Rotor Resistance Research Articles

Research on the Hoisting Motor Drive System’s Active Disturbance Rejection Control and Energy Consumption for a Crane

To allow the hoisting motor drive system of a crane to track a load torque quickly, a linearization method was used to transform a motor nominal dynamics model into two decoupled linear rotor speed and flux linkage subsystems. The method based on the theory of differential geometry was a precise feedback method. Two active disturbance rejection controllers (ADRCs) with identical structures were designed for the rotor speed and flux linkage subsystems. The extended state observer of the ADRC could estimate the unmodeled dynamics of the motor, the variation of motor parameters due to heating, and the unknown disturbances of the motor system to determine the total disturbances of the system. A closed-loop system with ADRC and an open-loop system were compared. The motor's full-load starting time was reduced by about 50%. When the motor operated smoothly at different load rates and the rated load was suddenly applied, the electromagnetic torque fluctuation range did not exceed 20 N·m. The rotor flux was always stable at the reference value. The motor speed decreased, but the amount of decrease did not exceed 7 rad/s. The closed-loop system had a significant energy-saving effect during the motor's starting process. The power saving rate was about 55%-59% if the motor started with a light load. The power saving rate could reach 71% if the motor started with a heavy load. The ADRC system could accurately estimate the unknown model of the rotor speed and flux linkage subsystems, and adapt to parameter variations of the motor stator and rotor resistance in the range of ±10%.

Effective Predictive Current Control for a Sensorless Five-Phase Induction Motor Drive

The paper aims to develop an effective predictive current control (PCC) procedure for a sensorless five-phase induction motor (IM) drive. The proposed PCC considers the discrete behaviour of the voltage source inverter (VSI) and provides the voltage vectors utilising the finite control set (FCS) principle, thus, there is no need for using the pulse width modulation (PWM) techniques. A combined sliding mode-Luenberger observer is used to estimate the motor speed, stator current, rotor flux, load torque, and stator and rotor resistances. An effective pole placement procedure is proposed for selecting the most appropriate gains of the observer to enhance the estimation process and to improve the observer's robustness against uncertainties in the system. The drive performance has been tested for a wide range of speed changes. The obtained results demonstrate the effectiveness of proposed PCC in obtaining high dynamic performance from the drive. Moreover, the proposed sensorless procedure has confirmed its validity to estimate precisely the required control variables.

Векторне керування асинхронним генератором з підвищеним коефіцієнтом корисної дії

Compared to today’s dominant in autonomous wind power, a synchronous generator with permanent magnets, an induction generator (IG) with a short-circuited rotor has such significant advantages as higher reliability and lower cost. But the energy performance in IG is lower, so their improvement is an actual task. To solve this problem, along with search algorithms, systems of no-search optimization of power losses in IG are intensively developed. In these systems, the optimal magnetic flux is determined by the analytical expression obtained from the loss model. The disadvantages of the known works on this topic are that they use various simplified models of losses. Accordingly, this reduces the accuracy of optimization algorithms. The aim of the work is to build the vector control system of IG, in which, due to the optimization of the sum of major power losses, a significant increment in the efficiency of the generator is achieved. The article uses a model of power losses, which includes all the main losses in the IG of electromagnetic nature. These include ohmic losses in the stator and rotor resistances, magnetic losses in the iron and additional losses. By analytical study of the model of losses to the extremum, an expression for determining the optimal flux linking of the rotor by the criterion of minimum total losses in the generator is obtained. The application of this expression allows to increase the accuracy of loss optimization in comparison with known analogues. The procedure for determining the optimal flux uses the signals of the instantaneous component of the stator current and rotor speed and is simple for computer implementation in real time. Numerical studies of steady-state processes in the mode of operation of the generator with a constant output power P2=const for its values from 15 % to 45 % have been conducted. It is established that the efficiency increment obtained due to control with loss optimization has an extreme character with a maximum in the vicinity of the nominal speed. As P2 increases, the loss optimization zone and efficiency increment decrease. The maximum and average efficiency increment obtained in the study reach 19 % and 11 %, respectively. This shows the prospects of the proposed system of energy-efficient vector control of IG.

