Stator Flux Estimation Research Articles

Implicit predictive flux control for high-performance induction motor drives

The paper aims to present a new formulation of a model predictive control for induction motor (IM) drives. The proposed control approach is based on utilizing the stator flux components as control variables; consequently, the cost function can be formulated in terms of only flux terms avoiding the use of weighting factor usually present in the model predictive direct torque control (MP DTC) techniques. The motor is modelled considering stator iron losses. An effective stator flux estimator is used to enhance the flux predictive control. A loss minimization criterion (LMC) is proposed in order to minimize the machine losses, especially at light load operation. In order to simplify the overall control scheme, the PWM strategy is eliminated and new model predictive flux control (MP FC) is implemented by the finite control set principle which enables the direct selection of voltage vectors among those (eight) delivered by the inverter. To prove the validity of the proposed MP FC, a detailed comparative study has been carried out between the performances of the IM drive under the classic MP DTC and the proposed MP FC control approaches (with and without the LMC). Dynamic performance of the drive is firstly tested by MATLAB/Simulink; then, a dSpace 1104 fast control prototyping board is used for the experimental verifications. The obtained results approve the improved dynamic performance of the IM drive under the proposed MP FC technique in comparison with the MP DTC.

Sensorless Synchronous Reluctance Motor Drives: A Projection Vector Approach for Stator Resistance Immunity and Parameter Adaptation

This article presents a general projection vector framework for the analysis of flux and position observers applied to sensorless control of synchronous reluctance (SyR) machines, with emphasis to parametric errors sensitivity. The stator resistance immunity property of Adaptive Projection vector for Position error estimation (APP) technique is demonstrated in maximum torque per ampere (MTPA) conditions. Out of MTPA, additional resistance adaption is devised for accurate estimation of stator flux and torque. Alternatively, inductance adaptation might be preferred to resistance's, when dealing with inaccurate motor flux-maps. Inductance adaptation is shown to decrease the steady-state position error. All the proposed APP observers with adaptation techniques are subjected to stability analysis. The merit and the feasibility of the proposed scheme are experimentally demonstrated on a 1.1-kW SyR machine test bench.

Adaptive Fuzzy Controller Based Self Regulated Reference Stator Flux Estimator of Direct Torque Control for Three Level Inverter Fed IPMSM

Adaptive Fuzzy Controller Based Self Regulated Reference Stator Flux Estimator of Direct Torque Control for Three Level Inverter Fed IPMSM

Performance Analysis of Encoderless DTC of IPMSM for Wide Operating Range

In this paper, a look-up table-based direct torque control (DTC) of interior permanent magnet synchronous motor (IPMSM) drive is reported. An approach is made to develop a sensorless four-quadrant electric drive for a wide operating speed range. In order to ensure efficient operation of IPMSM, maximum torque per ampere and field weakening algorithms are employed. The constraints associated with pure integrator in DTC are discussed, and an adaptive controller-based approach to estimating stator flux is proposed. A bidirectional DC–DC converter is implemented to allow four-quadrant operation of drive. In order to realize sensorless operation, stator current-based model reference adaptive control is employed to estimate the motor speed. Speed reversal, torque reversal, above-base-speed operation and low-speed operation of IPMSM drive are considered in this paper. The proposed algorithm is implemented in the MATLAB and Simulink, and the soundness of the suggested estimator is presented by simulation results.

Performance evaluation of MRAS and SMO based sensorless PMSM drives

PurposeFor vector control of permanent magnet synchronous motor (PMSM) requires motor speed and rotor position estimation. The precision of the open-loop techniques of the stator flux and speed for vector control PMSM drive drops as mechanical speed decreases. The stator resistance and estimated stator flux values crisscross have a huge effect on the transient and steady-state performance of the drive at lower speed. The framework turns out to be increasingly strong against parameter crisscross and signal noises by using adaptive observers for estimation of speed and flux.Design/methodology/approachThis paper presents a comparison of two-speed observers for the vector control PMSM drive: the sliding mode observer (SMO) and the model reference adaptive system (MRAS). A comprehensive analysis of SMO and MRAS respects dynamic, steady-state performance and robustness, affectability, stability and computational complexity has been introduced. The abstract of the advantages and disadvantages of both observer and their comparative analysis have also been discussed.FindingsDynamic performance steady-state performance and robustness, affectability and stability.Originality/valueThis paper presents a sensorless scheme, namely, MRAS and SMO for control of PMSM drive. These sensorless techniques have been tested for a PMSM motor drive and the motor performance was compared for both techniques. Matlab/Simulink based simulation results conclude that the adaptive methods improve dynamic response, reduces torque ripples and extended speed range.

