Rotor Time Constant Estimation Research Articles

Optimized Reference Points Based Vector Control of Induction Motor Drive for Electric Vehicle

In this paper, to reduce the power consumption and to improve the efficiency in both steady state and transient condition, optimized operating point selection based control of induction motor is presented. Firstly, the steady state non-linear loss function, which incorporates iron loss and saturation is solved for steady state optimized operating point (OOP) references. To enhance the maximum torque along with reduction in energy consumption during low speed transients, over fluxing based OOP reference selection is proposed. To overcome the adverse impact of over fluxing, in the decoupled control and to make the selection process robust, model reference adaptive system (MRAS) is used for parallel estimation of rotor time constant and stator resistance. Super twisting sliding mode observer (ST-SMO) is incorporated for speed estimation, which is also utilized as reference model (rotor time constant estimation) and adjustable model (stator resistance estimation) in MRAS based observer. This OOP reference selection method is implemented along with the rotor field-oriented control (RFOC) for the induction machine. From the simulation and experimental results, it is justified that the presented algorithm reduces the power consumption and improves the efficiency at all the modes of operation of electric vehicles.

An improved Sliding Mode Observer for parameter estimation in induction motor drive with optimised gains

ABSTRACT This paper represents the online parameter identification and continuous updating in the controller of Induction Motor Drives (IMD). The online measure of parameters improves the operation of the speed estimator, particularly nearer to the zero speed, and also computes the adaptive slip angular frequency. The parameter of speed estimation is performed by the improved Optimized Constant Rate Reaching Law (OCRRL)-based sliding mode observer (SMO), and electrical parameters of stator resistance, mutual inductance, and rotor time constant estimation is performed by Improved Adaptive SMO (IASMO). To enhance the monitoring reliability driven by parameter mismatches, an Online Parameter Estimation Control (OPEC) is presented. Lyapunov’s stability function is used to develop OPEC’s motor parameter adaptive rule. The conventional SMO suffers from the problem of higher chattering phenomena at the sliding surface, especially at very low and zero speeds. An improved OCRRL-based SMO dissolves this issue. Further, to enhance the performance by eliminating the time required for manual tuning of gains of observers in IASMO and PI controllers in Indirect Field Oriented Control (IFOC) are obtained by the Grey Wolf Optimization (GWO) technique. The effectiveness and performance of the proposed observers are tested and verified for possible operating conditions.

Online induction motor rotor time constant estimation using perturbation-based extremum seeking control

<p class="Abstract"><span lang="EN-US">A novel online induction motor (IM) rotor time constant estimator based on a perturbation-based extremum seeking control (ESC) and model reference adaptive system (MRAS) is proposed. Since implementations of fieldoriented control (FOC) requires accurate values of IM parameters, such as rotor time constant, so accurate and robust on-line estimations of such parameters are crucial for any modern industrial IM drives. The proposed MRAS estimator employs ESC method to estimate the IM rotor resistance in various operating conditions. Meanwhile, since extremum seeking control is a model-free scheme, so it is robust to other IM parameter variations. The feasibility and effectiveness of the IM rotor resistance estimation by utilizing ESC scheme has been verified by simulation and experimental results. A 2.2 kW experimental setup has been implemented. </span></p>

Synchronous reference frame sliding mode observers for the inverse of the rotor time constant of the induction motor

The paper discusses the problem of inverse rotor time constant estimation for the induction motor (IM) and presents two sensorless sliding-mode observers (SMOs) that are constructed using synchronous reference frame models. Estimation is done assuming that the magnitude of the flux is available. A voltage model observer is used to estimate the αβ fluxes: these are used to compute the field-orientation angle and the flux magnitude. The paper develops an observer based on the first-order model; however, this does not perform well under parameter variations. A second observer is developed using an augmented model (which now involves the speed of the motor) - this is transformed into a sensorless design by feeding it with a speed estimate (assumed inaccurate). It is shown how to design the feedback gains in order to reduce the sensitivity of the estimate to the input speed error. The theoretical developments are supported with simulations and experiments.

