Speed Estimation Of Induction Motor Research Articles

New disturbance observer-based speed estimator for induction motor

<p>This paper discusses a novel disturbance observer designed as an estimator to determine the rotor speed of an induction motor. This observer is a solution to obtain a simple structure with a small number of compact observer gains. Furthermore, the adaptation law is no longer required to estimate induction motor speed values. This is a machine model-based computation method that uses a stationary reference frame. The nonlinearity problem is solved using an additional state vector in the observer model, which is known as an extended state observer. This approach easily and systematically determines the observer gain by applying the linear quadratic regulator (LQR) method, thereby avoiding time-consuming trial errors. The proposed observer, which was presented in both continuous and discrete forms, was tested using a sensorless V/f- controlled induction motor. The simulation results show that the proposed observer can accurately estimate all states, namely, the rotor flux and stator current; therefore, the proposed estimator provides the speed and electromagnetic torque for a wide operational range of speeds and load torques. It was also shown that the proposed observer was robust to noise and uncertainty in induction motor parameters.</p>

Sensorless Speed Estimation of Induction Motors through Signal Analysis Based on Chaos Using Density of Maxima.

Three-phase induction motors are widely used in various industrial sectors and are responsible for a significant portion of the total electrical energy consumed. To ensure their efficient operation, it is necessary to apply control systems with specific algorithms able to estimate rotation speed accurately and with an adequate response time. However, the angular speed sensors used in induction motors are generally expensive and unreliable, and they may be unsuitable for use in hostile environments. This paper presents an algorithm for speed estimation in three-phase induction motors using the chaotic variable of maximum density. The technique used in this work analyzes the current signals from the motor power supply without invasive sensors on its structure. The results show that speed estimation is achieved with a response time lower than that obtained by classical techniques based on the Fourier Transform. This technique allows for the provision of motor shaft speed values when operated under variable load.

Speed Estimation of Induction Motor at Low and Zero Speed using High Frequency Signal Injection for Rotor Slot Harmonics Detection

Rotor position estimation based on high frequency signal injection method represents the interesting way to provide the high performances of the AC drives sensorless controlled at low or near zero speed range. So, this method requires the existence of saliencies inside the IM particularly the presence of the slots where their design constitutes the main advantageous to exploit its effect for rotor speed monitoring. First, the present paper exposes a model of the induction machine including slotting effects which it can be exploited in order to extract the harmonic saliency created by rotor slotting. Second, the high frequency signal injection method is used in order to allow tracking the characteristic harmonic saliency due to rotor slotting from which the rotor position and speed may be estimated. A High frequency voltage signal injection creates a high frequency current modulated by the saliencies presented inside the machine. To extract information about rotor position, the resulting stator current treads to heterodyning process to eliminate the disturbance components and subsequently the rotor position may be extracted by a closed-loop observer. Simulation results are shown in order to verify the validity of the proposal and to confirm the effectiveness of estimation method at zero frequency.

Super-Twisting MRAS Observer-Based Non-linear Direct Flux and Torque Control for Induction Motor Drives

Abstract This research paper proposes a novel design of an efficient combined sliding mode observer (SMO) for induction motor flux and speed estimation. The suggested sensorless technique employs the sliding mode’s second-order approach using a model reference adaptive system (MRAS). The second-order super-twisting control method is free-chattering, which lowers the chattering effect while preserving the same good features as the first-order sliding mode control (SMC). In addition, the conjunction with the MRAS as a separated speed estimator can raise the accuracy and make the observer immune to speed fluctuations, particularly for low-speed applications. Furthermore, in order to achieve effective decoupled flux–torque control, the super-twisting algorithm (STA) was combined with a non-linear feedback linearisation controller for the inner control loop construction. This strategy can boost the control system’s stability and robustness against external disturbances and modelling uncertainty. The performance analysis of the suggested methods has been carried out via simulation and experimental validation utilizing MATLAB/Simulink with the dSpace 1104 real-time interface.

Improving Regenerating Mode Operation of MRAS-Based Induction Motor Speed Estimation Using the Multilayer Technique

Improving Regenerating Mode Operation of MRAS-Based Induction Motor Speed Estimation Using the Multilayer Technique

Instantaneous speed estimation of induction motor by time-varying sinusoidal mode extraction from stator current

When an induction motor operates at variable speed, the fundamental wave and harmonics in the stator current are presented in the form of nonstationary sinusoidal components with time-varying parameters. To estimate the instantaneous speed of the motor utilizing the stator current signal, a time-varying sinusoidal mode extraction (TVSME) method is firstly proposed. In TVSME, a variational model, which compacts the frequency bandwidth of the desired time-varying sinusoidal mode (TVSM) to the narrowest bandwidth and excludes other harmonics as much as possible, is constructed to optimally extract the desired TVSM and to estimate its instantaneous frequency (IF). Then, the fundamental wave and the principal slot harmonics (PSH) are extracted by TVSME, and their IFs are used to calculate the instantaneous rotational speed of the motor. As a result, a highly accurate and smooth rotational speed curve, which is valuable for performance evaluation and fault diagnosis of induction motors, can be obtained. The proposed method is evaluated by both an artificial signal and two experimental signals collected from actual motors. Results show that the instantaneous speed of induction motor can be accurately estimated under the condition of speed variation and multi-harmonic interference.

