Model Of Induction Motor Research Articles

Research on Speed Sensorless Control of Induction Motor Based on Back EMF

This article mainly uses the reduced-order model of induction motor (IM) to study the speed identification. Since the traditional voltage model (VM) and current model (CM) each have certain limitations, a general reduced-order model obtained by combining VM and CM is proposed for flux observation. This method is more conducive to analyzing system stability and determining gain, so that the entire induction motor vector control system reaches complete stability. In addition, for the full-order observer, according to the rapidity of current convergence, the back EMF can also be used to convert the full-order observer into an equivalent reduced-order observer. In this way, state feedback matrix can be avoided, which can greatly reduce the complexity of calculation and be more convenient to analyzing the stability of the system. Through the simulation of this novel back EMF reduced-order model, the feasibility of the system can be verified.

The Cluster Computation-Based Hybrid FEM–Analytical Model of Induction Motor for Fault Diagnostics

This paper presents a hybrid finite element method (FEM)–analytical model of a three-phase squirrel cage induction motor solved using parallel processing for reducing the simulation time. The growing development in artificial intelligence (AI) techniques can lead towards more reliable diagnostic algorithms. The biggest challenge for AI techniques is that they need a big amount of data under various conditions to train them. These data are difficult to obtain from the industries because they contain low numbers of possible faulty cases, as well as from laboratories because a limited number of motors can be broken for testing purposes. The only feasible solution is mathematical models, which in the long run can become part of advanced diagnostic techniques. The benefits of analytical and FEM models for their speed and accuracy respectively can be exploited by making a hybrid model. Moreover, the concept of cloud computing can be utilized to reduce the simulation time of the FEM model. In this paper, a hybrid model being solved on multiple processors in a parallel fashion is presented. The results depict that by dividing the rotor steps among several processors working in parallel, the simulation time reduces considerably. The simulation results under healthy and broken rotor bar cases are compared with those taken from a laboratory setup for validation.

Loss Minimization of Induction Motors in a Transient Regime

This paper presents a novel design of an energy optimization approach for Induction Motor (IM) drives. Differently from former optimal control studies, the proposed control strategy is based on a designed cost function given as a weighting sum of power and energy models. The problem to be considered is to achieve the loss minimization of IM drives for any possible constraints imposed by the machine power quantity, such as ramp inputs in accelerate and decelerate modes and during different torque levels. The suggested energy optimization strategy, using the concept of Rotor Field Oriented Control (RFOC), allows a low-order current-fed IM model by means of a high-gain current control loop, which considers the stator currents as new inputs to the model and the rotor flux as a main state variable. An optimal rotor flux trajectory is determined by an off-line algorithm based on an optimal closed-loop control problem resulting in the Hamilton Jacobi Bellman equation. The resolution leads to an analytical solution which is implemented to RFOC and performs loss energy minimization during transient speed. Aiming to check the validity of the proposed strategy, a comparison study is conducted between RFOC operating with the optimal rotor flux and RFOC using a rated flux norm. The simulation and experimental results obtained for a 1.5 KW laboratory IM demonstrate the effectiveness of the proposed strategy.

Extended Kalman filter based estimations for improving speed‐sensored control performance of induction motors

In this study, an extended Kalman filter (EKF)-based estimation algorithm is presented to improve the speed-sensored control performance of induction motors (IMs). The proposed EKF-based estimation algorithm is to simultaneously estimate the stator stationary axis components of stator currents and rotor fluxes, rotor angular speed, load torque including viscous friction term, rotor resistance and magnetising inductance in a single EKF algorithm without requiring any switching operation or a hybrid structure. In order to improve the speed-sensored control performance, the measurement/output matrix of IM model is extended by the measured rotor speed in addition to stationary axis components of the measured stator currents. Therefore, the proposed EKF algorithm uses the speed and stator current errors between the measured and priori estimation values in order to calculate the posterior estimation ones. For performance evaluation, the eighth order (proposed) EKF algorithm is tested by simulations and real-time experiments under challenging scenarios and compared with the developed sixth order EKF in real time. The obtained real-time results also show that the eighth order (proposed) EKF algorithm provides additional and improved estimations with the increased but feasible execution time in terms of the sixth order EKF designed in this paper.

