Stator Resistance Estimation Research Articles

Extended Kalman Filter for Sensorless Fault Tolerant Control of PMSM with Stator Resistance Estimation

<p><span>This paper aims to provide a high performance sensorless control based on an Extended Kalman Filter (EKF) applied to fault-tolerant PMSM drive system with stator-resistance estimation. It proposes a fast method of fault switches detection in the power converters. The considered drive is composed of three phases PMSM and a four leg three phase’s inverter when the fourth is the redundant leg. After a short-switch fault occurrence, the redundant leg replaces the faulty leg. The simulation results verify that the proposed control method and the fault tolerant inverter ensure the high reliability and continuously operation of the sensorless vector control PMSM system under inverter fault.</span></p>

Proportional Integral Estimator of the Stator Resistance for Direct Torque Control Induction Motor Drive

In this paper, an improved proportional integral stator resistance estimation for a direct torque controlled induction motor is proposed. This estimation method is based on an on-line stator resistance correction regarding the variations of the stator current estimation error. In fact, the input variable of the PI estimator is the stator current estimation error. The main idea is to tune accurately the stator resistance value relatively to the evolution of the stator current estimation error gradient to avoid the drive instability and ensure the tracking of the actual value of the stator resistance. But there is an unavoidable steady state error between the filtered stator current modulus and its estimated value from the dq model of the machine which is due to pseudo random commutations of the inverter switches. An offset has been introduced in order to overcome this problem, for different speed command values and load torques. Simulation results show that the proposed estimator was able to successfully track the actual value of the stator resistance for different operating conditions

Adaptive direct torque control using Luenberger-sliding mode observer for online stator resistance estimation for five-phase induction motor drives

Direct torque control is considered as one of the variable structure control techniques which are characterized by fast response, simplicity and provide direct control of both electromagnetic torque and stator flux by adequate selection of the inverter switches in each sampling period. In case of multiphase motor drives, the increase in voltage vectors offers flexibility to optimize the selection of the inverter switching states, thereby achieving more precise control of the torque and flux. Nevertheless, the criterion for the selection of the inverter states becomes more complex. This aspect is not considered an issue in the traditional three-phase motor drives but needs to be considered in designing the switching table of the direct torque control of five-phase induction motor. Due to the auxiliary vector plane, the low-frequency harmonics need to be eliminated and full utilization of the dc link voltage is desired. The effects of parameter variation (particularly, stator resistance) on the performance of the direct torque control. It is necessary the addition of parameter adaptation algorithm to compensate this effects. A novel direct torque control of five-phase induction motor using a new switching table combined with an adaptive variable structure observer to avoid the effects of stator resistance variations is presented in this paper. Simulation results provided show the effectiveness of the proposed control strategy.

Sensorless Control of Permanent Magnet Synchronous Machine Based on Second-Order Sliding-Mode Observer With Online Resistance Estimation

In this paper, a supertwisting algorithm based second-order sliding-mode observer (STA-SMO) with online stator resistance ( $ R_{s}$ ) estimation for sensorless control of a nonsalient permanent magnet synchronous machine is proposed. A stator current observer is designed based on an STA to estimate the back electromotive force. A discontinuous sign function in the conventional SMO is replaced by a supertwisting function. The chattering problem, unavoidable in conventional SMO, is eliminated by reducing the amplitude of switching function of an STA-SMO. Meanwhile, a parallel online $ R_{s}$ estimation scheme is presented based on a modified SMO. Because mismatch between actual and set resistance may lead to estimation error and even system instability. The Lyapunov stability theorem is used to obtain the stable conditions of the proposed online $ R_{s}$ observer at both motoring and generating mode. With the help of online $ R_{s}$ observer, resistance uncertainties caused by temperature variation can be taken into account, which means robustness and stability of an STA-SMO can be improved. At the same time, higher position and speed estimation accuracy is obtained and operation range of sensorless control is extended. Finally, the proposed method is validated and compared with a conventional method by simulations and experiments.