Improved Direct Torque Control strategy for Wide Range Speed Control of Induction Motor Drives

Induction Motor is popular option for most of the drives applications. It has simple construction but complex control. DC motor like decoupled control of induction motor drives similar to Field Oriented control is possible using Direct Torque Control (DTC) method which is very simple control strategy compared to vector control. The DTC strategy is very useful for automobile and traction applications using IM but due to use of hysteresis band controllers, DTC has problems of torque ripples, variable switching frequency and poor low speed performance. Because of these reasons, DTC is used in such applications for high speed range and not for the whole speed range. An improved DTC strategy suitable for wide range speed control is suggested in this paper which is based on a performance index calculated on the basis of what is the value of THD of stator current, value of operating speed and switching frequency. It uses new five level variable width torque hysteresis band controller and two level variable width hysteresis band flux controller along with new hybrid model for stator flux estimation. This improved strategy is designed to maintain simplicity of conventional DTC and give better performance than it. This new strategy is simulated using Matlab/Simulink

Variable Sampling Frequency Model Predictive Torque Control for VSI-Fed IM Drives Without Current Sensors

For the purpose of improving the reliability, reducing the cost, and stabilizing the switching frequency of induction motors (IMs), a variable sampling frequency model predictive torque control (VSF-MPTC) for two-level voltage source inverter (VSI)-fed IM drives without current sensors is proposed in this article. This method first predicts the stator currents and stator flux by discretizing the mathematical model of the IM and replaces the measured currents and estimated stator flux with one-step delay of the predictive currents and flux, and then adjusts the average switching frequency to a low and quasi-constant level by increasing or decreasing the equivalent sampling frequency. Tedious tuning of weighting factor of the switching frequency in conventional model predictive control can be avoided. Meanwhile, the proposed scheme takes a shorter computation time by dividing the predictive variable into a variable component and a fixed component, which makes it possible to further decrease the minimum sampling period. The experimental results for a 2.2-kW IM are presented to illustrate the effectiveness of the proposed scheme.

A New Approach on Stator Flux Estimation of IPMSMs Considering Magnetic and Cross-Coupling Saturations

This paper deals with estimating the stator flux of interior permanent magnet synchronous machines (IPMSMs) for hybrid electric vehicles (EHV) applications. The magnetic uncertainties due to the magnetic saturation are considered as new terms on the current-flux model of the machine. Considering the new model, an appropriate observer based on extended Kalman like algorithm is proposed to observe those terms. The observed terms are then used on the flux estimator to take into account the effect of magnetic saturation. The observability and the stability of the observer for the proposed system are studied. The simulation and experimental results are presented to illustrate the capacities of the proposed method.

Stator Flux Based Model Reference Adaptive Observers for Sensorless Vector Control and Direct Voltage Control of Doubly-Fed Induction Generator

A position sensorless operation of a doubly-fed induction generator (DFIG) is desired from considerations of cost, maintenance, cabling, and reliability. This article proposes two stator flux based model reference adaptive observers (SF-MRAOs) for the estimation of the rotor speed and position in a stand-alone DFIG. The cross product of the reference and estimated stator flux linkage vectors is fed as controller input in the existing method, thereby, making the observer model nonlinear. The first proposed method, which is based on notch filtering, offers a performance comparable to that of the existing method while reducing the number of voltage and current sensors required. The second proposed method linearizes the error input to the controller, making the controller design straight forward, and also leading to superior performance than the existing methods. The linearized SF-MRAO is shown to work successfully with good dynamic performance in vector control of a stand-alone DFIG. This article also shows that the proposed linearized SF-MRAO can be employed for obtaining the rotor current angle in direct voltage control of a stand-alone DFIG. Simulation and experimental results are presented from a laboratory prototype of a 10-hp DFIG coupled to a squirrel-cage induction motor. The sensitivity of the performance of the proposed linearized SF-MRAO to variations in machine parameters is also studied theoretically and experimentally.

Energy‐efficient single‐stage solar PV powered sensorless PMSM drive for water pumping

This work presents a speed sensorless permanent magnet synchronous motor (PMSM) drive for single-stage solar photovoltaic (PV) powered water pumping. The elimination of speed sensor reduces the system cost and improves the system robustness. The estimation of rotor speed and position is achieved through estimation of stator flux from voltage and current in stationary reference frame. Conventional maximum power point technique uses two sensors for PV array voltage and current sensing. In the presented work, an effort is made to eliminate the PV array current sensor without compromising the system performance. The proposed system is modelled and its performance is simulated in MATLAB/Simulink. The experimental performance is validated on a developed laboratory prototype using a digital signal processor (DS-1202). A comprehensive comparison is made to validate the significance of the proposed work.

