Mechanical Speed Sensors Research Articles

Speed-Sensorless DFIG Wind Turbine for Power Optimization Using Fuzzy Sliding Mode Observer

In practice, speed erroneous measurements in the wind or in the rotor turbine generator, necessarily lead to non-optimal power transmission. This paper presents optimal power control of DWECS (DFIG-based wind energy conversion system), without mechanical speed sensor. In this context, we are interested to develop a speed FSMO (fuzzy sliding mode observer), in order to estimate the DFIG speed. The proposed method linked an IPC (indirect power control) and MPPT without speed subservience and FSMO to assess the rotor speed, for the wind turbine generator Power Control. The results presented are, a comparative study between SMO and FSMO, with robustness test using Matlab/Simulink software.

Efficient Sensorless Speed Control of Induction Motors Using Hybrid Grey Wolf Optimizer and Neural Network

The article addresses an efficient technique to drive a sensorless three phase induction motor with any desired speed and at different loading conditions by controlling both applied voltage and frequency. An artificial neural network (ANN) is developed to instruct the inverter frequency at the required reference speed to achieve maximum efficiency regardless of load torque. The applied voltage is controlled by a Proportional-Integral (PI) controller to drive the motor at the required reference speed and load torque. Speed of motor is estimated by using a model reference adaptive system (MRAS) without mechanical speed sensor to decrease the cost and increase system reliability. Grey wolf optimizer (GWO) is applied to generate the optimal parameters of a MRAS PI controller. Error between reference and actual motor speeds is minimized by optimizing the parameters of a voltage PI controller using GWO. To endorse the significance of the proposed methodology, it is compared with the classical V/f speed control method. The realized results by the proposed method support its applicability to attain maximum efficiency at varies operating conditions. The system is simulated in MATLAB/Simulink environment.

Three-Level DTC Based on Fuzzy Logic and Neural Network of Sensorless DSSM Using Extended Kalman Filter

This paper presents a direct torque control is applied for salient-pole double star synchronous machine without mechanical speed and stator flux linkage sensors. The estimation is performed using the extended Kalman filter known by it is ability to process noisy discrete measurements. Two control approaches using fuzzy logic DTC, and neural network DTC are proposed and compared. The validity of the proposed controls scheme is verified by simulation tests of a double star synchronous machine. The stator flux, torque, and speed are determined and compared in the above techniques. Simulation results presented in this paper highlight the improvements produced by the proposed control method based on the extended Kalman filter under various operation conditions.

Artificial Neural Network Based Sensorless Vector Control of Induction Motor Drive

Controlled induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. For these speed sensorless AC drive system, it is key to realize speed estimation accurately. This paper describes a Model Reference Adaptive System (MRAS) based scheme using Artificial Neural Network (ANN) for online speed estimation of sensorless vector controlled induction motor drive. The neural network has been then designed and trained online by employing a back propagation network (BPN) algorithm. The estimator was designed and simulated in Matlab. Simulation result shows a good performance of speed estimator. Also Performance analysis of speed estimator with the change in resistances of stator is presented. Simulation results show this estimator robust to resistances of stator variations.

Speed Estimation by Using EKF Techniques for Sensor-Less DTC of PMSM with Load Torque Observer

This paper proposes a Direct Torque Control (DTC) of a Permanent Magnet Synchronous Motor (PMSM) without mechanical speed and position sensors. These later are estimated by using the Extended Kalman Filter (EKF) only by measurement of the stator line voltages and currents. Moreover, DTC uses no current controller and no motor parameters other than the stator resistance, which yields a faster torque response and lower parameter dependence than with others motor control techniques. The Kalman filter is an observer for linear and non-linear systems. Also, due to an angle modification scheme with error tracking, the Sensor-less drive system is robust to parameter variations. A load torque can also be estimated by using Luenberger Observer. A simulation model is developed in MATLAB/SIMULINK and is used to verify the basic operation (performance) of the Sensor-less DTC of PMSM

Open-loop neuro-fuzzy speed estimator applied to vector and scalar induction motor drives

Scalar and vector drives have been the cornerstones of control of industrial motors for decades. In both the elimination of mechanical speed sensor consists in a trend of modern drives. This work proposes the development of an adaptive neuro-fuzzy inference system (ANFIS) angular rotor speed estimator applied to vector and scalar drives. A multi-frequency training of ANFIS is proposed, initially for a V/f scheme and after that a vector drive with magnetizing flux oriented control is proposed. In the literature ANFIS has been commonly proposed as a speed controller in substitution of the classical PI controller of the speed control loop. This paper investigates the ANFIS as an open-loop speed estimator instead. The subtractive clustering technique was used as strategy for generating the membership functions for all the incoming signal inputs of ANFIS. This provided a better analysis of the training data set improving the comprehension of the estimator. Additionally the subtractive cluster technique allowed the training with experimental data corrupted by noise improving the estimator robustness. Simulations to evaluate the performance of the estimator considering the V/f and vector drive system were realized using the Matlab/Simulink® software. Finally experimental results are presented to validate the ANFIS open loop estimator.