An improved sensorless sliding mode control/adaptive observer of a five-phase permanent magnet synchronous motor drive

This paper presents a new sliding mode observer (SMO) for sensorless sliding mode control (SMC) of five-phase permanent magnet synchronous motor (PMSM) with online stator resistance estimation. The proposed approach is shown to guarantee stability in the sense of Lyapunov context. The sliding mode controller considers the nonlinearities of the system. The sliding mode control strategy is developed using an integral switching surface. A sliding mode observer is proposed for the rotor speed and stator resistance estimation under assumptions that only the stator currents and voltages are available for measurement. The effectiveness of the proposed strategy has been successfully verified through simulation results.

Extended Kalman Filter for Sensorless Fault Tolerant Vector Control of PMSM with stator resistance estimation

Extended Kalman Filter for Sensorless Fault Tolerant Vector Control of PMSM with stator resistance estimation

Nonlinear tracking control for sensorless permanent magnet synchronous motors with uncertainties

The recent advanced solution in Marino, Tomei, and Verrelli (2013) to the tracking control problem for sensorless IMs with parameter uncertainties is translated on the basis of letter swap connections between the models of (nonsalient-pole surface) permanent magnet synchronous motors (PMSMs) and induction ones (IMs). The (stability proof-based) nonlinear adaptive position/speed tracking control for sensorless PMSMs (with simultaneous estimation of uncertain constant load torque and stator resistance), which is accordingly obtained by exploring and decoding the design paths in Marino et al. (2013) and which surprisingly represents a simple generalization of the controller in Tomei and Verrelli (2011), constitutes an innovative solution to the related open problem. Illustrative experimental results are included.

Robust simultaneous estimation of stator and rotor resistances and rotor speed for predictive maintenance of sensorless induction motor drives

In this paper, a novel rotor and stator resistances estimator has been proposed for detecting faults while they are still developing or adequate warning of imminent failure and to give minimum downtime and optimum maintenance schedules to apply in sensorless IM drives. The stator resistance estimation is applied for monitoring stator windings temperature and monitoring the status of stator windings insulation of induction motor. On the other hand, broken bars and end-rings are common faults in three-phase induction motors. A parallel model reference adaptive system (MRAS) has been proposed in order for simultaneous estimation of the stator and rotor resistances and rotor speed. The aim of the proposed MRAS is to save the cost of implementation and the processes time. The proposed parallel MRAS depends on the point of slowly variation of the rotor resistance with respect to the rotor speed.

Robust simultaneous estimation of stator and rotor resistances and rotor speed for predictive maintenance of sensorless induction motor drives

In this paper, a novel rotor and stator resistances estimator has been proposed for detecting faults while they are still developing or adequate warning of imminent failure and to give minimum downtime and optimum maintenance schedules to apply in sensorless IM drives. The stator resistance estimation is applied for monitoring stator windings temperature and monitoring the status of stator windings insulation of induction motor. On the other hand, broken bars and end-rings are common faults in three-phase induction motors. A parallel model reference adaptive system (MRAS) has been proposed in order for simultaneous estimation of the stator and rotor resistances and rotor speed. The aim of the proposed MRAS is to save the cost of implementation and the processes time. The proposed parallel MRAS depends on the point of slowly variation of the rotor resistance with respect to the rotor speed.

Novel robust simultaneous estimation of stator and rotor resistances and rotor speed to improve induction motor efficiency

This paper presents a novel method of parallel stator and rotor resistances and rotor speed estimation for robust sensorless induction motor drive. Moreover, the estimated parameters have been used to calculate the optimal rotor flux for improving the motor efficiency. In this scheme, a parallel model reference adaptive system (MRAS) is designed to simultaneous estimation of rotor speed and rotor-stator resistances in order to achieve a high-precise control in a wide range of motor speed. The aim of design of one MRAS for parallel estimation of stator and rotor resistances and rotor speed is to save the implementation cost and to reduce the processes time. Moreover, the stability of the control scheme has been derived based on Popov's criterion to design the adaptation mechanisms. Digital simulation based on Matlab/Simulink is carried out to evaluate the effectiveness of the proposed scheme at different operating conditions. The simulation results demonstrate the effectivity of the proposed scheme at a wide range of speed under load disturbance and parameter variation.