Nonlinear Observer Design for Load Torque Estimation of Induction Motors

The paper introduces a design of a nonlinear observer for the estimation of load torque of induction motors based on the output of the stator currents. The observer is built in the synchronous reference frame d-q with three main steps. First, the nonlinear observer for the class of non-affine control systems is reviewed. Second, the induction motor model is written in an appropriate form as a non-affine control system with canonical form for the design of the nonlinear observer. The system state is composed of the stator currents, speed and load torque. Based on the stator currents, the rotor flux leakages are estimated via an open loop and used for the load torque observer. The observer is designed with a constant gain which is calculated by considering the trajectory of the rotor flux leakages. Both the load torque and rotor speed can be estimated by using the proposed observer. Finally, simulation and experiment are carried to validate the effectiveness and robustness of the proposed observer.

Noninvasive Measurements and FEM Analyses for Estimating the Rotor Bar-Lamination Contact Resistance

This research work investigates the phenomenon of interbar currents in induction motors equipped with die-cast aluminum cages. Flowing in the lamination and distorting the bar current distributions, the interbar currents cause additional stray losses as well as an increase of the joule loss in the cage bars. The contact resistance between the bars and the rotor laminations is the key modeling element for a correct prediction of the interbar currents and the related extra losses. The study presents a new noninvasive method to obtain a reliable estimation of the contact resistance. The proposed hybrid approach is based on a mix of experimental data and Finite Element method (FEM)-based simulation results. A reliable three-dimensional FEM model of a four-pole 15-kW induction motor with closed rotor slots has been used to investigate the impact of variable contact resistance on the interbar currents, rotor joule losses, and the voltage drops along the bars, opening a new perspective for this complex phenomenon and its impact on the stray losses. Finally, the proposed methodologies are critically discussed and the obtained results compared with other relevant research works.

Linear and nonlinear controllers of a solar photovoltaic water pumping system

This paper provided a comparative study between linear and nonlinear controllers of a solar photovoltaic (PV) water pumping system using an induction motor and a centrifugal pump. For linear controller, classical Perturb and Observe was selected to ensure the operation of the PV system at the maximum power point (MPP) and is combined with Indirect Rotor Field Oriented Control (IRFOC) based on a conventional proportional integral speed regulator chosen to control and to optimize the rotor speed. In second and third controllers, Backstepping and first order sliding mode controls were proposed for controlling the whole system. To regulate and optimize rotor speed in the nonlinear controller, all considered control techniques were combined with IRFOC in order to establish easy control laws. In addition, MPP was tracked by acting on the DC-DC converter and using its mathematical model for developing control laws. Maximum delivered power was used as reference signal for optimizing actual rotor speed. The controlled system is operated without mechanical sensors. Estimators of rotor speed and load torque were proposed based on the mathematical model of induction motor and centrifugal pump and using only available output measurements.. Simulation results were investigated and the effectiveness of the nonlinear proposed strategies.

Sensorless Direct Torque Control of the Six-Phase Induction Motor by Fast Reduced Order Extended Kalman Filter

In this paper, a simple extended Kalman Filter (EKF) controller for direct torque control (DTC) of a six-phase induction machine in all speed ranges is proposed. The aim of this paper is to decrease the execution time of EKF modeling of a six-phase induction motor. The proposed method is fast and can operate online. If the machine parameters are changed during the operation, the EKF algorithm is activated to find parameters used for controlling the motor. In low speed, not only the motor speed measurement but also the DTC of machine is difficult. The EKF model can estimate speed, flux, load torque, and stator resistance in low speed; thus, optimization can be performed in all loads and speed range. The proposed method increases the accuracy of DTC of the six-phase induction machine and decreases the computation cost of the system using the simplified algorithm. The simulation and experimental results verify the effectiveness and the robustness of the proposed method against parameter variations.

D-Q Mathematical Modelling and Simulation of Three-Phase Induction Motor for Electrical Fault Analysis

D-Q Mathematical Modelling and Simulation of Three-Phase Induction Motor for Electrical Fault Analysis

Backstepping sliding mode control of induction motor based on disturbance observer

In this study, combining backstepping sliding mode (BSM) and disturbance observer-based control (DOBC), a state feedback controller is designed to regulate the speed of induction motor (IM). First, a feedforward compensation method is proposed based on the rotor flux observer and BSM control to counteract the mismatched lumped disturbances. Then, a disturbance observer is established to estimate the overall effect of possible modelling inaccuracy, load disturbance and motor parameters variation in the IM model. Compared with the conventional vector controller, the proposed controller solves the problems of modelling imprecise, unknown load injection and parameter variation, and realises the speed tracking of IM with good performance. Finally, experiments are presented to verify the effectiveness and practicability of the proposed control strategy.