Effective predictive current control for a sensorless five-phase induction motor drive

The paper aims to develop an effective predictive current control (PCC) procedure for a sensorless five-phase induction motor (IM) drive. The proposed PCC considers the discrete behaviour of the voltage source inverter (VSI) and provides the voltage vectors utilising the finite control set (FCS) principle, thus, there is no need for using the pulse width modulation (PWM) techniques. A combined sliding mode-Luenberger observer is used to estimate the motor speed, stator current, rotor flux, load torque, and stator and rotor resistances. An effective pole placement procedure is proposed for selecting the most appropriate gains of the observer to enhance the estimation process and to improve the observer's robustness against uncertainties in the system. The drive performance has been tested for a wide range of speed changes. The obtained results demonstrate the effectiveness of proposed PCC in obtaining high dynamic performance from the drive. Moreover, the proposed sensorless procedure has confirmed its validity to estimate precisely the required control variables.

A Novel Sensorless Predictive Voltage Control for an Induction Motor Drive Based on a Back-Stepping Observer-Experimental Validation

The current paper presents a novel predictive voltage control (PVC) for an induction motor (IM) without using a speed sensor. The proposed PVC is formulated using the model predictive control principle in which the stator voltages are directly controlled rather than regulating the flux and torque as in traditional MP DTC. The advantages of the proposed PVC over the commonly used MP DTC scheme are the reduced calculation time, the reduced ripples and the fast dynamic. To realize the sensorless operation of the IM, a robust observer is used to estimate the speed, rotor flux, stator current and stator and rotor resistances. The observer is constructed based on the back-stepping theory. Testing the validness of the proposed sensorless PVC technique is performed in a form of comparison between the PVC and MP DTC procedures. The tests are firstly accomplished using the Matlab/Simulink software; then, a dSPACE 1104 test board is utilized for the experimental validation. The simulation and experimental results show that the IM dynamics are effectively enhanced when applying the proposed PVC in comparison with the MP DTC performance. The back-stepping observer (BSO) also proved its ability to estimate the specified variables for different operating speeds and under parameters variation as well.

Identify magnetising inductance and rotor resistance to improve the performance of the induction motor through IRFOC

To get a high dynamic performance of AC machines, field-oriented control was used. The best method of field-oriented control is an indirect rotor flux-oriented control. When applied this method of ...

Sensorless Field-Oriented Control for Open-End Winding Five-Phase Induction Motor With Parameters Estimation

This paper proposes a sensorless field-oriented control (FOC) of an open-end stator winding five-phase induction motor (OESW-FPIM). The FOC technique used is associated with dual Space Vector Modulation (SVM) to provide a constant switching frequency and lower harmonics distortion. Furthermore, a simple hybrid observer is proposed which combines a model reference adaptive system (MRAS) and a sliding mode (SM) observer. The examined observer is designed for the estimation of the rotor flux and rotational speed as well as for the estimation of the load torque disturbances. Lyapunov theorem is used in this paper to prove the observer's stability. The work presented in this paper aims to enhance the researched motor's sensorless control and its robustness against external load disturbances and parameters variation. In the proposed MRAS-SM observer, the reference model is replaced by a SM model which uses a sigmoid function as a switching function to overcome the chattering problem. This combination is intended to make use of the advantages of both strategies. At the same time, to preserve the high-level performance of the sensorless FOC technique and to reduce system uncertainties, an estimation algorithm is developed to identify the rotor resistance and the stator resistance simultaneously during motor operation. The parameter estimation algorithm is combined with the proposed control to improve the speed estimation and control accuracy, particularly at low-speed operation. Finally, the effectiveness of the proposed control is validated in real-time by utilizing a hardware-in-the-loop (HIL) platform.

Identify magnetising inductance and rotor resistance to improve the performance of the induction motor through IRFOC

Identify magnetising inductance and rotor resistance to improve the performance of the induction motor through IRFOC

Enhancement of new rotor resistance unit for doubly fed induction generator-based wind turbines

It is very important to obtain smooth power and limit over-currents in grid-connected doubly fed induction generator (DFIG)-based wind turbines. Therefore, the rotor resistance unit can be used for power and over-currents control in DFIG. However, it may be insufficient to reduce oscillations in large power systems. This study aims to develop a new rotor resistance unit for low voltage ride through (LVRT) capability in DFIG. Moreover, electromotive-force (emf) models have been also developed in the stator and rotor circuit. The stator emf model of the simulation study was developed in the DFIG for accuracy and speed, while the rotor emf model was developed for over-current occurring in transient situations. In using the new rotor resistance unit and the stator-rotor emf, it was observed that the system stabilized in a short time, and the oscillations formed by the balanced and unbalanced faults on the grid side were damped.