Advanced Control Scheme for an IPM Synchronous Generator-Based Gearless Variable Speed Wind Turbine

This paper proposes a direct control strategy for an interior permanent magnet synchronous generator-based variable speed wind turbine. In this scheme, the requirement of the continuous rotor position is eliminated as all the calculations are done in the stator reference frame. This scheme possesses advantages such as lesser parameter dependence and reduced number of controllers compared with the traditional indirect vector control scheme. The direct control scheme is simpler and can eliminate some of the drawbacks of traditional indirect vector control scheme. The proposed control scheme is implemented in MATLAB/SimPowerSystems and the results show that the controller can operate under constant and varying wind speeds. Finally, a sensorless speed estimator is implemented, which enables the wind turbine to operate without the mechanical speed sensor. The simulation and experimental results for the sensorless speed estimator are presented.

Fault Detection and Control loop reconfiguration for WECS with PMSG speed sensor fault

This paper describes a fault tolerant controller (FTC) design to enhance the wind energy conversion system (WECS) with Permanent Magnet Synchronous Generator (PMSG) robustness to mechanical rotor speed sensor failure. This proposed sensor FTC strategy is based on the combination of the actual sensor and an adaptive Luenberger observer with a decision-making unit, which detects whether the mechanical sensor is faulty and selects the most accurate generator rotor speed and position for the Indirect Field Oriented control (IFOC) loops. Extensive simulation study shows that the proposed sensor FTC approach can efficiently detect the generator speed sensor fault and tolerate this type of fault, and so offers a simple configuration with a satisfactory accurate reference-rotor-speed tracking requirement for maximum power extraction.

Research on an Improved Method for Permanent Magnet Synchronous Motor

In permanent magnet synchronous motor (PMSM) traditional vector control system, PI regulator is used in the speed loop, but it has some defects. An improved method of PMSM vector control is proposed in the paper. The active-disturbance rejection control (ADRC) speed regulator is designed with the input signals of given speed and real speed and the output of given stator currentqcoordinate component. Then, in order to optimize ADRC controller, the least squares support vector machines (LSSVM) optimal regression model is derived and successfully embedded in the ADRC controller. ADRC observation precision and dynamic response of the system are improved. The load disturbance effect on the system is reduced to a large extent. The system anti-interference ability is further improved. Finally, the current sensor CSNE151-100 is selected to sample PMSM stator currents. The voltage sensor JLBV1 is used to sample the stator voltage. The rotor speed of PMSM is measured by mechanical speed sensor, the type of which is BENTLY 330500. Experimental platform is constructed to verify the effectiveness of the proposed method.

Sensorless Fuzzy Direct Torque Control for High Performance Electric Vehicle with Four In-Wheel Motors

This paper describes a control scheme of speed sensorless fuzzy direct torque control (FDTC) of permanent magnet synchronous motor for electric vehicle (EV). Electric vehicle requires fast torque response and high efficiency of the drive. Speed sensorless FDTC In-wheel PMSM drives without mechanical speed sensors at the motor shaft have the attractions of low cost, quick response and high reliability in electric vehicle application. This paper presents a new approach to estimate the speed of in-wheel electrical vehicles based on Model Reference Adaptive System (MRAS). The direct torque control suffers in low speeds due to the effect of changes in stator resistance on the flux measurements. To improve the system performance at low speeds, a PI-fuzzy resistance estimator is proposed to eliminate the error due to changes in stator resistance. High performance sensorless drive of the in-wheel motor based on MRAS with on line stator resistance tuning is established for four motorized wheels electric vehicle and the whole system is simulated by matalb/simulink. The simulation results show the effectiveness of the new control strategy. This proposed control strategy is extensively used in electric vehicle application.

Sensorless induction machine observation with nonlinear magnetic characteristic

SUMMARYThis paper addresses the problem of state estimation in induction motors. Generally, the motor observer design has been dealt based on standard models neglecting the saturation effect in the magnetic characteristic. As a matter of fact, magnetic saturation cannot be ignored especially when considering control strategies (speed and torque) that involve large flux variations. Such large flux variations are necessary to meet optimal operation conditions in the presence of wide range load torque changes. On the other hand, it is well known that use of mechanical (speed and torque) sensors entails reliability issues. In this paper, a new sensorless adaptive observer is designed for induction machine based on a model that accounts for the nonlinear feature in the magnetic circuit. The observer consists of two interconnected state‐dependent gain observers and is formally shown to provide accurate estimates of the mechanical and magnetic variables using only stator current and voltage measurements. Copyright © 2013 John Wiley & Sons, Ltd.