A Super-Twisting Sliding-Mode Stator Flux Observer for Sensorless Direct Torque and Flux Control of IPMSM

The scheme based on direct torque and flux control (DTFC) as well as active flux is a good choice for the interior permanent magnet synchronous motor (IPMSM) sensorless control. The precision of the stator flux observation is essential for this scheme. However, the performance of traditional observers like pure integrator and the low-pass filter (LPF) is severely deteriorated by disturbances, especially dc offset. Recently, a sliding-mode stator flux observer (SMFO) was proposed to reduce the dc offset in the estimated stator flux. However, it cannot eliminate the dc offset totally and will cause the chattering problem. To solve these problems, a novel super-twisting sliding-mode stator flux observer (STSMFO) is proposed in this paper. Compared with SMFO, STSMFO can reduce the chattering and fully eliminate the dc offset without any amplitude and phase compensation. Then, the precision of the stator flux and rotor position can be greatly improved over a wide speed region. The detailed mathematical analysis has been given for comparing it with another three traditional observers. The numerical simulations and experimental testing with an IPMSM drive platform have been implemented to verify the capability of the proposed sensorless scheme.

Reduced Sensor-Based PMSM Driven Autonomous Solar Water Pumping System

The nonlinear <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V–I</i> characteristic of solar cell, calls for the use of maximum power point tracking (MPPT) method in order to obtain optimum power from solar photovoltaic (PV) array. Conventional MPPT methods require one voltage and one current sensor. This paper proposes a novel single sensor-based MPPT technique for a PV array fed water pumping using a permanent magnet synchronous motor (PMSM) drive. As the use of encoders, is not preferred for submersible water pumping, this paper uses a sensorless speed and position estimation for speed control of PMSM. The estimation of rotor speed and position, is achieved through the estimation of stator flux from voltages and currents in stationary reference frame. As the conventional flux estimators suffer from the problems, such as saturation, dc drift, and distortion, this paper proposes a mix multi-resonant structure for flux estimation. A sensorless speed control decreases the cost and improves the reliability of the solar water pumping system. The energy extracted from the PV array, is used to drive the PMSM, which rotates the pump coupled to it. Suitability of the proposed system is demonstrated under varying insolation conditions through a prototype developed in the laboratory and utilizing a digital signal processor (dSPACE-1202) for controlling the SWP system.

An Improved Nonlinear Flux Observer Based Sensorless FOC IM Drive With Adaptive Predictive Current Control

This paper presents a novel adaptive predictive current controller (PCC) with improved flux estimator for a sensorless direct field oriented control (DFOC) induction motor (IM) drive. Classical PCC performance depends on the stator resistance of the motor which varies with temperature. In the proposed method, a discrete stator resistance estimator is developed to increase the robustness of the system toward stator resistance variations. An improved nonlinear discrete stator flux estimator is also developed to replace the pure integrator which reduces the initial value and dc offset problems. Sensorless operation of IM drive has advantages of reduced overall cost and increased reliability of motor operation. Dynamic and steady-state performances of the IM under different operating conditions are analyzed in MATLAB/Simulink as well as experimentally using dSPACE1104 controller and have been compared with conventional PCC. The simulation results of the classical and proposed methods are also validated experimentally. Smooth starting, reduced oscillations in speed and flux at low speed operation, fast speed and torque dynamics, robust operation of drive against load and variation in stator resistance, fast and smooth speed reversal are the main advantages of the proposed method over classical PCC-based DFOC IM drive.

Backstepping direct thrust force control for sensorless PMLSM drive

This study presents an analytic designing approach for the sensorless direct thrust force control (DTFC) of permanent magnet linear synchronous motor (PMLSM). A modified stator flux estimator developed by use of an adaptive mechanism and correction factors is devoted to measuring the stator flux linkage and the mover's position. The parameters of the flux estimator are adjusted in advance through an off-line identification process to increase the accuracy of estimation. Based on the principle of backstepping control, the reference q -axis flux command, which is equivalent to the thrust force command, is first obtained from the Lyapunov functional analysis. Then, the reference d -axis flux command is calculated according to the characteristics of stator flux linkage. The voltage control strategy is constructed to stabilise the global system and ensure the convergence of DTFC. Compared to the conventional direct torque/thrust control, the proposed control scheme can apply the space vector modulation to achieve a fixed switching frequency. Consequently, the phenomenon of flux and force ripples inherited from DTFC is improved. The experiment results are provided to validate the proposed control approach. Moreover, a recent work that is based on the optimal control is adopted as a comparison study.