Енергоефективна система керування автономним асинхронним генератором для віддалених поселень

Laying power lines to small settlements and farms away from towns and villages is not always cost-effective. Therefore, autonomous solar and wind energy sources are increasingly used in such settlements. In contrast to the dominant today in wind power plants synchronous generators with permanent magnets, an induction generator (IG) with a short-circuited rotor have such important advantages as higher reliability and lower cost. But the energy performance in IG is lower, so their improvement is an actual task. To solve this problem, systems of no-search optimization of power losses in IG are intensively developed. In these systems, the optimal magnetic flux is determined by the analytical expression obtained from the loss model. The disadvantages of the known works on this topic are that they use various simplified models of losses. Accordingly, this reduces the accuracy of optimization algorithms. The aim of the work is to build the vector control system of IG, in which, due to the optimization of the sum of major power losses, a significant increment in the efficiency of the generator is achieved. The article uses a model of power losses, which includes all the main losses in the IG of electromagnetic nature. These include ohmic losses in the stator and rotor resistances, magnetic losses in the iron and additional losses. By analytical study of the model of losses to the extremum, a expression is obtained to calculate the optimal flux linkage of the rotor by the criterion of minimum total losses in the generator. The application of this expression allows to increase the accuracy of loss optimization in comparison with known analogues. Numerical studies of steady-state processes in the mode of operation of the generator with a constant output power P2=const for its values from 10% to 50% have been conducted. It is established that the efficiency increment obtained due to control with loss optimization has an extreme character with a maximum in the vicinity of the nominal speed. The maximum and average efficiency increment obtained in the study reach 26% and 18%, respectively. This shows the prospects of the proposed system of energy-efficient vector control of IG.

Impact of Induction Motor Faults on the Basic Parameters' Values

Unlike fault diagnosis approaches based on the direct analysis of current and voltage signals, this paper proposes a diagnosis of induction motor faults through monitoring the variations in motor's parameters when it is subjected to an open circuit or short circuit faults. These parameters include stator and rotor resistances, self-inductances, and mutual inductance. The genetic algorithm and the trust-region method are used for the estimation process. Simulation results confirm the efficiency of both the genetic algorithm and the trust-region method in estimating the motor parameters; however, better performance in terms of estimation time is obtained when the trust-region method is adopted. The results also show the possibility of extracting fault signatures from the motor's parameter values because each type of the mentioned faults has a different impact on these parameters. Under a 10% short circuit fault condition, the mutual inductance and rotor resistance deviate by almost 10% from their original values to lower values. While the stator resistance noticeably reduces by up to 20% during the open circuit fault condition.

Parameter Identification Based Online Noninvasive Estimation of Rotor Temperature in Induction Motors

This article proposes a rotor temperature estimation method for in-service induction machine (IM) based on parameter identification, which combines the advantage of recursive least squares (RLS) and model reference adaptive system (MRAS). The RLS with forgetting factor is firstly adopted to identify the parameters of motor inductances. Then, the online identification of rotor resistance can be realized via the MRAS based on the instantaneous reactive power (IRP) and the proportional integral (PI) regulation adaptive law designed by the Popov hyper-stable theory. Thereby, the rotor temperature is computed by the resistance-temperature relationship of metals. To achieve a fast convergence of the parameter identification, rotor slot harmonics are extracted from the stator current and used to determine the rotor speed in real time. Furthermore, to obtain a more accurate initial value of the stator and rotor leakage inductances and resistances, the first 5–15 cycles of the IM starting process are used to mimic the locked-rotor test condition. A merit of the proposed method is that it requires significantly less time to estimate the rotor resistance than the traditional methods. With a novel test bench, experimental validation is performed on a 22-kW IM. In the test, the rotor temperature is measured in three different ways: 1) wireless sensors inserted in the rotating rotor core and rotor end rings, 2) infrared sensor for rotor end ring temperature, and 3) PT100 installed in stator end winding. With this test bench, the real rotor temperature was revealed, and the effectiveness of the presented method is also verified.