중성점을 사용하지 않는 BLDC 전동기 센서리스 제어 기법

Generally, brushless DC motor(BLDCM) driving system uses hall sensors or encoders as the mechanical position or speed sensor. It is necessary to achieve the informations of rotor position for driving trapezoidal type brushless DC motor without any position sensor. In this paper, the commutation signals are obtained without the motor neutral voltage, multistage analog filters, A/D converters, or the complex digital phase shift circuits which are indispensable in the conventional sensorless control algorithms. In the proposed method, in stead of detecting the zero crossing point of the nonexcited motor back electromagnetic force for the average motor terminal to neutral voltage, the commutation signal are extracted directly from the specific average line to line voltage with low-pass filter, adder and comparators circuit. In contrast to conventional methods, the neutral voltage is not need; therefore, the commutation signals are insensitive to the common mode noise. Moreover, the complex phase shift circuit can be eliminated. The effectiveness of the proposed method is verified through simulation results.

INDIRECT FIELD-ORIENTED CONTROL OF FIVE-PHASE INDUCTION MOTOR DRIVES

Five -phase ac motor drives are nowadays considered for various applications, due to numerous advantages that they offer when compared to three-phase motors. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the sensor, information of the rotor speed is extracted from measured stator currents and voltages at motor terminals. This paper proposes speed estimation method using model reference adaptive system (MRAS) to improve the performance of a sensorless vector controller of five-phase induction motor (IM). In the proposed method, the stator current is used as the state variable to estimate the speed. Since the stator current error is represented as a function of the first degree for the error value in the speed estimation, the proposed method can provide fast speed estimation and is also, more robust to variations in the parameters, compared with other MRAS methods. Consequently, this method can improve the performance of a sensorless vector controller in a low speed region and at zero-speed. The proposed method is verified by simulation using the Matlab/Simulink package. The performance of the proposed system is investigated at different operating conditions. The proposed controller is robust and suitable for high performance five-phase induction motor drives. Simulation results validate the proposed approaches.

Modified Euler integration based control of a five-phase induction motor drive

In principle, control methods for multi-phase machines are the same as for three-phase machines. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the speed sensor, information of the rotor speed is extracted from measured stator currents and voltages at motor terminals. Vector-controlled drives require estimating the magnitude and spatial orientation of the fundamental magnetic flux in the stator or in the rotor. Open-loop estimators or closed-loop observers are used for this purpose. They differ with respect to accuracy, robustness, and sensitivity against model parameter variations. This paper analyses operation of a modified Euler integrationbased sensorless control of vector controlled five-phase induction machine with current control in the stationary reference frame. A linear neural network has been then designed and trained online by means of back propagation network (BPN) algorithm, differently from that in the literature which employs a nonlinear back propagation network (BPN) algorithm. The Artificial Neural Network (ANN)-Model Reference Adaptive System (MRAS) based sensorless operation of a three-phase induction machine is well established and the same principle is extended in this paper for a five-phase induction machine. Performance, obtainable with hysteresis current control, is illustrated for a number of operating conditions on the basis of simulation results. Full decoupling of rotor flux control and torque control is realised. Dynamics, achievable with a five-phase vector controlled induction machine, are shown to be essentially identical to those obtainable with a three-phase induction machine. International Journal of Engineering, Science and Technology, Vol. 2, No. 6, 2010, pp. 218-230

Rotor Fault Analysis in the Sensorless Field Oriented Controlled Induction Motor Drive

In the paper an analysis of the Direct Field Control of induction motor drive with broken rotor bars is presented. A drive system with and without a mechanical speed sensor is analyzed. In the sensorless induction motor (IM) drive the rotor flux and speed is reconstructed with the use of a MRASCC estimator, where the induction motor is used as a reference model. The stator current estimator and current model of the rotor flux are used as adapted models. Most of the speed estimators used in sensorless drives are sensitive to motor parameter changes, especially to the rotor resistance changes. The proposed MRASCC estimator is very robust to all motor parameter changes, hence it should work properly in a faulty rotor. In the paper simulation and experimental results of the sensorless IM drive with broken rotor bars are presented. Characteristic frequency harmonics of the IM state variables connected with the broken rotor bars are introduced. The low speed region and the dynamic properties of the IM drive with rotor faults are tested. The range of stable work of the control system is shown.