Synchronous reference frame sliding mode observers for the inverse of the rotor time constant of the induction motor

The paper discusses the problem of inverse rotor time constant estimation for the induction motor (IM) and presents two sensorless sliding-mode observers (SMOs) that are constructed using synchronous reference frame models. Estimation is done assuming that the magnitude of the flux is available. A voltage model observer is used to estimate the αβ fluxes: these are used to compute the field-orientation angle and the flux magnitude. The paper develops an observer based on the first-order model; however, this does not perform well under parameter variations. A second observer is developed using an augmented model (which now involves the speed of the motor) - this is transformed into a sensorless design by feeding it with a speed estimate (assumed inaccurate). It is shown how to design the feedback gains in order to reduce the sensitivity of the estimate to the input speed error. The theoretical developments are supported with simulations and experiments.

Real-time implementation of MRAS rotor time constant estimation for induction motor vector control based on a new adaptation signal

PurposeThe major disadvantage of the field-oriented control (FOC) scheme of induction motors is its dependency on motor parameter variations because of the temperature rise. Among the motor parameters, rotor resistance is a parameter that can degrade the robustness of FOC scheme. An inaccurate setting of the rotor resistance in the slip frequency may result in undesirable cross coupling and performance degradation. To overcome this disadvantage, the purpose of this paper is to propose a model reference adaptive system (MRAS) rotor time constant tuning to improve the induction motor drive performance and to compensate the flux orientation error in vector control law.Design/methodology/approachFirst, the dynamic model and the indirect field-oriented control of induction motor are derived. Then, an inverse rotor time constant tuning is proposed based on MRAS theory where a new adaptation signal formulation is used as reference model, and the estimated stator currents obtained from induction motors (IM) state space resolution is used in the adaptive model.FindingsThe effectiveness and robustness of IM speed control with the proposed MRAS inverse rotor time constant estimator is verified through MATrix LABoratory/Simulink model simulation and laboratory experimental results. The simulation and experimental results show good transient drive performances, satisfactory for rotor resistance estimation and robustness with regard to uncertainties and load torque disturbance.Originality/valueThis paper presents an online tuning of the inverse rotor time constant using a new adaptation signal MRAS model. The proposed estimator is proved to guarantee the stability for different operating conditions, especially in very low/zero speed region and heavy load torque. The stability analysis of the proposed estimation procedure is also demonstrated.

A Reactive Power Based Reference Model for Adaptive Control Strategy in a SEIG

In this paper, a new control strategy is proposed for a three-phase squirrel-cage self-excited induction generator (SEIG) connected to a variable speed wind turbine in autonomous mode. In order to improve the dynamic performance of the mentioned vector control system, a model reference adaptive controller is used for online rotor time constant estimation. Thus, the main drawbacks of this method, which include the effects of the changes in machine parameters on rotor flux estimation, slip speed, the creation of instability problems and the system leaving vector control mode, are resolved. In this control strategy, a PI controller is used to control the dc voltage and three similar hysteresis current controllers (HCC) are used to control the switching of IGBTs. The results of the dynamic simulation indicate the desirable performance of the proposed system.

Design and implementation of a MRAS sliding mode observer for the inverse of the rotor time constant of the induction motor

The paper presents an estimator for the inverse of the rotor time constant of the induction motor. Estimation is done using a sliding mode observer under the assumption that the stationary frame fluxes are known. With measured voltages, currents, and with known fluxes and speed, the paper develops an MRAS-type sliding mode observer. This works well under ideal conditions; however, if the speed is inaccurate or if the magnetising inductance saturates, the accuracy suffers. The paper develops a model for the saturated induction motor and attempts to also estimate the saturation level. In the second part, an observer with only a single set of feedback terms is developed. This is transformed into a sensorless observer by feeding it with a speed estimate (assumed inaccurate). The error in the estimated rotor time constant can be reduced by operating the motor drive with a low ratio of id to iq.

Design and implementation of a MRAS sliding mode observer for the inverse of the rotor time constant of the induction motor

The paper presents an estimator for the inverse of the rotor time constant of the induction motor. Estimation is done using a sliding mode observer under the assumption that the stationary frame fluxes are known. With measured voltages, currents, and with known fluxes and speed, the paper develops an MRAS-type sliding mode observer. This works well under ideal conditions; however, if the speed is inaccurate or if the magnetising inductance saturates, the accuracy suffers. The paper develops a model for the saturated induction motor and attempts to also estimate the saturation level. In the second part, an observer with only a single set of feedback terms is developed. This is transformed into a sensorless observer by feeding it with a speed estimate (assumed inaccurate). The error in the estimated rotor time constant can be reduced by operating the motor drive with a low ratio of id to iq.