Fuzzy logic direct torque/power control for a self-excited induction generator driven by a variable wind speed turbine

This paper presents a new direct fuzzy control scheme for a decentralized wind power generation system with a wide operation range of wind speed variations. The proposed scheme makes use of direct fuzzy torque and power control laws to improve the performance of the system and more particularly the quality of energy inserted into the electrical grid. The direct fuzzy torque control law is used to generate the control signal of the converter on the generator side in order to extract the maximum power available at the turbine and also to maintain the stator flux of the machine at an acceptable level while the direct fuzzy power control law of the converter is used on the grid side to obtain a power efficiency close to unity. A comparison of simulation results between the proposed control method and the classical direct control method found in the literature, shows that the proposed control method provides better performance by improving trajectory tracking as well as robustness against variations in the internal parameters of the asynchronous generator (rotor resistance and stator resistance). It also ensures a supply of quality electrical energy into the electrical grid.

Extended Kalman filter based estimations for improving speed‐sensored control performance of induction motors

In this study, an extended Kalman filter (EKF)-based estimation algorithm is presented to improve the speed-sensored control performance of induction motors (IMs). The proposed EKF-based estimation algorithm is to simultaneously estimate the stator stationary axis components of stator currents and rotor fluxes, rotor angular speed, load torque including viscous friction term, rotor resistance and magnetising inductance in a single EKF algorithm without requiring any switching operation or a hybrid structure. In order to improve the speed-sensored control performance, the measurement/output matrix of IM model is extended by the measured rotor speed in addition to stationary axis components of the measured stator currents. Therefore, the proposed EKF algorithm uses the speed and stator current errors between the measured and priori estimation values in order to calculate the posterior estimation ones. For performance evaluation, the eighth order (proposed) EKF algorithm is tested by simulations and real-time experiments under challenging scenarios and compared with the developed sixth order EKF in real time. The obtained real-time results also show that the eighth order (proposed) EKF algorithm provides additional and improved estimations with the increased but feasible execution time in terms of the sixth order EKF designed in this paper.

Online-Identification of Electromagnetic Parameters of an Induction Motor

Incompliance of the settings of the system to control actual values of the parameters of a variable frequency induction electric drive may sometimes result in complete non-operability of a variable frequency electric drive as well as in the considerable reduction of the dynamic quality parameters. Such parameters as active rotor resistance, rotor inductance, and inductance of the magnetization circuit are available for the immediate measuring. They are not identified in terms of the acceptance tests, and the values presented in catalogues and reference books are calculated ones that may differ considerably from the real values of a certain machine. Despite constant studies by the researchers, a task to identify electromagnetic parameters of the equivalent circuit of an induction motor is still important and topical. The objective of the paper is to develop a method of online-identification of the electromagnetic parameters of an induction motor making it possible to implement accurate regulator adjustment of the frequency control system in terms of operational changes in the driving motor parameters. For the first time, the paper analyzes a steady mode of induction motor operation which does not apply T-network of the equivalent circuit of an induction motor. An approach has been proposed relying on the equation of an induction motor in three-phase fixed coordinate system obtained on the basis of the theory of generalized electromechanical converter.

Online Rotor and Stator Resistance Estimation Based on Artificial Neural Network Applied in Sensorless Induction Motor Drive

This paper presents a new approach method for online rotor and stator resistance estimation of induction motors using artificial neural networks for the sensorless drive. In this method, the rotor resistance is estimated by a feed-forward neural network with the learning rate as a function. The stator resistance is also estimated using the two-layered neural network with learning rate as a function. The speed of the induction motor is also estimated by the neural network. Therefore, the accurate estimation of the rotor and stator resistance improved the quality of the sensorless induction motor drive. The results of simulation and experiment show that the estimated speed tracks the real speed of the induction motor; simultaneously, the error between the estimated rotor and stator resistance using neural network and the normal rotor and stator resistance is very small.