Extended Kalman filter based speeds estimation of series-connected five-phase two-motor drive system

The multi-phase machines enables independent control of a few number of machines that are connected in series in a particular manner, and the supply is fed from a single voltage source inverter (VSI). The idea was first implemented for a five-phase series-connected two-motor drive system, but is now applicable to any number of phases. The number of series-connected machines is a function of the phase number of VSI. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the sensor, information of the rotor speed is extracted from measured stator currents and voltages at motor terminals. Open-loop estimators or closed-loop observers are used for this purpose. They differ with respect to accuracy, robustness, and sensitivity against model parameter variations. This paper analyses operation of an EKF-based sensorless control of vector controlled series-connected two-motor five-phase drive system with current control in the stationary reference frame. Results, obtained with fixed voltage and fixed frequency supply fed and hysteresis current control, is presented for various operating conditions on the basis of simulation. The purpose of this paper is to report first time, the simulation results on a sensorless control of a five-phase two-motor series-connected drive system using EKF estimator.

MRAS Based Sensorless Control of a Series-Connected Five-Phase Two-Motor Drive System

Multi-phase machines can be used in variable speed drives. Their applications include electric ship propulsion, 'more-electric aircraft' and traction applications, electric vehicles, and hybrid electric vehicles. Multi-phase machines enable independent control of a few numbers of machines that are connected in series in a particular manner with their supply being fed from a single voltage source inverter (VSI). The idea was first implemented for a five-phase series-connected two-motor drive system, but is now applicable to any number of phases more than or equal to five-phase. The number of series-connected machines is a function of the phase number of VSI. Theoretical and simulation studies have already been reported for number of multi-phase multi-motor drive configurations of series-connection type. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the sensor, information concerning the rotor speed is extracted from measured stator currents and voltages at motor terminals. Open-loop estimators or closed-loop observers are used for this purpose. They differ with respect to accuracy, robustness, and sensitivity against model parameter variations. This paper analyses operation of an MRAS estimator based sensorless control of a vector controlled series-connected two-motor five￢phase drive system with current control in the stationary reference frame. Results, obtained with fixed￢voltage, fixed-frequency supply, and hysteresis current control are presented for various operating conditions on the basis of simulation results. The purpose of this paper is to report the first ever simulation results on a sensorless control of a five-phase two-motor series-connected drive system. The operating principle is given followed by a description of the sensorless technique.

MRAS-based sensorless control of a vector controlled five-phase induction motor drive

Multi-phase ac motor drives are nowadays considered for various applications, due to numerous advantages that they offer when compared to their three-phase counterparts. In principle, control methods for multi-phase machines are the same as for three-phase machines. Variable speed induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the sensor, information of the rotor speed is extracted from measured stator currents and voltages at motor terminals. Vector controlled drives require estimating the magnitude and spatial orientation of the fundamental magnetic flux waves in the stator or in the rotor. Open-loop estimators and closed-loop observers are used for this purpose. They differ with respect to accuracy, robustness, and sensitivity against model parameter variations. This paper analyses operation of an open-loop and model reference adaptive system (MRAS)-based sensorless control of vector controlled five-phase induction machine with current control in the stationary reference frame. The MRAS-based sensorless operation of a three-phase induction machine is well established and the same principle is extended in this paper for an IRFOC five-phase induction machine. Performance, obtainable with hysteresis current control, is illustrated for a number of operating conditions on the basis of simulation results. Full decoupling of rotor flux control and torque control is realised. Dynamics, achievable with a five-phase vector controlled induction machine, are shown to be essentially identical to those obtainable with a three-phase induction machine. Experimental verification is also provided.

Sensorless Control of Induction Machines—With or Without Signal Injection?

Controlled induction motor drives without mechanical speed sensors at the motor shaft have the attractions of low cost and high reliability. To replace the sensor, information on the rotor speed is extracted from measured stator currents and from voltages at motor terminals. Vector-controlled drives require estimating the magnitude and spatial orientation of the fundamental magnetic flux waves in the stator or in the rotor. Open-loop estimators or closed-loop observers are used for this purpose. They differ with respect to accuracy, robustness, and sensitivity against model parameter variations. Dynamic performance and steady-state speed accuracy around zero speed range are achieved by signal injection, exploiting the anisotropic properties of the machine. The overview in this paper uses signal flow graphs of complex space vector quantities to provide an insightful description of the systems used in sensorless control of induction motors.

Sensorless speed control of permanent-magnet motors with nonsinusoidal EMF waveform

A novel sensorless speed-control strategy for permanent-magnet AC motors (PMACMs) is presented. A nonlinear reduced-order observer and a high-gain observer are designed to estimate the induced EMF, without mechanical position or speed sensors. In contrast with previous proposals, the EMF estimation is performed without previous knowledge of its waveform. From the estimated EMF, the rotor speed and the position derivatives of flux are calculated and used for the implementation of a PMACM speed control without mechanical position sensor. The proposed strategy is not limited to PMACM with sinusoidal or trapezoidal EMF waveform. Moreover, it allows the PMACM ripple torque and copper losses to be minimised. The performance of the proposal is validated through simulation and experimental results.