Search results for "Induction Motor"

Innovative Observers for Induction Motor Control

In this thesis the problem of designing observers and controllers for induction motors has been studied and thoroughly discussed using tools from the nonlinear system theory, both for analysis and control purposes. Useful techniques have been used to identify the machine parameters off-line. In the Introduction was dealt the design a control system for a drive of asynchronous machines that uses a voltage source inverter to generate the currents and voltages which carry the drive by making use of an observer of the state rotor variables. The used control algorithms is the \textit{field oriented control} (FOC). The model of the asynchronous induction motor is described starting from the mecha…

Online Fault Diagnosis System for Electric Powertrains Using Advanced Signal Processing and Machine Learning

2018

Online condition monitoring and fault diagnosis systems are necessary to prevent unexpected downtimes in critical electric powertrains. The machine learning algorithms provide a better way to diagnose faults in complex cases, such as mixed faults and/or in variable speed conditions. Most of studies focus on training phases of the machine learning algorithms, but the development of the trained machine learning algorithms for an online diagnosis system is not detailed. In this study, a complete procedure of training and implementation of an online fault diagnosis system is presented and discussed. Aspects of the development of an online fault diagnosis based on machine learning algorithms are…

Analysis of Stray Flux Spectral Components in Induction Machines under Rotor Bar Breakages at Various Locations

2018

Induction machines under rotor electrical faults have been subjected to intensive research over the years. It is not only the nature of the fault that makes it important to study, but also the differences observed regarding this fault's effect on the motor's conditions. One of these conditions is the rotor bar breakages at non adjacent positions, which has drawn the attention of researchers due to the false negative diagnostic alarms that may be caused. In this paper, a novel approach is presented aiming to reliably detect this type of fault condition. The proposed method is based on the analysis of specific subcomponents of the stray flux over time. The analysis is implemented on an indust…

State Space-Vector Model of Linear Induction Motors Including Iron Losses Part I: Theoretical Analysis

2018

This is the first part of a paper, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear Induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses and its off-line identification. This first part specifically treats the theoretical formulation of this model, which has been expressed in a state form, so to be, in perspective, suitably adopted for developing novel non linear control techniques, non-linear observers as well as electrical losses minimization techniques (ELMTs). Besides the formulation of the dynamic model in space-vector state form, a steady-state analysis is proposed, highlighting the combined e…

State Space-Vector Model of Linear Induction Motors Including Iron Losses: Part II: Model Identification and Results

2018

This is the second part of a paper, divided into two parts, dealing with the definition of a space-vector dynamic model of the linear Induction motor (LIM) taking into consideration both the dynamic end-effects and the iron losses as well as the off-line identification of its parameters. The first part has treated the theoretical framework of the model. This second part is devoted to the description of an identification technique which has been suitably developed for the estimation of the parameters of the LIM dynamic model accounting for both the dynamic end-effects and iron losses, described in the first part of the paper. Such an identification technique is strictly related to the state …

Descriptor-type Kalman Filter and TLS EXIN Speed Estimate for Sensorless Control of a Linear Induction Motor.

2014

This paper proposes a speed observer for linear induction motors (LIMs), which is composed of two parts: 1) a linear Kalman filter (KF) for the online estimation of the inductor currents and induced part flux linkage components; and 2) a speed estimator based on the total least squares (TLS) EXIN neuron. The TLS estimator receives as inputs the state variables, estimated by the KF, and provides as output the LIM linear speed, which is fed back to the KF and the control system. The KF is based on the classic space-vector model of the rotating induction machine. The end effects of the LIMs have been considered an uncertainty treated by the KF. The TLS EXIN neuron has been used to compute, in …

Extended Kalman Filter for sensorless control of induction motors

2010

This paper deals with speed and rotor flux estimation of induction motors via Extended Kalman Filter (EKF). The filter is designed starting from a discrete time model obtained by means of a first order discretization of the original nonlinear model of the induction motor (IM). In order to obtain accurate estimation of the above mentioned variables, the load torque is included into the state variables and then estimated, thus constructing a sixth order EKF. Experimental results are shown with reference to a closed loop sensorless control system, consisting of a 750 W induction motor supplied by a voltage source inverter, a cascade controller consisting of four PI control loops and the design…

Improving the speed estimation by load torque estimation in induction motor drives: an MRAS and NUIO approach

2021

This paper proposes the application of the NUIO inside a FOC induction motor drive for the simultaneous estimation of the load torque and the rotor speed. The idea is to estimate at first the speed with the current model in parallel with a reference model developed on the basis of the voltage model of the induction machine. Then, the estimated speed is given as input to a nonlinear unknown input observer (NUIO) to estimate the load torque. This estimation is then used to correct the previous estimation of the speed. Simulation and experimental results confirm the goodness of the method for an extended range of speed and different load torque, and they confirm the reduction of error in trans…

Diagnosis of inverter-fed induction motors in short time windows using physics-assisted deep learning framework

2019

This article presents a framework for accurate fault diagnostics in inverter-fed induction machinery operating under variable speed and load conditions within very short time windows. Condition indicators based on fault characteristic frequencies observed over the extended Park's vector modulus are fused with deep features extracted using stacked autoencoders to generate a multidimensional feature space for fault classification using support vector machine. The proposed approach is demonstrated in a laboratory setup to detect the most commonly occurring faults, namely, the stator turns fault, broken rotor bars fault and bearing fault with an accuracy > 98% within a short time window of 2–3 …

Speed control of double-sided linear induction motors for automated manufacturing systems

2014

The double-sided linear induction motor (DLIM) is acquiring a significant relevance in the application of automated manufacturing systems. For this purpose, the modeling, simulation and determination of the parameters of a double-sided linear induction motor is presented in this paper. Furthermore, the DLIM constant voltage/frequency speed control system for this application is here described. In order to verify the performance of the proposed system, a suitable test bench for the DLIM motor is set-up. From the good agreement shown by the comparison between measured and simulated results, it can be stated that the DLIM model and the speed control system is successfully validated. © 2014 IEE…