Comparison of BPN, RBFN and wavelet neural network in induction motor modelling for speed estimation

ABSTRACT This paper discusses the question of estimating a neural network induction motor speed. The neural network is trained in the relationship between stator currents and rotor speed. Rotor currents and speed are created using MATLAB from simulated model induction motor and from experimental real-time set-up using LABVIEW. With these two data sets, Induction motor is modelled using three neural network architectures, namely BPN, RBFN and Wavelet Neural Network, comparing the performance of each neural model in estimating speed. Results show the neural approach's ability to replace the speed sensor used in the closed loop speed control system to accurately estimate speed.

Bearing faults and broken bars simulation in an induction motor using an engineering tool

Industrial processes require reliable, safe, and continuous operation of electric motors. However, unexpected failures result in production losses, high emergency maintenance costs, damage to other related machines and prolonged shutdowns. Therefore, the development of failure analysis, detection and prevention systems is of high importance for the industrial sector. The following paper proposes the generation of a model of a squirrel cage induction motor in the software tool Simulink capable of simulating: i) broken bars and broken rotor rings, and ii) failures in the bearings of the motor, based on the Motor Current Signature Analysis (MCSA) technique which is a non-invasive method. Moreover, the Fast Fourier Transform (FFT) analysis is used to perform spectral investigation on the current to detect specific components that characterize faults in these conditions.

IMPLEMENT DIRECT TORQUE AND FLUX CONTROL (DTC) INDUCTION MOTOR DRIVE MODEL: A REVIEW

Direct torque control ( DTC ) is considered one of the modern control methods, which wildly used in industrial variable speed drive systems to govern behaviors of induction motors. The main objective of this paper is to introduce a comprehensive study of a conventional direct torque of three phase induction motors. Moreover, the paper also aims to enhance and improve the transient response of the conventional DTC by proposing a novel design of its switching table, which considered as an essential component of DTC control circuit. At first, Space Vector theory was implemented to derive a mathematical model of a threephase induction motor. Second, the model was simulated by using Matlab Simulink software due to its simplicity. The conventional DTC and proposed DTC were applied on the computer model of the motor at no-load and when the motor shaft is loaded respectively. It was observed from the results that the transient response of the proposed DTC is better than the response of the conventional one. The paper concluded with number of important results, which obtained from the computer model of the two DTC control methods. Ripple

유도 전동기의 턴쇼트 고장에 관한 다이나믹 모델 연구

An inter-turn short fault is one of the frequent induction motor faults. When the inter-turn short fault occurs, a closed-circuit loop is formed in the stator. Owing to the low impedance and coupled flux linkage voltage, a high fault current is induced in the closed loop. The high current may cause an electrical fire because of the overheated shorted wire from faults. To prevent sudden expansion of failure, a lot of diagnosis methods have been studied. In this study, dynamic models of induction motor with inter-turn short faults are developed. The proposed model is based on the deformed flux model to analyze effects from an inter-turn short fault. To verify the proposed model, a finite-element method (FEM) was applied. By using the proposed model, the inter-turn short fault can be analyzed without the complex simulation.

Erratum to “An Advanced Equivalent Circuit Model for Linear Induction Motors” [Sep 18 7495-7503

Erratum to “An Advanced Equivalent Circuit Model for Linear Induction Motors” [Sep 18 7495-7503

Predictive current control of a bearingless induction motor model based on fuzzy dynamic objective function