Novel robust simultaneous estimation of stator and rotor resistances and rotor speed to improve induction motor efficiency

This paper presents a novel method of parallel stator and rotor resistances and rotor speed estimation for robust sensorless induction motor drive. Moreover, the estimated parameters have been used to calculate the optimal rotor flux for improving the motor efficiency. In this scheme, a parallel model reference adaptive system (MRAS) is designed to simultaneous estimation of rotor speed and rotor-stator resistances in order to achieve a high-precise control in a wide range of motor speed. The aim of design of one MRAS for parallel estimation of stator and rotor resistances and rotor speed is to save the implementation cost and to reduce the processes time. Moreover, the stability of the control scheme has been derived based on Popov's criterion to design the adaptation mechanisms. Digital simulation based on Matlab/Simulink is carried out to evaluate the effectiveness of the proposed scheme at different operating conditions. The simulation results demonstrate the effectivity of the proposed scheme at a wide range of speed under load disturbance and parameter variation.

Estimation of Rotor and Stator Resistance for Induction Motor Drives using Second order of Sliding Mode Controller

Estimation of Rotor and Stator Resistance for Induction Motor Drives using Second order of Sliding Mode Controller

Sensorless Torque/Speed Control of Induction Motor Drives at Zero and Low Frequencies With Stator and Rotor Resistance Estimations

Stability, robustness, and estimation accuracy of the adaptive flux observer (AFO) for sensorless induction motor (IM) drives are the most critical issues at zero and very low frequencies. In this paper, the design of speed, stator resistance, and rotor resistance estimators, to improve the robustness of AFO to parameters variation, is proposed. These estimators are arranged to have a cascade multi-input multi-output structure, and simplified to a single-input single-output structure for stability analysis and gain selections. To design both the observer feedback gains and adaptive proportional-integral gains, the stability conditions of the estimators are derived to guarantee a stable AFO in all the four quadrants of operation. The sensitivity analysis against stator and rotor resistance variations is also provided. The detailed analytical, simulation, and experimental results are presented to validate the proposed AFO of sensorless IM drives in torque- and speed-controlled modes of operation, particularly at zero and very low frequencies.

A simplified three-level SVM-DTC induction motor drive with speed and stator resistance estimation based on extended Kalman filter

In this paper, a speed-sensorless direct torque control (DTC) drive for induction motors (IMs) fed by three-level neutral-point clamped (NPC) inverter has been investigated. The main objective of the study is to solve two different problems in DTC drive with three-level NPC inverter. First, the conventional switching table fails to consider some limitations caused by the topology of NPC inverter. As a solution to this problem, a new switching method based on simplified three-level space-vector modulation (SVM) technique has been developed by fulfilling both neutral-point potential balance and soft commutation requirements needed for three-level NPC inverters. Other problem is to make accurate estimates, especially in very low and zero speed operation. To address this issue, an extended Kalman filter (EKF)-based observer has been utilized for the estimation of rotor speed, load torque, and flux. The estimated load torque is used to improve the response of speed estimation in both transient and steady states. The stator resistance has also been estimated simultaneously to make more robust and reliable flux estimation. The proposed drive system has been tested under some challenging conditions and verified by the simulation results.

Sensorless Speed Control of Synchronous Motors: Analysis and Mitigation of Stator Resistance Error

Direct torque control-based sensorless speed control (DTC-SSC) of a synchronous motor is a high performance and reliable approach for the control of speed and stator flux modulus. This paper proposes an analytical method to study the effect of error in estimation of stator resistance on the stability of a synchronous motor controlled via DTC-SSC approach, a reliable resistance estimator based on the angle between the stator flux and current vectors with no need to solve nonlinear equations, and a modified structure for sensorless speed control of synchronous motors based on this estimator. Simulation and experimental case studies validate the proposed stability analysis and the resistance estimator.

