronous operation of the machine without a position sensor at medium and high electrical frequencies. For a given speed and torque, power losses in the machine are shown to be a function of only the stator flux magnitude. As the power losses are a convex function of the stator flux level, the optimal flux value can be found using a one-dimensional optimization algorithm, such as the Method of Sequential Quadratic Interpolations. Optimal flux values for a synchronous reluctance machine are determined using an experimental setup that accurately determines losses in the motor/drive system. Experimental results obtained from the test setup confirm the validity of the controller and the optimization algorithm.     

A sensorless vector control system for induction motors usingq-axis flux with stator resistance identification

This paper presents a sensorless vector control system for general-purpose induction motors, which is based on the observer theory and the adaptive control theories. The proposed system includes a rotor speed estimator using a q-axis flux and stator resistance identifier using the d-axis flux. The advantages of the proposed system are simplicity and avoidance of problems caused by using only a voltage model. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including the influence of the observer gain, motor operating state, and parameter variations. In order to obtain stable low-speed operation and speed control accuracy, an algorithm for compensating for the deadtime of the inverter and correcting the nonideal features of an insulated gate bipolar transistor was developed. The effectiveness of the proposed system has been verified by digital simulation and experimentation     

An online identification method for both stator-and rotorresistances of induction motors without rotational transducers

This paper describes an effective online method for identifying both stator and rotor resistances, which is useful in robust speed control of induction motors without rotational transducers. The identification method for stator resistance is derived from the steady-state equations of induction motor dynamics. On the other hand, the identification method for rotor resistance is based on the linearly perturbed equations of induction motor dynamics about the operating point. The identification method for both stator and rotor resistances uses only the information of stator currents and voltages. It can provide fairly good identification accuracy regardless of load conditions and be easily incorporated into any sensorless speed controller proposed in the prior literature. Some experimental results are presented to demonstrate the practical use of the identification method. A sensorless speed control system has been built for experimental work, in which all algorithms for identification and control are implemented on a digital signal processor. The experimental results confirm that the proposed method allows for high-precision speed control of commercially available induction motors without rotational transducers     

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     

An innovative direct self-control scheme for induction motor drives

The paper presents a new direct self-control (DSC) scheme for induction motor drives using the stator voltage third harmonic component in order to estimate the air-gap flux and the torque as well as to synchronize the supply voltage vector. Compared to previous DSC schemes the new one is independent from any motor parameter variation, specifically on stator resistance thus showing better performances at low speeds. The paper starts with a quick review on standard DSC main features pointing out the influence of stator resistance variations on the flux and torque control. The new DSC scheme is then introduced and evaluated by simulations and experimental tests on a 1.5 kW induction motor drive     

A digital current control technique for voltage-fed induction motor drives

Precise control of stator current is essential to high performance field orientation controlled induction motor drives. Any current error degrades the performance of the drive in the same way as incorrect tuning of field orientation. Previous research has shown that accurate current control can be achieved with intelligent but complex control algorithms. This paper presents a new current control scheme which can achieve high accuracy and fast dynamic response but which is very simple for microprocessor implementation. The scheme was derived using the discrete state space modelling of the induction motor. The control law does not require knowledge of rotor flux and was independent of the field orientation control tuning. Good static and dynamic performances were obtained in both the simulation and experimental verifications. The results also show that the leakage inductance model error might cause a current ripple. However, this parameter can be tuned to its correct value easily by inspecting the current response.     

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     

An implementation of a programmable cascaded low-pass filter for a rotor flux synthesizer for an induction motor drive

This paper investigates a programmable cascaded low pass filter for the estimation of rotor flux of an induction motor, with a view to estimate the rotor time constant of an indirect field orientation controlled induction motor drive. Programmable cascaded low pass filters have been traditionally used in stator flux oriented vector control of the induction motor. This paper extends the use of this filter to estimate the rotor flux for the indirect field orientation control by generating rotor flux estimates from stator flux estimates. This is achieved by using a three-stage programmable cascaded low pass filter. The three-stage programmable cascaded low-pass filter investigated in this paper has resulted in excellent estimation of rotor flux in the steady-state and transient operation of an indirect field oriented drive. The estimated rotor flux data have also been used for the on-line rotor resistance identification with artificial neural network. Modeling and experiment results presented in this paper demonstrate this method of estimating rotor flux clearly.     

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     

PI and fuzzy estimators for tuning the stator resistance in directtorque control of induction machines

Direct torque control (DTC) of induction machines uses the stator resistance of the machine for estimation of the stator flux. Variations of stator resistance due to changes in temperature or frequency make the operation of DTC difficult at low speeds. A method for the estimation of changes in stator resistance during the operation of the machine is presented. The estimation method is implemented using proportional-integral (PI) control and fuzzy logic control schemes. The estimators observe the machine stator current vector to detect the changes in stator resistance. The performance of the two methods are compared using simulation and experimental results. Results obtained have shown improvement in DTC at low speeds     

A MRAS-based adaptive pseudoreduced-order flux observer for sensorless induction motor drives

The performance of vector-controlled sensorless induction motor drives is generally poor at very low speeds, especially at zero speed due to offset and drift components in the acquired feedback signals, and the increased sensitivity of dynamic performance to model parameter mismatch resulting especially from stator resistance variations. The speed estimation is adversely affected by stator resistance variations due to temperature and frequency changes. This is particularly significant at very low speeds where the calculated flux deviates from its set values. Therefore, it is necessary to compensate for the parameter variation in sensorless induction motor drives, particularly at very low speeds. This paper presents a novel method of estimating both the shaft speed and stator resistance of an induction motor. In this novel scheme, an adaptive pseudoreduced-order flux observer (APFO) is developed. In comparison to the adaptive full-order flux observer (AFFO), the proposed method consumes less computational time, and provides a better stator resistance estimation dynamic performance. Both simulation and experimental results confirm the superiority of the proposed APFO scheme for a wide range of resistance variations from 0 to 100%.     

Real-time sliding-mode observer and control of an induction motor

This paper deals with the control and observation of an induction motor using a sliding-mode technique. The authors' aim is to regulate the speed and the square of the rotor flux magnitude to specified references. Assuming that all the states are measured, sliding surfaces are proposed within a sliding-mode control framework. Then, the stator voltages are derived such that the sliding surfaces are asymptotically attractive since, in practice, the rotor fluxes are not usually measurable, a sliding-mode observer is derived to estimate the rotor fluxes. Furthermore, it is shown that their observer is robust against modeling uncertainties and measurement noise. To illustrate their purpose, they present experimental results for a 0.37-kW induction motor obtained on a digital-signal-processor-based system (TMS 320C31/40 MHz). The experimental results show that the proposed control system is robust against rotor resistance variations