A control strategy for a bearingless induction motor (BL-IM) based on the fuzzy dynamic objective function is proposed in this paper. Firstly, based on the discrete mathematical model of the BL-IM, the stator current and flux linkage are predicted according to the given stator current and flux linkage, the objective function of model predictive current control (MPCC) is designed. Secondly, the fuzzy control algorithm is introduced in the objective function of the MPCC to dynamically assign the weighting factors before the current component on the d- q axis and the influence of the objective function on the performance of the BL-IM is analyzed under different weighting factors. By discretizing the rotational speed deviation Δ ω and rotational speed deviation rate, fuzzy reasoning is performed to obtain the optimal fuzzy dynamic function. Finally, the optimal fuzzy dynamic function is selected as the objective function of the MPCC to perform the simulations and experiments. The results show that the performance of the BL-IM under the MPCC strategy based on the fuzzy dynamic objective function is improved compared with the traditional MPCC and the vector control based on the fuzzy PID, due to its better dynamic and suspension performance. Meanwhile, the stability of rotor current component is enhanced.

A convex model for induction motor starting transients imbedded in an OPF-based optimization problem

Large horsepower induction motors play a critical role in the operation of industrial facilities. In this respect, the distribution network operators dedicate a high priority to the operational safety of these motor loads. In this paper, the induction motor starting is modeled analytically and in a semi-static fashion. This model is imbedded in a convex distribution system restoration problem. In this optimization problem, it is aimed to determine the optimal status of static loads and the optimal dispatch of distributed generators such that: a) the induction motors can be reaccelerated in a safe way and, b) the total power of static loads that cannot be supplied before the motor energization, is minimized. The proposed optimization problem is applied in the case of a distribution network under different simulation scenarios. The feasibility and accuracy of the obtained results are validated using a) off-line time-domain simulations, and b) Power Hardware-In-the-Loop experiments.

Vectorized Mathematical Model of a Slip-Ring Induction Motor

The paper deals with the modeling of a slip-ring induction motor. Induction motors are very often used in industry and their suitable model is needed to reduce control and operating costs. The identification process of self and mutual inductances of the stator and rotor, and mutual inductances between them in the function of the rotor rotation angle is presented. The dependence of each inductance on the rotor rotation angle is determined experimentally. The inductance matrix is then formulated. Taking the magnetic energy of the inductances and kinetic energy of the rotor into account, the Lagrange function is defined. Next, the motor motion equations are obtained. After making some algebraic transformations and using the dimensionless variables, the motion equations of electric circuits and of the mechanical equation are written separately in the forms facilitating their solution. The solution was obtained using the Simulink model for the stator and rotor currents in the form of vectors. The simulation was controlled by MATLAB script. The results of the simulation are presented in the form of basic variables time courses and compared with some values calculated with the use Steinmetz model of induction motor. The work is followed by two appendices, which contain procedures for determining the inverted inductance matrix.

Electrical–thermal modeling of a double-canned induction motor for electrical performance analysis and motor lifetime determination

In nuclear and chemical fields, canned motor pumps are one of the safest ways to pump dangerous fluids. The canned motor pump is a compact unit integrating a hydraulic part and an induction motor with a common shaft. The particularity of the motor is that two non-magnetic cans are inserted in the air gap for leak tightness reasons. This study is therefore motivated by the fact that on one side classical electromagnetic and thermal models are not applicable for the canned motor, and on the other side new European standards about electrical machines require the design of motors with higher efficiency. In this work, an analytical model that combines electrical and thermal approaches has been performed to determine both electrical performances of the canned motor and the stator lifetime through the prediction of the maximum temperature of the winding for different operating conditions.

Induction Motor Adaptive Backstepping Control and Efficiency Optimization Based on Load Observer

In this paper, an adaptive load torque observer based on backstepping control is designed, which achieves accurate load estimation where the load is unknown. Based on this, in order to reduce the loss of the motor at low load, a smooth switching strategy of rotor flux based on speed error is designed. According to the real-time speed error of the induction motor, the smooth switching strategy achieves dynamic flux switching. Firstly, when the uncertain load occurs for the first time in the recursive design, the adaptive law of the load is designed, and a novel adaptive load torque observer is obtained, which accurately estimates the uncertain load torque in real time. Secondly, the relationship between the loss and the rotor flux is established by analyzing the loss model of induction motor, and the optimal rotor flux is obtained. The smooth switching control strategy based on speed error is designed to realize the efficiency optimization of induction motor. Finally, the control strategy proposed in this paper is experimentally verified on the LINKS-RT platform. The results show that the proposed control strategy has excellent load disturbance attenuation performance and reduces the energy loss.