Model Reference Adaptive Controller Based Rotor Resistance Estimation for Vector Controlled Induction Motor Drive Using Artificial Intelligence

For high performance application in industries induction motor with indirect field oriented control is used due to its excellent dynamic behavior. However, it is sensitive to changes in rotor time constant and has to be estimated online. In this paper a scheme based on the reactive power model reference adaptive controller is designed for estimating the rotor time constant. One of the major advantages of the reactive power adaptive controller is that the rotor time constant estimation is not affected due to the change in stator resistance. The estimation requires only the measurement of motor terminal voltage and current. The effectiveness of the TS fuzzy controller as an adaptive mechanism for estimation of rotor resistance during four quadrant operation of motor drive is investigated in Matlab/Simulink environment and is compared with the conventional PI and Mamdani fuzzy controller.

Robust On-line Rotor Time Constant Estimation for Induction Machines

This paper proposes an on-line rotor time constant estimation strategy for indirect field oriented induction machines. The performance of the indirect field oriented control is dependent especially on the rotor time constant whose value varies according to the temperature. The proposed method calculates the difference between the nominal rotor time constant and the real value from the d- and q-axis integration terms of a proportional integral (PI) current regulator and the demanded voltages of the induction machine to regulate the current in the steady state. Because the proposed strategy has a simple structure and is available in wide speed and torque ranges, the proposed method can be easily used in the industrial field. The effectiveness of proposed strategy is verified with simulations and a 7.5kW experimental setup.

Induction-Motor Rotor Temperature Estimation Using Superheterodyne Receivers

A rotor temperature estimator is proposed in this paper for grid-connected squirrel-cage induction motors during dynamic or steady-state operations. The method utilizes a pipelined architecture with two superheterodyne receivers that operate on a common complex current vector input. The first superheterodyne receiver detects motor speed by extracting an instantaneous rotor-slot-harmonic frequency from the complex current vector. The second superheterodyne receiver extracts a complex fundamental current vector from the same complex current vector. Given a few known motor parameters and a complex voltage vector, a model-reference adaptive system then produces an estimate of the rotor time constant from the superheterodyne receivers' outputs. Finally, the rotor temperature is derived from the estimated rotor time constant via a correlation between the rotor temperature and its resistance. Experimental results demonstrate that the proposed method is capable of estimating induction-motor rotor temperature on a sample-by-sample basis without using temperature or speed sensors.

MRAS-Based Rotor Time Constant Estimation for Indirect Vector Controlled Induction Motor Drive

Decoupling the stator current into magnetizing current and torque current, the vector control technique improves the performance of AC drive system effectively. However, the rotor time constant varies widely with rotor temperature and the flux level of the machine, which decreases the quality of the drive system. By the contrastive analysis of the variable current on-line estimation methods, this paper uses the Model Reference Adaptive System (MRAS) and designs a set of self-adaption estimation arithmetic which has its basis on the Lyapunov theorem of stability. The simulation shows that the estimation arithmetic has the characteristics of fast convergence speed, few stability errors, good track performance and etc. On the basis of simulation of the rotor time constant on-line estimation, this paper designs the system of vector control with the rotor time constant on-line estimation and has the simulation. According to the simulation results, applying the estimation to the vector control system can improve the performance of the system effectively and establish the theoretical basis of the research on the high-performance AC drive system.