Speed Estimation of Multiphase Induction Motor Using Rotor Slot Harmonics With Limited SNR and Dynamic Load Conditions

Accurate and reliable speed feedback is vital for closed-loop control of multiphase induction motors (IMs), especially in harsh operating scenes like ship propulsion. High performance speed estimation is effective in getting rid of usual sensor failures, through the rotor slot harmonic (RSH) based method that featured for parameter mismatch robustness. However, the accurate and real-time low speed estimation through RSHs under limited signal noise ratio (SNR) and dynamic load conditions is still a challenge, mainly due to the extremely weak and nonstationary amplitude and closely distributed frequency properties of RSHs. In this paper, we investigate the performance limitations of low speed estimation using primary rotor slot harmonics (PSH) of multiphase IMs, whose detectability is ensured through an improved interior detection coil, under limited SNR and dynamic load conditions. A frequency shifting and an amplitude limiting zero-crossing detection algorithm are proposed for efficient extraction and processing of PSHs in full speed range, which effectively improve the estimation accuracy with reduced complexity. Finally, the proposed method is investigated on a nine-phase IM experimental platform within the whole speed range, limiting the steady and transient error respectively under 4r/min and 20r/min for closed-loop control.

A new approach of robust speed-sensorless control of doubly fed induction motor fed by photovoltaic solar panel

<span lang="EN-US">In this work, we presented the modelling and simulation of the electrical operation of a photovoltaic (PV) system adapted by an MPPT control, the latter is applied to the robust observer for the control of the speed without sensor of a double fed induction motor (DFIM).Our machine is powered by the PV system, where the chosen control is the direct field oriented control with sliding mode speed regulator is used for the control of this machine which is powered by two pulse-width modulation (PWM) voltage inverters, finally the speed estimation of induction motor with observer based dual feed in sliding mode is presented. The simulation results show the efficiency of the proposed method.</span>

A New SMO for Speed Estimation of Sensorless Induction Motor Drives at Zero and Low Speed

AbstractA novel sliding mode observer for speed estimation in sensorless induction motor drives at zero and low speed is proposed in this paper. First, aiming at the poor stability when the induction motor runs at low speed, analyze the reasons of the poor stability and a new feedback gains design method is proposed. Second, for the problem of ignored flux error in speed estimation which cause speed error at low speed, a new compensation method is put forward, which can improve the accuracy of speed estimation in the dynamic and steady state of the system. Meanwhile, a continuous function is given which can replace sign, to restrain the chattering problem of sliding mode observer. Detailed simulation results are given showing the operation at zero and low speed, the results prove the effectiveness of the proposed sliding mode observer. © 2023 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Neural network based Q-MRAS method for speed estimation of linear induction motor

The linear encoder for acquiring the speed information of the linear motor is costly and unreliable. Therefore, a sensorless control system without the speed sensor is designed in this paper. Based on the reactive-power-based model reference adaptive system (Q-MRAS) algorithm, the neural network is applied to replace the reference model in the traditional Q-MRAS algorithm. And the reference voltage instead of the measured voltage is used as the input. The proposed method is robust to noise due to the elimination of the current differentiation term in the traditional Q-MRAS algorithm, and it does not require a voltage sensor. Besides, the neural network is deployed in FPGA to achieve real-time calculation. Through the elaborate design of the hardware implementation, the fast calculation of the neural network is realized with less hardware resource consumption. The feasibility of the proposed method has been verified through simulation and hardware-in-loop tests.

An Improved PLL-Based Speed Estimation Method for Induction Motors through Harmonic Separation

The real-time speed estimation of induction motors (IMs) is important for the motors’ state monitoring and control. The utilization of rotor slot harmonics (RSHs) due to the inherent cogging effect is regarded as a promising way to realize the speed estimation of IMs. The key to the RSH-based speed estimation method is how to accurately and quickly identify the frequency of an RSH signal. However, as the RSH signal always consists of two side-frequency components that are adjacent to each other, it is actually improper to directly use the conventional phase-locked loop (PLL) method designed for single-frequency tracking. Furthermore, the form of the two side components in the frequency domain also leads to a significant amplitude fluctuation in the time-domain waveform of RSHs, thus resulting in the obvious frequency tracking errors of the conventional PLL method. In this paper, we proposed an improved PLL through harmonic separation to further improve the performance of the RSH-based speed estimation method of multiphase IMs, so that the dynamic tracking errors of PLL due to the reasons mentioned above can be significantly reduced. Simulations and experiments in a wide speed range were also performed, with their results presented as verifications of the proposed method.