Robust ANFIS Vector Control of Induction Motor Drive for High-Performance Speed Control Supplied by a Photovoltaic Generator

This paper presents the vector control of Induction Motor (IM) supplied by a photovoltaic generatorwhich is controlled by an adaptive Proportional-Integral (PI) speed controller. The proposed solution is used toovercome the induction motor rotor resistance variation problem, which can affect negatively the performanceof the speed control. To overcome the rotor resistance variation, an adaptive Proportional-Integral controller isdeveloped with gains adaptation based on Adaptive Neuro-Fuzzy Inference System (ANFIS) in order to guaranteea high performances of electric drive systems against the parametric variations. The proposed control algorithmis tested by Matlab-Simulink. Analysis of the obtained results shows the characteristic robustness to disturbancesof the load torque and to rotor resistance variation compared to the classical PI control and Model ReferenceAdaptive System (MRAS) rotor resistance observers.

Analysis aerodynamics diffuser-augmented wind turbines

A complete and consistent, one-dimensional momentum theory is derived for the aero-dynamics of slotted diffuser-augmented wind turbine (sDAWT). This theory does not require empirical relations. It results in a set of three-parameter relations for aerodynamic characteristics such as power coefficient Cp , rotor resistance k, rotor axial force coefficient CT , axial induction factor α, wake-expansion factor β, duct axial force coefficient CT,duct and slot mass flux . The theory predicts that the maximum achievable power coefficient Cp of (s)DAWT’s increases monotonically with increasing β, surpassing the Betz limit of open-rotor wind turbines (ORWT’s), already for modest (>2) β’s. The slot of an sDAWT feeds outside air into the diffuser, which for given β decreases the flow through the rotor and therewith Cp . However, the flow through the slot delays the onset of flow separation in the diffuser, increasing the maximum achievable β and therewith the power coefficient of sDAWT’s beyond that of DAWT’s.Based on a vortex model of the (s)DAWT, an expression is derived for the velocity induced at the rotor plane by the diffuser and for the corresponding circulation of the diffuser.The derived three-parameter relations for sDAWT’s reduce to two-parameter relations for DAWT’s and the familiar one-parameter relations for ORWT’s.

Linear parameter varying sensorless torque control for singularly perturbed induction motor with torque and flux observers

In this paper, a new approach being different from the concept of DTC and IFOC for a robust torque control design for induction motor is addressed. The design is based on the framework of singularly perturbed system theory and linear varying parameter systems. In these systems, the rotor flux is considered to be a time-varying parameter in order to guarantee a robust torque control with LPV flux observer with respect to the speed and resistance variations. In fact, this observer is designed to estimate the rotor flux as well as an MRAS observer is introduced to estimate the mechanical speed and rotor resistance. The main feature of this proposed structure is the enhancement of robustness with flux, speed and rotor resistance variation. This improvement leads to a considerable decrease of the torque ripples and ensures the stability for the entire operating range. The obtained simulations and experimental results are used to validate the effectiveness of the proposed control strategy.

Deadbeat-Based Model Predictive Voltage Control for a Sensorless Five-Phase Induction Motor Drive

This paper introduces a direct model predictive voltage control (DMP VC) for a sensorless five-phase induction motor drive. The operation of the proposed sensorless DMP VC is based on the direct control of the applied stator voltages instead of controlling the torque and flux as in model predictive direct torque control (MP DTC). Thus, the simplicity of the control system is enhanced, which saves the computational time and reduces the commutation losses as well. The methodology based on which the proposed sensorless DMP VC performs its operation depends on minimizing a cost function that calculates the error between the reference and actual values of the direct and quadrature (d-q) axes components of stator voltages. The reference values of d-q components of stator voltages are obtained through incorporating the deadbeat control within the proposed model predictive system. A robust back-stepping observer is proposed for estimating the speed, stator currents, rotor flux, and rotor resistance. The validity of the proposed sensorless DMP VC is confirmed through performing detailed and extensive comparisons between the proposed DMP VC and MP DTC approach. The obtained results state that the drive is exhibiting better performance under the proposed DMP VC with less ripples content and reduced computational burden. Moreover, the proposed back-stepping observer has confirmed its effectiveness in estimating the speed and other variables for a wide range of speed operation.