Implementation of direct power control based on stator flux estimation using low-pass filter estimator for doubly fed induction generator–wind energy conversion system

This article deals with the direct power control strategy applied for a grid-connected variable speed wind turbine based on doubly fed induction generator. The proposed method is based on a stator flux estimation algorithm which allows to control the rotor-side converter of the doubly fed induction generator. Several methods of stator flux estimation are based on the integration of the stator back electromotive force signal. However, in practice, the pure integration can cause various problems due to noises, stator resistance uncertainty, unknown initial conditions and measurement errors. Several algorithms, reported in the literature and used to estimate machine stator fluxes, are reviewed and compared. Particular attention is drawn to the low-pass filter–based algorithms that show good performances. In this article, the novelty of the proposed approach is the development of the direct power control–based stator flux estimation method with a low-pass filter. Theoretical analysis and implementation procedures of the proposed method are developed in detail. Simulation results of a variable speed wind turbine based on doubly fed induction generator are performed in MATLAB/Simulink software in order to evaluate the dynamic performances of the proposed control method under wind speed variations. The adopted control strategy is implemented using dSPACE 1104 board and tested for a wind turbine emulator. Experimental results show the effectiveness and the originality of the proposed control strategy.

Extending Low-Speed Self-Sensing via Flux Tracking With Volt–Second Sensing

This paper introduces an enhanced speed self-sensing method that tracks the stator flux linkage in induction machines at very-low speeds. Volt–second sensing technology is used to mitigate the inverter nonlinearity, which is the major source of flux estimation error in the very-low-speed range. By integrating volt–second sensing in the Gopinath style closed-loop flux observer, the rotor speed information with more precision and lower noise is extracted from the estimated stator flux. Experimental results show that the proposed self-sensing method extends the low-speed operating range, reduces the speed and torque ripple, and increases the disturbance rejection capability compared with the traditional self-sensing method based on the voltage integration method and the back electromotive force (EMF) tracking method.

Stator Flux Estimator Using Feed-Forward Neural Network for Evaluating Hysteresis Loss Curve in Three Phase Induction Motor

The operation of induction motors with high performance contributes significantly to the global energy savings but hysteresis loss is one of the factors causing decreased performance. Stator flux density (B) and magnetic field intensity (H) must be plotted to know hysteresis loss quantity. Unfortunately, since the rotor rotates in time series, the stator flux density is unmeasurable quantities, it’s hard to direct sensored this properties because of limited airgap space and costly to install additional instrument. The purpose of this paper is to evaluate the hysteresis loss quantity in induction motor using a novel method of multilayer perceptron feed forward neural network as stator flux estimator and magnetizing current model as magnetic field intensity properties. This method is effective, because it’s non-destructive method, without an additional instrument, low cost, and suitable for real-time motor drive systems. The FFNN estimator response is satisfying because accurately estimate stator flux density for evaluating hysteresis loss quantity including its magnitude and phase angle. By using the proposed model, the stator flux density and magnetizing current can be plotted become hysteresis loss curve. The performance of flux response, speed response, torque response and error deviation of stator flux estimator has been presented, investigated, compared and verified in Simulink Matlab.

Single-Stage PV Array Fed Speed Sensorless Vector Control of Induction Motor Drive for Water Pumping

This paper deals with a single-stage solar powered speed sensorless vector controlled induction motor drive for water pumping system, which is superior to conventional motor drive. The speed is estimated through the estimated stator flux. The proposed system includes solar photovoltaic (PV) array, a three-phase voltage source inverter, and a motor-pump assembly. An incremental-conductance-based maximum power point tracking algorithm is used to harness maximum power from a PV array. The smooth starting of the motor is attained by vector control of an induction motor. The desired configuration is designed and simulated in MATLAB/Simulink platform and the design, modeling, and control of the system are validated on an experimental prototype developed in the laboratory.

Model Reference Adaptive System for the Online Rotor Resistance Estimation in the Slip-Ring Machine Based Test-bench

Motor control algorithms with high dynamics are generally based on two basic approach field oriented control (FOC) and direct torque control (DTC). The idea of the first one is to decompose the stator current based on the rotor flux, the second one controls the torque based on the stator flux. Therefore, the FOC is very sensitive to the parameter accuracy regarding the drive performance. That is why it is crucial to verify the parameter identification in the real environment. On the other hand, the parameter sensitivity of DTC is much smaller since the stator flux estimation requires only the knowledge of the stator resistance. The article focuses on the verification of rotor resistance identification in the FOC based drive system by means of the slip ring machine based test bench. The recommended procedure calculates the torque based on the stator current and flux to implement model reference adaptive system for online rotor resistance estimation without signal injection.

Speed estimation vector-controlled induction motor drive based on fuzzy logic control flux estimator

A current-and-voltage serial-model stator flux estimator, based on fuzzy logic control for a speed estimation stator flux vector-controlled induction motor drive, is proposed in this study. Stator ...