Induction Motor Speed Estimation Based on Airgap Flux Measurement Using Hilbert Transform and Fast Fourier Transform

This paper proposes the rotor speed estimation of a squirrel cage induction motor fed by a sinusoidal power supply or an inverter based on the use of a Hall effect sensor installed between two stator slots of the machine. As well known in literature, inverter-fed induction motors usually contains a series of current harmonics and in case of rotor faults, such as broken bars, this operational condition becomes even more severe. The speed estimation has been extensively investigated for its use in control schemes, to compute output power or machine efficiency and particularly for fault diagnosis using motor current signature analysis. In this method, it is necessary an accurate speed estimation to prevent false positives and false negative indications. Therefore, the present research has been carried out by applying the Fast Fourier Transform and Hilbert Transform in the airgap signal measured by the Hall sensor, in order to estimate the rotational speed of the induction motor in a healthy condition and with broken rotor bars. This approach has been compared to the same signal processing techniques using the stator current phase, usually used for speed estimation in the state of the art solutions. The efficiency of this approach was evaluated from simulation and experimental tests, for motor running at distinct load torques, at very low slip conditions and considering a damaged rotor cage. The simulation and experimental results have shown a better accuracy with the measured or simulated speeds, using the airgap estimations when compared to those obtained from stator current processing.

Implementation of disturbance observer for sensorless speed estimation in induction motor

The use of speed sensors in induction motors is considered to be less effective because of the high price and diminishing reliability. Over time, a speed estimator was developed to increase the speed of the sensor. This paper describes the application of a disturbance observer algorithm as an estimator of the speed of an induction motor. In this case, the estimator is seen as an embedded system that only uses current information to measure speed of induction motor. To test the performance of the disturbance observer-based estimator, a comparison was made with the estimator based on the extended Kalman filter. From the experiment, it is found that the speed estimation using the disturbance observer has a smaller root mean square error in the low-speed operation than one of the extended Kalman filter, i.e. the root mean squared error (RMSE) value is below 4% in the range of 250 revolution per minute (RPM)–600 RPM.

Experimental evaluation for fluxes, currents and speed estimation of induction motor

Induction motor drive control and estimation is a wide subject. The market for variable speed drives has grown dramatically in the last few years. Manufacturers have recognized the importance of not only managing the speed or torque range, but also reducing power consumption. This necessitates the development of new control algorithms and schemes to include these solutions. Indeed, the speed estimate must be employed in one or more regions of the control scheme, depending on the control objective. This concept, as well as the most common speed estimation methodologies, is investigated. Currently, many tools can be used for the evaluation of the rotor speed without a speed sensor. By modern signal processing methods, it is possible to implement an estimation scheme with the possibility of monitoring currents and voltages. Therefore, in this paper, the concept of currents, speed and fluxes estimation based on the extended Kalman filter is proposed. By monitoring the ratio of the theoretical residual to the actual residual, the measured noise covariance matrix is recursively corrected online to make it gradually approach the real noise level. So that the filter performs the optimal estimation, improves the accuracy of the speed estimation. The effect of the load change on the currents, fluxes and speed estimation was also studied. Simulation and experimental results show that the proposed improved adaptive extended Kalman estimator has a strong ability to suppress random measurement noise. The experimental and simulation results prove the accuracy of the proposed scheme towards the state estimation of an induction motor at different load levels. It can accurately estimate the speed of the motor and has a good anti-error ability to meet the actual needs of the project.

SPEED OBSERVER FOR SENSORLESS ENERGY GENERATION SYSTEMS BASED ON FIELD ORIENTED INDUCTION GENERATOR

The paper presents a novel adaptive speed – rotor flux linkage observer for sensorless field oriented control of induction generators. The proposed solution is based on Matsuse observer structure to- gether with specially designed correction terms and utilize current measurement and calculated stator volt- ages for real-time flux and speed reconstruction. A special coordinate transformation is used to avoid non- linear parametrization in the right side of flux linkages differential equations. Adaptive observer is designed in two steps: at the first step nonadaptive flux linkage observer is designed under condition of speed meas- urement; at the second step adaptive to rotor speed version of the flux linkage observer is designed. Infor- mation about rotor speed for adaptive flux observer is calculated by developed speed observer. A second Lyapunov’s method together with adaptive control theory are utilized for observer’s correction terms synthe- sis and stability proof. Designed adaptive observer under persistence of excitation conditions guarantees local exponential estimation of constant rotor speed and flux linkage vector components of induction ma- chine. From the practical point of view persistency excitation conditions are met if rotor flux linkages are nonzero. Proposed solution investigated by simulations. It is shown, that developed adaptive speed observer provides asymptotic estimation of induction motor currents, speed and flux linkage components under con- stant speed conditions. For varying speed proposed observer provides estimation of required variables with a small dynamic error. Proposed observer can be used in energy generation systems based on induction generators as well as in sensorless induction motor-based drive systems with constant or slowly varying ro- tor speed.