Parallel Stator Resistance Estimator Using Neural Networks for Rotor Flux Based Model Reference Adaptive System Speed Observer

Model reference adaptive system schemes offer simpler implementation and require less computational effort compared to other speed sensorless methods. The performance of rotor flux based model reference adaptive system schemes at low-speed operation is poor because of parameter sensitivity and presence of the integrator in the reference model. As stator resistance inevitably varies with temperature, for accurate operation at low speeds, an appropriate online identification algorithm for the stator resistance is required. In this article, a neural network based parallel stator resistance and rotor speed estimator has been proposed to simultaneously rectify the limitation of model reference adaptive system schemes, i.e., stator resistance variation and DC offset due to integrator, employing a neutral network in stator resistance estimator and modifying the reference model by adding a compensating voltage term. An indirect sensorless vector control scheme has been simulated and experimentally validated using the dSPACE DS-1104 R&D controller board (dSPACE GmbH, Paderborn, Germany) to verify the performance of drives at different operating conditions.

Estimation of Stator Resistance and Rotor Flux Linkage in SPMSM Using CLPSO with Opposition-Based-Learning Strategy

Electromagnetic parameters are important for controller design and condition monitoring of permanent magnet synchronous machine (PMSM) system. In this paper, an improved comprehensive learning particle swarm optimization (CLPSO) with opposition-based-learning (OBL) strategy is proposed for estimating stator resistance and rotor flux linkage in surface-mounted PMSM; the proposed method is referred to as CLPSO-OBL. In the CLPSO-OBL framework, an opposition-learning strategy is used for best particles reinforcement learning to improve the dynamic performance and global convergence ability of the CLPSO. The proposed parameter optimization not only retains the advantages of diversity in the CLPSO but also has inherited global exploration capability of the OBL. Then, the proposed method is applied to estimate the stator resistance and rotor flux linkage of surface-mounted PMSM. The experimental results show that the CLPSO-OBL has better performance in estimating winding resistance and PM flux compared to the existing peer PSOs. Furthermore, the proposed parameter estimation model and optimization method are simple and with good accuracy, fast convergence, and easy digital implementation.

An Extended Sliding Mode Observer for Speed, Position and Torque Sensorless Control for PMSM Drive Based Stator Resistance Estimator

This paper presents a robust sixth-order Discrete-time Extended Sliding Mode Observer (DESMO) for sensorless control of PMSM in order to estimate the currents, speed, rotor position, load torque and stator resistance. The satisfying simulation results on Simulink/Matlab environment for a 1.6 kW PMSM demonstrate the good performance and stability of the proposed ESMO algorithm against parameter variation, modeling uncertainty, measurement and system noises.

Robust software sensor with online estimation of stator resistance applied to WECS using IM

In this paper, a robust software sensor with online estimation of stator resistance applied to a wind energy conversion system (WECS) using an induction machine (IM) was developed. The mechanical speed control requires a specific estimation of the flux which is dependent on the IM stator resistance. As a consequence, this estimation may face some problems because of the stator resistance variation. In this paper, a robust software sensor was designed and developed for online stator resistance estimation under parametric variations. The estimated flux and mechanical speed as well as stator resistance are given by the software sensor. The robustness and stability study of the suggested software sensor were proven and validated by simulation results.

A Review of the DTC Controller and Estimation of Stator Resistance in IM Drives

<span>In recent years an advanced control method called direct torque control (DTC) has gained importance due to its capability to produce fast torque control of induction motor. Although in these systems such variables as torque, flux modulus and flux sector are required, resulting DTC structure is particularly simplistic. Conventional DTC does not require any mechanical sensor or current regulator and coordinate transformation is not present, thus reducing the complexity. Fast and good dynamic performances and robustness has made DTC popular and is now used widely in all industrial applications. Despite these advantages it has some disadvantages such as high torque ripple and slow transient response to step changes during start up. Torque ripple in DTC is because of hysteresis controller for stator flux linkage and torque. The ripples can be reduced if the errors of the torque and the flux linkage and the angular region of the flux linkage are subdivided into several smaller subsections. Since the errors are divided into smaller sections different voltage vector is selected for small difference in error, thus a more accurate voltage vector is selected and hence the torque and flux linkage errors are reduced. The stator resistance changes due to change in temperature during the operation of machine. At high speeds, the stator resistance drop is small and can be neglected. At low speeds, this drop becomes dominant. Any change in stator resistance gives wrong estimation of stator flux and consequently of the torque and flux. Therefore, it is necessary to estimate the stator resistance correctly. This paper aims to review some of the control techniques of DTC drives and stator resistance estimation methods.</span>