Application of RBF Network in Rotor Time Constant Adaptation

The paper presents the results of the rotor time constant adaptation method with the application of artificial neural network. Theestimation of the rotor time constant for adaptive model of MRAS is realized by the help of PI-controller and then is replaced by theRadial Basis Function network. The estimated rotor time constant is then used in the vector control of electrical drive. There werediscussed the different architectures of RBF network in the field of adaptation of rotor time constant parameter. Simulations have beenperformed in the Matlab-Simulink. Ill. 20, bibl. 8 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.113.7.606

Sensorless Control of Induction Machines using a Reduced Order Extended Kalman Filter for Rotor Time Constant and Flux Estimation

Sensorless Control of Induction Machines using a Reduced Order Extended Kalman Filter for Rotor Time Constant and Flux Estimation

Real-time Estimation of Rotor Time Constant and Flux of an Induction Motor: Experimental Results

In this study, a reduced-order discrete-time Extended Sliding Mode Observer (ESMO) is introduced for on-line estimation of rotor fluxes and rotor time constant. The satisfying simulations and experimental results carried out on a 5.5 kW induction motor demonstrate the excellent performance and high robustness of the proposed ESMO against parameter variations, modeling uncertainty and measurement noise. It is concluded that the implementation in real-time of this reduced-order ESMO in the industrial applications, compared with the full-order ESMO, permit on the one hand to overcome the heavy computational effort, complexity and hard tuning of the estimation algorithm and on the other hand, to reduce the execution time of the observation with a good accuracy and considerable rapidity.

Passivity-Based Rotor Time Constant Estimation and Adaptive Position Control of Induction Machines

This paper presents an adaptive controller based on the passivity theorem to control the position of an induction machine. Firstly, an open-loop flux observer estimates the rotor flux linkages, and then adaptive laws are designed to estimate the inverse rotor time constant, mechanical parameters, and load torque. The passive properties of the feedback connection of the rotor flux observer to the inverse rotor time constant estimator, and the adaptive controller are analyzed by the passivity theorem. The overall control system is formally verified to be globally stable by the theorem instead of Lyapunov-like functions. Experimental results show that the parameter estimation errors converge to zero when the position command is a sinusoidal signal with two distinct frequencies. Furthermore, good position tracking responses can be obtained, and the approach is robust with regard to the variation of the parameters and load torque disturbances.

Performance of a reactive power-based adaptive estimation of inverse rotor time constant for vector controlled induction motor drives

A detail investigation on an adaptive estimation of rotor time constant is presented here. The adaptation mechanism forms a Model Reference Adaptive System (MRAS) for the online estimation of inverse rotor time constant for high performance Indirect Vector Controlled Induction Motor Drive. The instantaneous and steady state reactive powers are utilised in the proposed MRAS. A merit of the scheme is that the flux computation is not required in both the models (reference model and adjustable model) of MRAS. So, the low speed estimation problems like drift and saturation of integrator (related to flux estimation from voltage model) are overcome. The use of reactive power as a functional candidate of MRAS naturally makes the scheme independent of stator resistance. The workability of the proposed MRAS is verified through extensive simulation and experiment. The stability of the system is investigated and a study on the sensitivity to stator and rotor parameters is reported. The technique is simple and can be implemented in the existing indirect vector controlled system without any additional hardware.

Robust Feedback linearization and Observation Approach for Control of an Induction Motor

This study presents a feedback linearization strategy and a robust controller to permit a decoupling and regulation of the motor states in order to assure a good dynamic performance and stability of the global system. As the control required the knowledge of the instantaneous flux of the rotor and the rotor parameter estimation can improve the control quality, a six-dimensional discrete-time extended sliding mode observer is proposed for on-line estimation of rotor fluxes and rotor time constant. The simulation results for a 1.8 kW induction motor are presented to illustrate the validity and the high robustness of the proposed approach against parameter variations and disturbances.

A robust nonlinear observer for states and parameters estimation and on-line adaptation of rotor time constant in sensorless induction motor drives

This paper presents a robust non linear observer for variables and parameters estimation in sensorless Indirect Field Oriented Control (IFOC) of induction motors (IM). Based on the reduced order of the IM model, the rotor fluxes and time constant are estimated with the High Gain Observer (HGO) using only the stator currents and voltages. This reduced order model offers many advantages for real time identification and fault diagnosis of the IM. The major contributions of this work are: first, avoid the use of fluxes and speed sensors which increases the installation cost and degrades the mechanical robustness. Second, by reducing the order of the IM model, the implementation of the proposed observer doesn’t require a very effective Digital Signal Processor (DSP). Finally, we show that the proposed control scheme is not sensitive to disturbances and parametric errors and it is robust against load variations and measurement noises. Simulation results are provided to prove the effectiveness of the proposed method.