Speed estimation of the three-phase induction motor with Volts/Hertz control using artificial intelligence techniques

This paper deals with the design and development of a prototype for speed estimation of a three-phase squirrel cage induction motor using Volts/Hertz control. The speed estimation was using an embedded electronic device with an adaptive neuro-fuzzy inference system. In this way, it is expected to increase the reliability of the rotor speed measurement. For the estimation, the currents and voltages that feed the induction motor were taken as input data to training an adaptive neuro-fuzzy inference system. Additionally, a Volts/Hertz control technique was used to test the operation of the estimator at different operating speeds, comparing the estimation with a speed sensor coupled to the machine shaft. The estimation was supported on a Raspberry Pi 3B hardware. The algorithms were developed using Simulink, which allows a graphical block interface that facilitates the understanding of the system. For the power stage, a multilevel converter was developed, thus, ensures a low total harmonic distortion.

Analysis of Non-Intrusive Rotor Speed Estimation Techniques for Inverter-Fed Induction Motors

Most non-intrusive induction motor (IM) efficiency estimation methods rely on the machine slip to compute the output power and the efficiency. To achieve the overall non-intrusive nature of the entire process, it is vital to utilize a reliable and non-intrusive rotor speed measurement technique in order to obtain the slip of an in-service motor. A number of rotor speed estimation techniques have been proposed in literature. This article focusses on the review and analysis of different techniques in terms of intrusiveness, relative accuracy, sensitivity and computational overhead particularly when the IM is fed by an inverter supply. An experimental accuracy and sensitivity analysis of some motor current and vibration-based techniques is carried out to check the accuracy trends reported in literature and the robustness of these techniques. Potential techniques for non-intrusive rotor speed estimation of inverter-fed induction motors are recommended.

A new stator voltage error-based MRAS model for field-oriented controlled induction motor speed estimation without using voltage transducers

A sensorless speed estimation method for performing the indirect field-oriented control (IFOC) of induction motors (IMs) is presented in the current research. The method uses the stator voltage as state variable but eliminates the voltage transducers. Traditional MRAS methods use two sets of equations to estimate the motor speed. However, the proposed system utilizes the q-axis current regulator proportional–integral (PI) control output $$ \left( {V_{\text{sq}}^{*} } \right) $$ in the reference model as a new Model Reference Adaptive System (MRAS) technique and compares this value with the estimated voltage $$ \left( {\hat{V}_{\text{sq}} } \right) $$ in an adaptive model. The method calculates the steady-state q-axis stator voltage in adaptive model, so, the calculation burden in the estimation loop is significantly reduced. Choosing the q-axis stator voltage as state variable removes requirement of the rotor parameters in calculations, and therefore, the system becomes resistant to the alteration in rotor parameters. Furthermore, the mentioned special calculation ensures the elimination of the need for flux estimation, so the speed estimation technique becomes resistant to integral and derivative calculation-based problems. The MATLAB/Simulink simulation results and experiments under various operation conditions verifies the effectiveness of the studied technique.

Improved double‐surface sliding mode observer for flux and speed estimation of induction motors

This study studies a double-surface sliding-mode observer (DS-SMO) for estimating the flux and speed of induction motors (IMs). The SMO equations are based on an IM model in the stationary reference frame. The DS-SMO is developed based on the equations of a single-surface SMO (SS-SMO) of IM. In DS-SMO method, the observer is designed through combining sliding variables produced by combining estimated fluxes of currents error. The speed is easily determined based on the pass of switching signal through a low-pass filter. Also, an optimal DS-SMO (ODS-SMO) is proposed to improve the transient condition by optimally tuning the observer parameters. To optimise these parameters, the particle swarm optimisation method is adopted. Moreover, an improved DS-SMO (IDS-SMO) is proposed to improve both transient and steady-state conditions, torque ripple and total harmonic distortion. Moreover, the proposed IDS-SMO has a stable performance under sudden load change and the low-speed region. Finally, the accuracy of the proposed ODS-SMO and IDS-SMO methods is substantiated through simulation and experimental results.

Reactive-power-based MRAC for rotor resistance and speed estimation in bearingless induction motor drives

The reactive power-based model reference adaptive controller (MRAC) is presented in this paper in detail to estimate rotor resistance online. This controller can maintain rotor flux orientation of bearingless induction motor (BIM) driven by indirect